Her husband had been offered the chance to buy a dive bar in Park Slope. A place he loved, priced at what I can only describe as an almost criminal discount given the neighborhood, the foot traffic, and the fact that he basically lived there anyway. He was going to pass on it. He had a corporate job. It felt risky. He wasn’t sure.

I thought he was insane.

To make my point, I did what any reasonable person arguing about someone else’s life choices would do. I pulled up LoopNet on my phone and found a restaurant in my own neighborhood in Chicago. “Look!” I said, “even in my neighborhood, you can buy a restaurant for not that much money. Your opportunity is a steal. You’re crazy.”

I was right about him. I was also, apparently, talking myself into something I didn’t fully realize yet.

The restaurant sat there in my browser for longer than I expected, and definitely in my mind during hot showers.

Outside of the occasional fantasy, I’d never actually wanted to own a restaurant. I’m a product guy. I’ve spent my career building data platforms, managing product teams, doing technical due diligence on acquisition targets. Restaurants were not part of the plan.

But the feeling kept eating at me. pun intended :)

So I did what I do with anything that won’t leave me alone at 2 AM. I got curious. I asked for the financials. I also looked at the neighborhood demographics. I did the kind of analysis that sounds slightly absurd when you describe it out loud: I calculated the total purchasing power of the surrounding census tracts, estimated the discretionary spending fraction, divided it across the commercial corridor, and derived a reasonable revenue ceiling for any given business operating on that block.

The number I landed on was somewhere between $1 and $1.2m in annual revenue for a well-run establishment in that location. The restaurant I was looking at was doing somewhere around $400k. The only thing I thought was “how the hell is the annual revenue that low?!”

Looking at the opportunity

The previous owners were not bad operators. They were optimized operators. Careful about waste. Running a tight ship by the metrics they thought were important.

The problem is they were so optimized on cost control and waste management that they completely forgot to look at the upside. They had underpriced their menu relative to every comparable restaurant within 5 blocks. Not by a little. By enough that you’d notice if you ate there and then walked down the street and looked at the menu in the window.

And then there’s the service. The food was genuinely good. The space was beautiful. But the experience of being there, the pace at which food arrived, the tone with which staff talked to customers, the availability of items on the menu, all the invisible things that make a customer decide whether they’re coming back, those things were quietly eroding whatever the product quality was trying to build.

When I looked at the financials through that lens the story changed. This wasn’t a broken business. This was a business that had been optimized into a local minimum. The fundamentals of the location, the neighborhood, the product quality, were all there. The execution was the problem. And execution layers can be fixed.

I bought it. All cash.

But I want to be specific about one thing because it matters to how I think about running businesses. I didn’t hire someone to manage the restaurant. I brought in an operating partner, a good friend of mine who has a day job just as I do, whose compensation is entirely profit participation. No salary. 40% of profit at the end of the year, nothing otherwise. If the restaurant doesn’t perform, neither do we. I wanted someone whose incentives were identical to mine. That structure was a deliberate choice and it’s one I’d make again.

What the restaurant added was consequence. My money. My risk. Six or seven people whose employment depended on whether my thesis was right. A neighborhood that either had a good place to eat or didn’t.

Time to fix things up

The first year was humbling in ways I did not fully anticipate.

Revenue went from roughly $400k to $600k. By the end of last year we were tracking at $750k on a trailing twelve month basis. The neighborhood purchasing power thesis held up. The pricing adjustments worked. The service improvements worked. Customers started coming back and more importantly started coming back again after that.

What I did not anticipate was tariffs, which I realize sounds like something a person says when they need an excuse, but the COGs for a restaurant sourcing quality ingredients moved in ways my pro forma did not model. CapEx for back of house equipment was really important to focus on as far as re-investments go. Staffing hours scaled with volume because a two-three dollar sign restaurant in an affluent Chicago neighborhood has a service expectation you can’t shortchange without customers noticing immediately.

Net margin ended the year at 6-7% percent. Not the teens I wanted. Not yet.

The thesis was right, the diagnosis was right, and the execution mostly worked. The gap between what I projected and what happened was external and capital intensive, not fundamental. The business is now in optimization mode rather than turnaround mode, which means the margin expansion I wanted is still in front of me rather than behind me.

I’ve kept six or seven people employed through this. I’ve kept a genuinely good restaurant operating in a neighborhood that deserves one. These things matter to me more than I expected them to when I was doing the TAM analysis on my phone to win an argument about someone else’s bar and I’m really happy about that.

Making non-standard choices in life

I’m telling you this story because I’m still not entirely sure what to make of it.

I pulled up LoopNet to win an argument. I ended up doing a neighborhood TAM analysis, diagnosing an operational execution problem, negotiated a better price to buy the restaurant, and learning more about pricing psychology and customer retention in six months than I had in the previous several years of building software products. And holy shit, I actually bought the damn thing!

The framework felt familiar the whole time. The purchasing power calculation, the gap between what an asset is capable of and what it’s actually delivering, the diagnosis of whether a problem is fundamental or just an execution layer that can be fixed. I’d been doing versions of this in corporate settings for years.

What the restaurant added was consequence. My money. My risk. Six or seven people whose employment depended on whether my thesis was right. A neighborhood that either had a good place to eat or didn’t.

I find myself increasingly curious about where else this pattern shows up. Businesses with sound fundamentals and broken execution just under the radar of what PE wants to deal with. Things that are worth more than they’re currently delivering, if someone is willing to ask the right question and then actually do the work. That curiosity turns out to travel pretty well.

I ended up down that rabbit hole by another completely unrelated topic - The Russo-Japanese War of 1905. Don’t worry, this isn’t my Roman Empire or something, but a while ago I was performing my duty as a tech bro by listening to the Dwarkesh Patel podcast where a recurring (and freaking fantastic!) guest, Sarah Paine, was back to talk to everyone through a lecture on early 20th-century Russian/Japanese conflicts.

She does such a great job with these because she makes me feel way less like a pompous humanities douche and more like someone who just wants to know things for the sake of knowing things. Because its good (and fun) to know things.

Anyway, a big part of that lecture covers the Russo-Japanese War, its origins, outcomes, and why it ended the way it did. She’s quick to admit she might not have all the answers, but she offers strong evidentiary reasons for historical events. A very small (like 45 seconds) piece of the lecture touches on how both nations financed their ships, railroads, and military campaigns. She explains here that Japan’s war loans came from private Western institutions, with interest rates tied to their military performance. She moved on, but I thought, “wait....hold up. You can’t just say that and move on like it’s totally normal.” She can, obviously, since this is her lecture, but...I can press Pause just as easily 😛

Now, we could go into a lot of different directions with today’s post, but I’m going to constrain it to three things:

1. How did Tsarist Russia and Japan go about building their war-fighting “products” for the conflict?

2. How did State Capacity (the government’s ability to make, run, and do things) in either situation factor in?

3. How should we think about State Capacity in the US today? (Spoiler: It’s not a war-fighting example)

Russian Railroads!

The Russian Empire, much like Russia today, relied heavily on railroad infrastructure. Most of this was in the western parts of the country, with less in the east near Japan. However, that was starting to change with the Trans-Siberian Railway, but its last stretch wasn’t even finished until the very end of the Russo-Japanese War—a key factor in the war’s outcome.

Despite significant internal taxation, it wasn’t enough. By 1900, Russia was the largest foreign debt holder in the world

Their naval fleet was largely supplied by the French (who were allies, both aiming to contain Germany).

How could the Russian Empire pay for this?

(This is a worthwhile tangent, but if you don’t care feel free to skip this part.)

They lacked the internal capacity to finance their naval fleet, railroads, and other major infrastructure. So, they borrowed. A lot. From the French people.

Despite significant internal taxation, it wasn’t enough. By 1900, Russia was the largest foreign debt holder in the world, with French investors owning 80% of foreign government debt. This heavily influenced both buying decisions and geopolitical alliances. The Russians wanted State Capacity (a phrase we’ll focus on today) to do a lot of heavy lifting. They’d do design and technology transfers to build things in-house at the government’s direction and control and culturally, it was important to have that centralized control. To be clear, this isn’t good or bad in and of itself and it’s a theme we’ll focus on today.

So with all the borrowing from Europe, it’s no wonder that most of the Russian Navy were essentially vessels supplied by or the licensed designs of the other European nations and a secret purchase of a submarine from the US. Russian debt products were issued by in French, German and Dutch capital markets. With all this money and sourced componentry, they spent a lot of effort to industrialize the western parts. While the leaders at the top were a little wonky, a big part of all this Capex was under the stewardship of Sergei Witte, the finance minister at the time. He’s a whole writeup on his own and I can’t put y’all through another tangent so let’s move on to Japan.

Japan’s the Underdog

Like we talked about last week, a nation’s long-term sovereign debt (government bonds) is its most essential product—a promise to pay future investors, whose valuation is the market’s real-time assessment of national trust. Its serviceability depends on reliable revenue and a sensible budget. Sounds simple, but history (and today) shows countless examples where this fails. Japan offers a fascinating case of self-reinvention.

Japan saw what happened to China and realized they needed to avoid that outcome at all costs.

In the late 1800s, a big thing that started to happen around this time was the Meiji Reformation. I intellectually knew about how Japan changed it’s government to govern more similar to Western institutions (thank you bill wurtz), but things were not that easily accepted within Japan. There was a huge cultural resistance to selling “western institutions” to the Japanese people UNTIL this war broke out and Japan started to get some wins.

Japan saw what happened to China and realized they needed to avoid that outcome at all costs. (We’ll conveniently ignore the first Sino-Japanese War that happened a few years earlier) So they just outsourced everything to start with. This is a very different approach to State Capacity than the Russian Empire. Japan didn’t pretend that it could grow its industrial capacity overnight. So they went out and bought literally the best of the best war-fighting products for their Navy, mostly from the British and the Italians. They then spent the following years building out their domestic capacity, but that wasn’t their main objective. So now everyone’s got their fancy ships and trains. Time for war, I guess?

The War That Re-Rated the Financial Products

So a lot of stuff went down during the event, but the Russo-Japanese War served as a brutal market stress test for the sovereign debt products of both empires. At the end, it was a dramatic Re-Rating of their bond value by external investors.

• Tsarist Russia’s Downgrade: Despite its larger economy, military defeats and rising social unrest (especially the 1905 Revolution) exposed Russia’s fragile institutional structure. The social risk became a financial liability. Investors realized the state’s internal capacity to manage crisis was low. The value of Russian debt fell because the underlying product was too unstable. They then had to borrow even more from France just to fulfill their existing debt burden, which was already rather high.

• Meiji Japan’s Upgrade: Japan, despite its smaller initial reserves, executed the war with really good fiscal and military discipline. Its ability to manage logistics, fight effectively, and impose new taxes proved its execution capacity was high. Its product was quickly upgraded by American and British financiers, allowing it to raise the critical foreign capital needed to finish the war.

While the war ended with objectives achieved before Russia could fully deploy troops via the Trans-Siberian Railway, the lesson is clear: The financial value of an organization—be it a company’s stock or a country’s bond—is determined not just by its size, but by everyone’s perception of its internal capacity to execute under stress. This is pretty helpful context to keep in mind for life in general.

Diving into State Capacity

We’ve talked a lot about financial engineering on this blog. While it’s commonly associated with how Private Equity funds do “Value Creation,” it can swing the other way, too. In the West, we often view State Capacity with disdain; it’s a punch line I’ve used countless times when something was “good enough for government work.”

Meiji Japan, however, was different. Its approach was much like the industrial policy-making seen in China today and South Korea decades ago.

The government actively invested in establishing and operating industries vital for modernization, known as “model factories” (kan’ei kōjō). Similar to Tsarist Russia, this involved technology transfers. After purchasing the “best of the best” products globally, Japan aimed to build its own capacity for maintenance and repair. The purpose was to introduce Western technology and best practices. These transfers included shipbuilding, railways, telegraphs, and advanced textiles. These choices stemmed from a clear nationalistic mission that transcended private interests—a condition that no longer exists in that extreme form today, but which we can learn from. Once stable, the government typically sold their assets in these industries to wealthy private businessmen at low prices.

Many of those companies still exist over a century later, like the Mitsubishi Corporation. While private, these companies act very differently from their American, British, or Russian counterparts. They weren’t just an excuse for individuals to amass wealth by acquiring conglomerates cheaply from the State; they were a product of national development. Times are different, especially globally, but there’s a clear yearning for domestic or localized priorities in many parts of the West again. The real lesson here is about what matters most to the nation as a whole, and how best to ensure citizens get the best outcomes. Not everything is deterministically good or bad and the sheer contrast between Japan’s approach to Tsarist Russia shows that. Before I dive deeper into this, I want to offer a completely different, and surprisingly rare, example from the United States.

Blurring the lines between government and private entities

So here’s the counter argument: what matters most is the willingness to accomplish difficult or complicated things. We often hear that the profit motive makes private enterprises more efficient than governments, but I don’t think that’s always the case. We’ve all seen bloat, process as a proxy for the obvious, and political silos hinder progress in most private enterprises from startups to large corporations. So, is there an example of something that side-steps this whole debate, not only works well, but has endured for a really long time?

Turns out, my hometown of Irvine, California, is a pretty rare bird. It’s one of those unique planned cities in the U.S. that was mostly privately developed, yet with a cohesive, village-oriented design and a municipal structure that’s really worth thinking about.

This ad from the 1980s is hilarious to me.

For a long time, The Irvine Company essentially was the planning authority, controlling nearly all the land. This is where a “state capacity” mindset gets applied by a private entity: deciding where to place parks (most homes are within a ten-minute walk!), and ensuring development was self-financed. Roads, sewage, schools – much of it paid for by capturing the increase in land value that resulted from its own investment and planning.

Even though Irvine is a fully functional municipality with a mayor and city council, The Irvine Company remains the most powerful actor. It’s the largest taxpayer and landowner, owning huge portions of commercial centers and acting as the city’s private infrastructure arm for major growth. This structure means the city itself needs to put up less capital.

Growth is a collective agreement, and The Irvine Company understands you can’t just build for a quick buck; enduring value, brand, and sustainable infrastructure are key to the long-term appreciation of homes.

Of course, there’s tension, especially with longtime residents wanting more control. Yet, The Irvine Company has largely proven it can meet the needs of those who rely on it, whether customers, employees, or institutions. This blurred line between private entity and government body is fascinating. It offers a healthy alternative to the often unnecessarily bifurcated U.S. debate about what governments are good for versus what private companies should do.

The proof is in the pudding: Irvine has been financially self-sufficient for most of its history, and residents enjoy some of the best public schools in the country. This all stems from a village model that sustainably offers homes and the corresponding services people actually want – like a nearby shopping center, school, or community center you could theoretically bike or walk to. (Though, let’s be real, unless you’re retired or a kid, no one’s really walking that much in Irvine!)

We live in a world where our coworkers (temporary or permanent) can be from anywhere in the world. This is true for sectors like agriculture and automotive manufacturing just as it is for tech. Understanding how their home countries deal with crises gives us a way to connect with them, but also a keen understanding of how they may culturally view risks, tradeoffs, and eventually make decisions in a room with you when you’re building, buying or selling a product. So we’re going to continue to take a detour from AI hype and focus on how countries sell sovereign products, through the lens of the global Covid crisis.

NOTE: I wanted to make it clear that a ton of important people and decisions had to be in place for us to weather the Covid crisis. My wife is in healthcare and when we were in the Bay Area in California, she had a pretty up close look at the harsh realities of Covid with her geriatric patient population.

Today, however, we’re going to look at a very macroeconomic thing and we’re going to compare how the US dealt with it and compare it to India, China, and Kenya. Each of these nations offer us a different approach to weather the storm, and it’s always helpful to see what we can learn from it.

These nations represent very different aspects of human experience around the world. Going into 2020, they all had different tools and levels of maturity in their economies to deal with Covid. For the US, this was something they hadn’t dealt with in a century. For Kenya and India, this was a real test of their ability to deal with a non-military crisis that affected their entire nation. We’re not going to use any country as a benchmark since no one really got everything right and there are lessons to learn all around.

Sovereign Financing 101

Before we dissect how each country handled the economic fallout, let’s cover the basics: how governments actually get their hands on money when they need it. Remember my mantra, “Everything is a product to someone”? Well, even a nation’s need for capital is a product, meticulously designed and sold.

When we talk about how countries financed their COVID-19 responses, we’re really talking about how effectively they designed and “sold” these financial products, and who was willing to buy them.

When a country needs to raise serious cash – whether for infrastructure, social programs, or, say, a global pandemic – it essentially sells two main “products” in this market: sovereign bonds and syndicated loans.

They break down a bit differently:

• Sovereign Bonds: This is like a country issuing notes to thousands of investors around the world similar to your local city or state doing the same thing. Private investment banks step in as the intermediaries. They act as underwriters (buying the bonds from the government, guaranteeing the capital, then reselling them), advisors (telling the government when and how to sell), and marketers (using their global networks to find buyers). It’s a complex dance, but it’s how governments tap into that vast global pool of money. And by the way, this has been going on forever, its not some new thing.

• Syndicated Loans: Sometimes, a single bank can’t lend enough, or the risk is too high for one institution. That’s when a group of banks pools its resources to offer a giant loan to a nation. One or more banks act as the lead arranger to do the paperwork and coordinating activities, inviting other folks to join the “syndicate.” This is particularly common for developing countries or emerging markets that might not have easy access to the big bond markets. Why? The trust isn’t there. This is going to be a recurring theme today.

So, when we talk about how countries financed their COVID-19 responses, we’re really talking about how effectively they designed and “sold” these financial products, and who was willing to buy them.

The Pre-COVID Starting Line

Going into 2020, our four contenders weren’t all starting from the same place. Each had a unique financial “tool kit” and a different level of economic maturity.

• The United States: Wielded the the global reserve currency. This meant its deep capital markets could tap into demand from literally the entire world.

• India: Boasted a massive domestic savings pool and a growing, but still maturing, financial market. It largely relied on its own internal strength.

• China: Operated with a highly state-controlled financial system, immense national savings, and strict capital controls, giving the government significant direct leverage.

• Kenya: Faced significant external reliance, a much smaller domestic capacity to absorb debt, and a heavy pre-existing debt load, severely limiting its policy options.

Weathering the Storm

Now, let’s see how these different starting positions and financial strategies played out when the pandemic hit.

The United States: The Global Reserve Currency Advantage

The U.S. didn’t just weather the COVID-19 storm; it played a completely different game, leveraging its unique superpower: the global reserve currency.

Unlike many other nations, the U.S. fiscal response was defined by massive, direct cash injections straight into the pockets of its citizens and businesses. Most working-age Americans know about this, so this will for the younger audience and the non-Americans.

We’re talking:

• Stimulus Checks: Direct payments sent to most Americans.

• Enhanced Unemployment Benefits: A significant weekly boost to unemployment insurance.

• Paycheck Protection Program (PPP): Forgivable loans designed to keep small businesses afloat and employees on payroll.

The goal was clear: there was no time to be thoughtful, just pump money directly into people’s and companies’ pockets and keep the economy from seizing up.

A Flood of New Money Comes In

This direct injection had a fascinating effect on household savings. Like in India, consumption opportunities vanished during lockdowns, leading to “forced savings.” But crucially, in the U.S., household disposable income actually increased for many, especially in lower and middle-income brackets, thanks to all that government cash. This created a massive glut of new money, but the bigger problem was the absolute lack of cultural norms for building up savings.

And what did Americans do with it? Much of it went into bank deposits, sure. But we also saw an unprecedented and speculative retail investor boom. With zero-commission trading apps and time on their hands, many dove into the stock market, famously fueling the “meme stock” phenomenon (think GameStop, AMC, etc). Others poured money into crypto. For those stuck at home, it was less about conservative saving and more about actively chasing returns.

Because the U.S. dollar is the world’s reserve currency, foreign central banks, sovereign wealth funds, and international investors have a structural, almost mandatory, need to hold dollar-denominated assets, primarily U.S. Treasuries.

Debt Absorption: The Fed and The World

This is where the U.S. truly stands apart. The massive issuance of U.S. Treasury bonds wasn’t just absorbed by its own citizens; it was absorbed by a diverse global audience, supercharged by the Federal Reserve. Because the U.S. dollar is the world’s reserve currency, foreign central banks, sovereign wealth funds, and international investors have a structural, almost mandatory, need to hold dollar-denominated assets, primarily U.S. Treasuries. The U.S. effectively outsourced a large part of its crisis financing to the global system – a phenomenon people refer to as the dollar’s “exorbitant privilege.“

India: Self-Reliance and Accidental Savings

If the U.S. leveraged its global financial superpower, India’s story is one of resilience and the quiet strength of a nation that largely borrows from itself. There were no “shock and awe” direct payments on the same scale; instead, India relied on its vast domestic savings pool and a robust financial system to absorb an unprecedented surge in government borrowing. I want to remind people that Covid’s Delta variant hit India hard. There isn’t a person anywhere in India or a friend/family member around the world who didn’t see someone close to them get hit or unfortunately pass away from Covid during this time.

India’s fiscal response was more focused on providing a safety net and supporting vulnerable populations rather than direct, broad-based income replacement. Think:

• Free staple grains for the poor.

• Credit guarantees for small and medium-sized enterprises (SMEs) to keep them from collapsing.

• Some smaller, targeted cash transfers to vulnerable parts of the population. The goal was to cushion the immediate blow and prevent widespread destitution

Now, here’s where it gets interesting, and it’s a story many of us might miss if we just look at headlines. While the average Indian citizen didn’t suddenly start buying government bonds in droves, household savings did skyrocket. Net financial savings of Indian households surged to a multi-decade high of 11.5% of GDP in the 2020-21 fiscal year.

Iit was a direct and rational response to the crisis:

• Forced Savings: During severe lockdowns, people simply couldn’t spend money. Malls, restaurants, travel – all shut down. Income that would normally be spent had nowhere to go and accumulated in bank accounts.

• Precautionary Savings: The pandemic brought immense uncertainty about future jobs, income, and health. Fear of the unknown prompted families to save aggressively as a buffer against future shocks.

A portion of these savings also flowed into mutual funds, particularly debt funds, which are significant institutional investors in government bonds. The Reserve Bank of India (RBI) was a crucial stabilizing force. Their bond-buying programs (OMO, G-SAP, and a couple of others that I can’t immediately remember) injected liquidity and stabilized yields, preventing a market collapse.

So, while it felt like the country was “borrowing against itself,” it was actually the collective, crisis-driven decision to save that temporarily swelled the national savings pool.

The government didn’t (and honestly, couldn’t) simply force banks to absorb all the new debt via high Statutory Liquidity Ratio (SLR) mandates. The absorption during COVID-19 was a true market response kind of by accident, but channeled efficiently by a robust domestic financial system.

India’s experience demonstrated the immense strategic advantage of a high domestic savings rate and its ability to self-finance even in the face of an unprecedented crisis.

Turns out, a nation’s most powerful financial tool isn’t always a fancy global mechanism, but the accidental, collective prudence of its own people, born purely out of necessity.

The problem in place right now is that there is a lot more borrowing activity than ever before in India, coming out of the pandemic. Much like the US isn’t used to saving well, non-agricultural parts of India aren’t really used to being stewards of revolving credit or larger forms of debt while sustaining limited savings. But...that’s a whole post on its own :P

China: The State-Directed Production Machine

If the U.S. was about stimulating demand and India about leveraging domestic savings, China’s response was a heavy focus on state-directed production. By now, you can see how cultural bias is turning up in these policy choices. It wasn’t about giving money directly to citizens or relying on organic market forces; it was about the state’s absolute power to get factories humming, infrastructure built, and the economy roaring back through sheer force of will.

China’s fiscal stimulus was almost the mirror image of the U.S. There were no large direct cash handouts to citizens. Instead, the focus was heavily weighted towards the supply side as soon as the first “Zero Covid” shutdowns turned off (and before the next wave of shutdowns came in):

• Tax Cuts and Fee Reductions: Businesses, especially manufacturers, received significant relief.

• Massive Infrastructure Spending: The government explicitly ordered state-owned enterprises (SOEs) to accelerate projects like high-speed rail, 5G networks, and energy grids. The aim was to create jobs and maintain production capacity.

• State-Directed Lending: Financial institutions were guided to lend to corporations to ensure they didn’t collapse, keeping the industrial engine running.

The philosophy is pretty clear: control the virus, then stimulate production. Keep the factories open and people employed, and the economy will recover through exports and investment.

China already boasts one of the world’s highest household savings rates, partly due to a less robust social safety net. The pandemic didn’t just amplify this; it created a unique psychological dynamic. The strict, sudden, and often unpredictable “Zero-COVID” lockdowns meant families saved by default. Imagine not knowing if your city would be the next to shut down for months, cutting off income and access to essentials. We’re not going to go into it today, but much of Chinese household wealth was tied up in real estate and that was just turning into a huge issue for them. The result was a population that, despite an economy focused on production, was hoarding cash, unsure of what the next lockdown might bring.

When China needed to borrow big, their state-controlled system basically just funded itself.

Think of it as a super-efficient, almost circular flow: the government issued debt, and then their massive state-owned banks, like ICBC or Bank of China, were simply told to buy it up (this is what India didn’t do, by the way). The central bank (the PBoC) made sure those banks had plenty of cash, and strict capital controls kept money from escaping the country. Whether you like it or not, it is kind of crazy they could get away with the last bit. With nowhere else for all that domestic savings to go, the government always had eager buyers for its bonds. (Side note: Starting this year, looks like China is starting to ease up a little bit on its capital controls, so that’s gonna be pretty interesting to watch)

In summary, China’s pandemic response was a testament to their power of absolute state control. It used its command over production, its financial institutions, and its citizens’ savings (both voluntary and involuntary) to orchestrate a recovery focused on supply, all within a tightly managed, largely closed financial loop. But you’ll be left with a population in constant fear of whether they can walk out of their home next week or not, and that’s not fun. It’s a stark contrast to the market-driven approaches of the West, offering its own unique lessons in crisis management.

Kenya: Crisis Management Under Acute Constraint

Forget economic philosophies for a moment. If the U.S. and China had big strategic choices, Kenya’s pandemic experience was pure crisis management under extreme pressure.

They were caught in a desperate balancing act: battling a public health emergency and trying to stave off a sovereign debt crisis all at once. Their options were incredibly limited, which meant relying heavily on international financial institutions just to keep going.

While wealthier nations debated spending trillions, Kenya was hit by a brutal “fiscal scissor”: government revenues collapsed just as spending needs soared. Tourism and horticultural exports were decimated by global lockdowns and disrupted supply chains. This left the government with dramatically less money.

Kenya’s stimulus was a mere fraction of the size of the other nations we’ve discussed, focusing on immediate, critical relief:

• Temporary tax relief (e.g., reductions in VAT and income tax for lower earners).

• Modest cash disbursements to the elderly and most vulnerable populations.

• Some credit guarantees for small and medium-sized enterprises (SMEs) to prevent a total economic collapse.

• Emergency healthcare spending to bolster a struggling medical system. There were no massive direct checks or grand infrastructure projects. The government simply lacked the fiscal capacity. The primary goal was to cushion the immediate blow and keep the lights on, not to stimulate a roaring recovery.

M-Pesa to the rescue…sort of

Unfortunately, while households in developed nations and even India saw savings rates spike, the vast majority of the Kenyan population experienced the opposite: For millions, especially those working in the informal economy (street vendors, casual laborers, small-scale traders), lockdowns meant a complete loss of income. They were forced to draw down on whatever meager savings they had accumulated, simply to survive day-to-day. M-Pesa, a fantastic mobile money platform, became a bigger piece of national infrastructure. The Central Bank of Kenya (CBK) waived fees on small mobile money transactions, which proved invaluable. This made it super easy for people to send aid to each other, like relatives in the city sending money back to their villages. It also meant folks could pay digitally since cash was too risky to handle. Though the middle class and up were in a better spot with savings, the story of the Kenyan household was one of hardship, resilience, and reliance on community and family support.

And when you take things to the national level, it gets really easy to see how difficult the decisions are to make. Kenya does have a domestic bond market, and local pension funds and banks do buy government debt denominated in Kenyan Shillings. However, this market is nowhere near large enough to absorb the kind of deficit the crisis created. Attempting to do so would have sent domestic interest rates soaring, crushing the economy.

Lifelines were a matter of life and death

Kenya simply couldn’t self-finance its way out. Their most critical calls went to Washington D.C., securing emergency financing from the International Monetary Fund (IMF) and the World Bank. Getting an IMF program wasn’t just about the cash; it was a vital signal of confidence to all other international creditors, essentially saying, “Kenya’s taking the necessary steps, they’re not about to default.” It was a true lifeline. On top of that, Kenya got a temporary break from paying some debts through the G20’s Debt Service Suspension Initiative (DSSI), freeing up crucial cash. Trying to borrow from private international markets (like issuing new Eurobonds) was just too expensive and risky, with interest rates that would have crushed the struggling nation.

In conclusion, Kenya’s experience starkly illustrates the profound inequalities of the global financial architecture. It lacked the monetary sovereignty of the U.S. and Japan, the state-directed capacity of China, and the vast domestic savings pool of India. Its response was a testament to navigating a global storm with limited tools, where every policy decision was a difficult trade-off, and survival depended heavily on the support and confidence of the international financial community.

We are way past “normal,” but aren’t doing much about it

We see how nations, from global superpowers to emerging economies, navigate unprecedented crisis. But this isn’t just a history lesson for economists. It’s a stark mirror reflecting the strategic choices we, as product builders, engineers, and executives, face every day in our companies – especially now, as the illusion of a stable “normal” has been shattered.

The true “boring” takeaway here—the one that really matters—is about trust as the ultimate accelerant for value creation, and why we must now pivot from optimizing for a past stability to building for an uncertain future.

Trust is Your Ultimate Capital for Big Ambitions

Looking at these national stories, it’s clear: trust isn’t just a bonus; it’s the core ingredient that lets you do big, ambitious things. The U.S. relies on global trust in its currency. India taps into deep domestic trust in its financial system. Nations without that trust? They’re stuck paying exorbitant costs, with severely limited options, always playing defense. For companies, it’s the same deal. Consistently earning and keeping trust—from customers, employees, and investors—is what gives you the freedom to innovate, take smart risks, and really create value. Without it, you’re constantly battling headwinds, your choices are narrow, and every move is under the microscope.

Speedrunning to develop high-speed rail or a flashy infrastructure project for optics, without genuine underlying trust and capacity, is eerily similar to a legacy company rushing to be “AI-first” within a year, driven by hype rather than deep product conviction. It’s often a shortcut that bypasses the real work of building enduring value.

Financial Engineering was a Luxury

For decades, in a context of relative global peace and predictable societal structures, we had the luxury to pursue agendas heavily focused on financial engineering.

Companies could do things like EBITDA-optimization and margin expansion, often by cutting internal know-how, slowing expensive new feature development, and purging what seemed like “inefficiencies.” These decisions, while impacting internal capacity, felt acceptable because the core aspects of society— global supply chains, geopolitical stability, public health—were largely constant. Then came COVID-19, and that underlying stability vanished overnight. It wasn’t just a market blip; it was a non-militarized test of our ability to adapt to a radically changed environment. We largely kept things going as if we were going to snap back to “normal.” But as our national comparisons show—from Kenya’s precarious reliance to India’s internal fortitude—the world didn’t go back to normal. We’re still dealing with the aftermath. The structural vulnerabilities, previously masked by calm, were laid bare.

A Focus on Structural Resilience and Positive-Sum

So, if “normal” isn’t coming back, the next five years will present every company with its own “non-militarized test,” demanding a redefinition in a market that might irrationally expect unsustainable financial performance. This isn’t just about avoiding short-term stock bumps; it’s about recognizing that the luxury of pure financial engineering is over.

Anyone who takes their eye off the ball by fixating solely on cost controls, instead of pushing the upside through real value creation (and most importantly, communicating it well to the market on their own terms) is going to get a painful lesson. This means a re-focus on structural issues:

• Investing in core product engineering: Building deep, internal know-how and capabilities, rather than externalizing problems or cutting crucial development.

• Cultivating genuine trust: With employees (who hold that know-how), customers (who drive long-term revenue), and investors (who seek sustainable growth).

• Building Antifragility: Designing systems and strategies that not only withstand shocks but benefit from disorder. We’ve talked about these items in the past. This is the path to creating a bigger pie for everyone. It’s about understanding that the big commercial picture now demands a focus on fixing our structural issues—both within our companies and in the broader economy—because the stable context that once allowed for less rigorous approaches is simply no longer guaranteed.

PS - I only mentioned AI like twice in this whole writeup because while it might be a potential driver for change, it is not a primary or monocausal driver for anything I am talking about.

Programming Note: I want to make sure if you click on this article, it’s going to be worth your time. When everyone and their puppy is a thought leader on LinkedIn with absurd takes like ‘Cursor was the fastest to $900M in Revenue! MAKE NO MISTAKE. THIS IS THE NEW NORMAL. If you’re not crushing it with just 10 engineers and agentic workflows, you’re not getting it yet.’ - clearly the barrier of entry for commentary and takes has lowered quite a bit.

My core thesis often gets challenged enough by new AI developments that I have to change at least 20% of the content every few days. Annoying? For sure. But it ultimately means you’re getting a perspective that’s been truly wrestled with and is as current as possible, not just a quick take.

“...MAKE NO MISTAKE. THIS IS THE NEW NORMAL...”- ugh 🙄

--awkward segue time--

Aaaaand speaking of barrier to entry, there was a pretty big shift in the 2010s for enterprise software. In 2011, the mantra was something like “These SaaS products are great for small companies, but make no mistake, large corporations with their complexities require heavily customized software from a proven reliable player with decades of experience.” This is when Oracle, SAP, and the like were the only game in town. Cut to 2016 where the story was “SaaS products will break down the monolith of heavily custom enterprise software that is expensive to maintain in-house or with a vendor.”

Pendulum shift

Now we’re slowly shifting back (albeit with more viscosity than many expected). The barrier to do customization until recently was quite high. As any Sr. Engineer if they were asked to build a custom integration for any poorly documented 3rd party API (which is a lot of them out there), they’d just have said “I’d rather just build our own thing in-house because integration will take just as long” and you’d either not do that thing at all or end up in a pretty sticky situation. Additionally, cron jobs used to be mostly for DevOps or Networking workflows. Event-driven architectures used to be for middle tier stuff that hardly saw the light of day. Then came self-hosted (often open source) Internal Developer Platforms. RedHat has a good overview for what these are. These things gained pretty quick adoption in just a handful of years with engineering staff. Now, we have something similar (and more glorified) with low-code agentic workflows, but this time, it’s not the engineers that are turning heads, but the Product and Non-Tech folks. These offerings aren’t perfect, but there is already some preliminary research around this. Therein lies the difference and there is lies the distinction for the future of SaaS companies.

The Quiet Revolution: Building In-House

While the rest of tech is going nuts over the AI/Agentic hype and the bigger consultancies are out there raking in money on transformation projects, something quieter is going on.

“The most effective teams will embrace the ‘boring’ work...”

It’s now easier to ask for something custom-built from an internal team. And it’s becoming less difficult (though still not trivial) to actually design and build that custom solution internally, with a higher chance of it being maintainable. The most effective teams will embrace the ‘boring’ work: improving internal workflows once deemed too complex to automate, or building robust, in-house ‘Zapier-like’ integrations between systems (especially for thorny areas like IAM). Why? Because the more you can take underlying infrastructure for granted, the more you can focus on higher-level, differentiating features. Here’s a very spicy take on this from the folks at HFS Research.

This was technically possible before, but the tradeoffs were far more brutal. Imagine explaining to your best product/engineering teams that two quarters would be spent overhauling an internal API instead of building new revenue-generating features! It’s not perfect yet, but these conversations are significantly less painful today.

An Awkward Future for SaaS

If you find merit in my hypothesis, then we have a pretty awkward future for SaaS companies over the next few years (especially, the ones who magically became AI-enabled in the last 10 minutes). For example, UiPath has historically been seen as a good automation pivot story. But recently, it’s been struggling to grow as a lot of what they offer has been easier to achieve in-house. For Desktop-based activities, it might still be around.

Another thing to keep in mind is that most SaaS companies that may have started as a tool doing just a few things really well are now trying to become systems of record for your company. This is because the ones with the willingness to pay are at the Enterprise level, so they come with the needs for as much of a monolithic solution as possible to simplify procurement.

But we have a problem here - there can only be a handful of systems-of-record for your company. More than that, the incentives are quite aligned for the SaaS company to do the same because of “stickiness” – a term which used to be a practical way to explain why a customer wouldn’t leave because of how much value you’re providing, but is now used to explain the degree of pain it’ll take to leave that solution.

So, let’s recap the emerging landscape. Large software providers are scrambling to prove their modernity to avoid losing customers to nimble in-house solutions. Smaller SaaS companies are struggling to retain customers as in-house alternatives become more viable. And new frameworks are making it significantly easier and cheaper to build custom solutions internally – tasks that were prohibitively expensive just months ago. Bottom line: This isn’t looking good for SaaS.

“In a world where every team is short-staffed, that kind of genuine time-saving isn’t just a nice-to-have; it’s a tangible ROI.”

The Time Premium

I’m not even going to pretend to offer a prediction here since things keep changing all the time. Instead, I want to spend this time to ask you, most likely a person (and hopefully a leader) in tech, to really be thoughtful about what your customers actually need. Today, the bar is so low to offer a ‘helpful’ product to consumers, and it’s not going to be easy to compete against free or in-house solutions. But it is absolutely possible.

Think about it like this: London’s Indian food scene is saturated, right? You can get a decent curry anywhere. But then there’s a place like Dishoom. They aren’t the cheapest, but they’re packed. Why? Because they offer an experience and a quality that makes you want to be there. It’s the atmosphere, the consistency, the little details that make you willing to wait in line.

The same logic applies to your product. The decision-makers in those sales rooms are the same people who likely still buy an iPhone even though a Samsung A-series phone will do everything except iMessage for way cheaper. They’re paying a premium not just for features, but for the seamless experience, the reduced friction, the time saved. In a world where every team is short-staffed, that kind of genuine time-saving isn’t just a nice-to-have; it’s a tangible ROI. It’s a strategic asset worth far more than just OpEx. They will gladly pay a premium for something that can truly save them and their team the most precious resource of all: time.

So, the real tradeoff decision for leaders? It’s shifting hard. It’s no longer just ‘do I deal with the hassles of an in-house solution today, or do I face an expensive, potentially escalating, renewal next cycle?’ That question used to be a weird one. Not anymore. Not today. It’s a fork in the road, plain and simple, and the path chosen will absolutely define who wins and who just... survives.

One of my favorite columnists is Matt Levine at Bloomberg Opinion . He has this not-so-inside joke with his readers that “Everything/Anything can be securities fraud.” He explores a lot of complicated things in the world of business and finance with humor that’s hard to find elsewhere these days. I hope to emulate a bit of what he does with my own thing - “Everything is a product to someone.”

Admittedly, it’s a working title until I can come up with something better, but it also gives me creative license to talk about more things through the lens of building great products.

Today’s segment is about a product sold mostly to large institutional investors: Private Equity!

There have been small attempts to crowdfund this, but we lowly simple folk aren’t really the target audience.

So... what exactly is sold as the product itself? Well, to keep things simple, the first thing that’s sold is a promise by a General Partner to spend money on your behalf on things that’ll hopefully make you some more money in like 7-10 years. (See: Committed Capital) Then, assuming that promise is kept and there is an enticing investment that needs to be bought, they’ll ask you for that money for real and then do the thing.

What’s ultimately sold at the end of it all is a Limited Partnership in a fund (See: Investment Vehicle). Based on how much you put in, and what tier you are, you’ll get paid out some amount of money based on how that fund does.

There are some good and not-so-good things that come with this product compared to other financial products an institution might buy into.

The Good:

• Incentive alignment for those who provide and manage the money: The carried interest tends to be larger for more success delivered and lower for less success at the end of the fund’s life. I always thought it was just a flat 2/20 model, but that’s not universally the case, it seems. Trivia: This carried interest concept is actually based on how in the 1600s a ship captain would have their own fee structured for the trouble of taking a ship with cargo around the world and maybe fighting some pirates along the way.

• A cooperative and commitment-based approach: You’re literally stuck in a fund for many, many years to ensure the returns come through. Everyone kinda gets a piece of the pie.

• Diversification of different kinds of PE: An institutional investor could put money into a fund that buys small companies, medium-sized companies, enterprise software companies, big companies, companies that failed, real estate, and the list goes on. Recently, secondaries have become quite big, and I think I could probably do a whole post on it, but... I’m not educated enough yet to say anything in detail here.

The not-so-good:

I’ve accidentally already covered Diversity and Equity... but unfortunately, there really isn’t much Inclusion (😉) in Private Equity yet.

While PE is open to individuals from all backgrounds in theory, the practical on-ramps are narrow. Fundamentally, you’re just more likely to be in this world if you were made aware of it and groomed for it through specific educational and early-career pathways.

This isn’t just a social issue; it’s a potential product issue.

At an educational level, it’s such a diverse field that you’d think there would be a BS or BA in Private Equity or something, or even a PE concentration in a BS Finance or Economics degree, but largely, no. PE firms kind of act like hospitals and only want permanent staff who’ve gone through a “residency” period at other Investment Banking institutions first. So, it’s a largely gatekept industry and this is a real challenge they’re wrestling with. That “IB residency” is a common path, but firms are starting to look wider.

To be clear, I have many close friends in PE, and they’re clearly not assholes or snobby people. I might have problems with some of the things PE does, but they’re not unsolvable problems.

The Trust Barrier and Group-think

Sometimes we might be better off having common language or some shared set of values to move the needle in the “correct” direction, whatever that may be. So let’s focus on that today: How can PE be a better product for their current customers, but also for a whole host of other people? I really don’t think we need to think zero-sum or negative-sum here.

The PE industry operates on a foundation of immense trust. LPs entrust GPs with billions, asking: Can we trust your ability to raise money? Can we then trust your ability to borrow money well? Can we trust your ability to buy things correctly? Can we trust your ability to operate/improve what you bought (and yes... sell for parts)? Can we trust your ability to stick around for at least a handful of years in one place? If you think about it, these are questions we have for our life partners (including the “sell for parts” conversation! I would love Marie Kondo to help our home be less cluttered and make a home with intention in mind.)

These questions get hard to objectively prove or answer unless you’ve ironically already done some work that people in the industry will understand. There is no credit score for this. There is no defined pathway to getting larger and larger amounts of capital over time unless you really are in the network. All the institutions are there to work with those who are already in that world.

For that reason, I think they can be quite narrow-minded at times, but I’m in the peanut gallery here, so feel free to apply a discount to what I have to say.

That narrow-mindedness, I argue, has created a group-think on what it means to generate returns. And what kind of returns are preferred, at that. And how to achieve those returns. This shared, insular perspective means the industry can develop blind spots, potentially overlooking innovative strategies or different types of investments that fall outside the traditional playbook. It narrows the aperture for what the “product” of private equity is perceived to be and limits the potential for evolving how value is truly created, both for LPs and the companies they invest in.

Another post in the future can probably talk about LBOs, borrowing terms, and how things have been an interesting roller coaster for the last 7-8 years in PE in particular, but for now, I’m going to focus on the cultural aspect of groupthink.

It also creates a problem where often, when someone from the outside offers critical commentary, they’re shunned or dismissed by the industry since the trust isn’t there. The possibility that you might understand their world deeply, despite being an outsider, isn’t a scenario they’ve really gamed out. Even if, for a moment, we assume that’s not the case and the person offering feedback does know the world and is offering commentary on what value should or could mean, well... it’s still pretty difficult to take a hard look in the mirror. This isn’t to excuse any fund or anyone in PE, but it certainly highlights how challenging it can be to be effective in living in a world that is driven more and more by PE actions.

When Bigger Isn’t Necessarily Better

To be clear, they’re not all having a great time. It’s been observed pretty clearly that larger funds aren’t necessarily better at providing returns, and ironically, they have diseconomies of scale. I wish I could have found a more recent study that took into account the ZIRP-era, but who knows, maybe the jury is still out on that? There is a working paper out there by NBER that’s taking a look at this, but using a different proxy to anchor their analysis. Even that paper is saying that a single standard deviation increase in fund size means their IRR goes down hard, plain and simple. WHY it goes down... well, I’ll need to make some popcorn for that at another time.

Redesigning the Product: A Positive-Sum Approach

Overall, it seems to be the case that the standard recipe of buying an undervalued/underperforming business and turning it around isn’t the most notable or readily available way to do PE right now. Additionally, most people hear “Private Equity” and immediately think about roll-ups where long-standing smaller HVAC businesses, car washes, housing communities, HOA managers, or private practices are gobbled up by a large machine designed to print out money for their LPs and nothing else. That is what people see today.

If we view PE as a product, could a more “tasteful” design be more culturally appealing and economically beneficial for a wider range of stakeholders?

As a product, if the model was designed more tastefully, this could be more culturally appealing to the broader population of those that can benefit from Private Equity as another means to build a better life.

We’re already seeing the rise of continuity vehicles or even evergreen funds for certain types of businesses. Today PE is often used to help an HVAC small business owner make an exit, while it leaves an uncertain future for that business owner’s staff.

Maybe... just maybe, more than just the owner could benefit from this transaction? Why couldn’t we instead use the ESOP model to help a whole host of parties all at once when that small business owner wants to exit? In Chapter 4 of the book Staying Private, Ira Starr of Long Point Capital and Matthew Hricko of Stout argue for just that. Business owners can get some nice cash plus some tax advantages, the employees can have even more skin in the game, and since the PE fund can arrange some portion of the debt based on future cash flows, a lot more people can have aligned incentives to make it all work well.

Why isn’t this ESOP model, or variations of it, more central to the PE “product” offering?

Why can’t we do this where everyone can come along for the ride? Of course, the ESOP model doesn’t work for everything, but we have a generation of small businesses that are about to change hands in the next decade. How we go about that transition will literally define a big part of our relationship with capitalism.

Applying a product mindset isn’t just for building apps or good businesses. It’s a lens that lets you look at things like Private Equity and see them as complex designs. Seeing something as a design means it’s not set in stone – it can be questioned and, yes, redesigned.

I wrote about the concept of scale that PMs sometimes get blinded by a little bit in a previous article. A couple of friends read it, and we started having a debate about what “scaling something” even means, why we feel so strongly about the way we see the world, etc. Then one of them said, “You should probably write about this,” so here I am.

I tend to have pretty critical views about “scale” now after having lived through a decade in the Bay Area. I’m of the firm belief that a lot of us were told to drink the Kool-Aid of “only businesses that scale to a billion (in valuation 😉 ) are the businesses worth doing or starting.” This narrative often originates from people who clearly stand to benefit from that speculative outcome even it that comes with some unsavory externalities.

Before we talk about the nuance, let’s get a few things out of the way, especially if this is the first post of mine that you’re reading. Yes, I know the standard VC model is to invest in things that have the potential for a blowout exit. It’s supposed to be high risk, high reward, yada yada. And sure, different VC models do exist now – pure plays, rollups, the de-SPAC trend that thankfully peaked in 2021, venture debt via hybrid funds, etc. Those are all fun and fine and we may even discuss them in a future post.

But I don’t think this dominant focus of scaling to a billion is primarily because large funds want consolidated control over different parts of commerce, though maybe some do. At the end of the day, they’re also subservient to their Limited Partners and investors too. Even the different General Partners at each fund don’t always have aligned incentives, which makes for some amazing drama.

::Engage Peanut Gallery Mode::

I think the root cause is a lot simpler than that. They’re just flawed, selfish humans like us, and they fall for the same crap we do.

Maximizing the easy win... or not?

There’s a meme going around Instagram and Tiktok (for which a link is quite hard to find right now) about a professor offering to adjust their students’ grades with extra credit. Students can request either 2 points or 6 points. If more than x% of students pick 6 points, then no one gets anything. There are a few variations, but I like this one because there isn’t a truly negative outcome, only a potentially decent positive-sum outcome that can be missed. It’s a great illustration of game theory and incentive alignment.

The simplest thing to do is coordinate and guarantee 2 points for everyone. But we all know that’s not how the game is usually played. Inevitably, some portion of the class, for a variety of motivations, will go for the 6 points because 2 points isn’t “good enough.” Maybe they bombed the test and need the highest return, or they did well and want the upside of pulling ahead...or the ones who did well just don’t want others to pull ahead and will consciously try to push past the % threshold so no one wins extra points. Often these types of common-pool resource experiments reveal a pretty honest (although sometimes shitty) view of humanity. These games play out in classrooms over a few rounds to see if there is a change in behavior.

Now, think about the VC world and the “billion or bust” mentality. The VC funding model sets up a similar game. The “6 points” is the billion-dollar exit – the outcome that delivers the necessary fund returns. The “2 points” might be building a profitable, sustainable, smaller business. The system incentivizes founders and teams to chase the high-risk “6 points,” knowing that while most players pursuing this path will end up with “0 points” (the startup fails), the few who hit “6 points” make the whole model work for the VCs and LPs. The VCs, as the architects of this game, profit from the system that encourages this behavior, often with less personal risk than the founders and teams playing the game.

But here’s the kicker, and it’s a big one. Even when a few companies do manage to get those 6 points – that shiny billion-dollar exit – it’s often not the fairytale ending you’d expect for the company itself. Look around: how many of those high-flying ‘unicorns’ truly thrive once they’re public or get tucked away inside a larger corporate parent? We talked about Zenefits last time and I’ll stay away from going deep into Lyft, Uber or WeWork that others often talk about. Think about companies like Box and Dropbox, which achieved huge valuations, but have faced ongoing questions about profitability, growth sustainability, or stock performance post-IPO. Or consider Slack, acquired for a huge sum by Salesforce, whose integration and continued independent innovation have been subjects of much discussion. And this pattern holds true for countless other B2B products acquired for huge sums only to see their roadmaps stifled, teams disbanded, or innovation slow dramatically as they’re forced into an acquiring company’s structure. The intense pressure to grow at all costs to achieve that exit valuation often builds companies optimized for that one single moment, not for much else. The “win” for the initial investors and founders doesn’t always translate to long-term health or continued product innovation.

The new Manifest Destiny

Marc Andreeson tends to represent this mindset quite well. “I can make multiple bets that have contradictory theses. This is the whole Peter Thiel thing of determinant optimism versus indeterminate optimism. A company founder CEO has to be a determinant optimist. They have to have a plan and they have to make the hard trade-offs to be able to succeed at that plan. A VC is an indeterminate optimist. We can fund a hundred different companies with 100 different plans with mutually conflicting assumptions.” - his words, not mine.

This neatly captures the portfolio approach that necessitates chasing those outlier outcomes. Obviously, we also have Private Equity with another angle that tries to go for fancy financial engineering magic as a way to generate returns regardless of the externalities.

Look, I could do the fun Bernie Sanders “It’s the Millionaires and Billionaires!” thing and call it a day. But I write about this world, not because these VCs/Founders/PE folks are the “other” group for me. They’re my friends and colleagues. These are all places where significant capital pools operate, where their careers are made and frankly, where many of them will be the leaders in the coming decade. But they aren’t the only or necessarily the best places to build lasting value or a fulfilling career.

Awesome Alternatives

What about the rest of us? Those who either don’t care to go to a BigTech/xTech firm, can’t get into one, or don’t even know much about them? I think being a part of a smaller business is quite underrated. Especially a business that doesn’t need to scale exponentially, or is in a niche unlikely to be the first target for consolidation. These companies offer compelling models for building sustainable value and careers outside the hyper-growth paradigm, potentially serving as a counterbalance to the trend of larger capital pools consolidating more parts of the economy.

From a Product perspective, there are companies like 37Signals, Automattic, Element84, Baremetrics, Kit, or Harvest that offer a great alternative to the big ones. My friend and colleague, Erad Fridman runs Fluxon, and they’re pretty great too! There’s also a giant list of consulting firms that focus on a niche like cybersecurity, systems integration/development, supply chain, product development, etc. Could these be opportunities for acquisition? Sure. Are they the first places to look for a blowout exit? Likely not, is my bet. They might either serve a limited market size, have lumpy revenue cycles, or don’t really have an enticing (aka 70%+) margin profile, nor do they explicitly follow the rule of 40.

I find these companies super fascinating; they represent smart, viable paths for building businesses and careers outside the traditional VC-funded model. The other thing that’s been very interesting to me is the “Micro” Private Equity space and its various flavors like Micro Permanent Equity, Micro Evergreen Fund, etc. They’re just the modern-day version of having a variety of small businesses conglomerated together the way many folks do in small towns. Think Dr. Lu Saperstein from Parks and Recreation! I want to explore a bit of this in a future post!

So, what are your thoughts on the “scale to a billion” mindset? Have you seen it impact how products are built or how careers are shaped? Do you know of other businesses thriving outside this model? I want to know :)

Stewed cooking is quite common across the world. In South Asia, it became prevalent because there was a lack of high-temperature cooking fuel, so cow dung, wood, or crude charcoal were the primary methods of making food. It’s a similar story in many other parts of the world, and that has shaped to quite a large degree what those cuisines tend to evolve into – dishes that require long, slow simmering to become tender and flavorful.

When your primary method to make large-scale batches of food is constrained by heating temperature, you have to extend the amount of time you do the cooking. This actually offers an excellent look into how product development differs in some really well-known products and services available in the market today.

Think about it. When you have limited “heat” – limited capital, constrained resources – you have to take your time. You have to be disciplined, focus on the core, ensure every step is right before moving to the next. You build your flavor base slowly. But what happens when you suddenly get an artificial burst of high heat? An artificially large amount of capital injected into a business that hasn’t had time to simmer and develop its fundamental structure?

There’s an entire VC industry that developed with institutions juicing up businesses on the hope that growth and scale can magically solve underlying problems.

Companies that received this kind of premature, oversized capital often suffer through significant challenges in growth and gross retention of customers. There’s an entire VC industry that developed with institutions juicing up businesses on the hope that growth and scale can magically solve underlying problems. We could talk about the usual suspects like Uber or Doordash, which famously still lose money while squeezing customers and labor. But honestly, that story’s a bit tired.

Instead, I want to look at two specific examples from the peak startup boom era of the 2010s that illustrate this perfectly. One business got that huge, early capital injection and chased explosive growth before it was truly ready. The other took a more disciplined, focused approach. Their outcomes couldn’t be more different.

Back in the early 2010s, both companies emerged aiming at small and medium businesses (SMBs), promising to simplify HR. On the surface, they looked like similar disruptors. But their journeys, and their fates, highlight the difference between getting too much money before you’re ready to make that money work for you.

Let’s start with Zenefits. Founded in 2013, they were famously fueled by massive early capital – over half a billion dollars raised by mid-2015. They offered free HR software, making money instead by acting as the insurance Broker of Record for their customers. This meant they were deeply embedded in the complex, state-by-state world of insurance regulation from day one, but their focus was clearly elsewhere. With that massive funding, they chased hyper-growth on steroids. By mid-2015, just two years in, they’d hit just over $20M ARR, but had scaled to nearly 1,500 employees to make that revenue, and had a crazy $4.5 billion valuation. On the surface, they were cooking fast and were a huge darling in San Francisco. I worked a block away from their office and compared to the Macys.com office, their after work happy hours were awesome!

Too Much Funding, Not Enough Discipline

This growth outpaced fundamental operational and compliance things they needed to get right. Their culture became a high-pressure “growth at all costs” machine that a lot of us in tech already know about. Speed and sales targets consistently seemed to trump boring, but critical things like ensuring their brokers were properly licensed in every state.

This wasn’t just a few slip-ups; it was systemic. It led to predictable, severe problems: service issues surfaced as early as 2014-2015, massive compliance failures were exposed in 2016 (remember the CEO creating a browser extension to bypass mandatory training?), followed by regulatory fines across multiple states, leadership changes, significant layoffs, and ultimately, a forced fundamental shift in their business model to a paid subscription in 2017, long after the damage was done and trust eroded. Despite the massive early funding and explosive growth, Zenefits eventually sold to TriNet in 2022 for a figure significantly less than its peak valuation, effectively ending its run as an independent entity.

The Discipline Dividend: Why Gusto Won

Meanwhile, Gusto (originally ZenPayroll), started a bit earlier in 2011. While also well-funded (raising a pretty big seed round of $6.1 million), they approached growth differently. Their initial model was paid from the start, focused laser-like on one critical, complex area: payroll. They built a reputation for absolute accuracy and reliability – a non-negotiable foundation when you’re handling people’s paychecks and taxes.

Their growth felt more measured, more methodical. They built a culture that prioritized customer service and crucially, compliance right from the start, understanding the sensitivity and regulatory demands of payroll data. They didn’t chase hyper-growth at the expense of fundamentals. Only after establishing this solid core did they strategically expand into other HR areas like benefits (rebranding to Gusto in 2015), time tracking, and building strategic partnerships (like with accountants). Gusto reached a $1 billion valuation by December 2015 (a few months after Zenefits’ peak, showing a different trajectory), achieved profitability, and has continued to grow sustainably, reaching a valuation of $10 billion by 2021, remaining an independent and from the looks of it, a thriving company. They focused on building that strong foundation, mastering the simmer, and the result is a resilient, enduring business.

The contrast is stark and instructional for anyone building products or leading teams today. It shows what happens when one company gets a huge, early capital injection and chases explosive growth in a complex, regulated space without building the necessary operational, compliance, and cultural structures needed for that kind of heat. And what happens when another builds a solid core product, prioritizes discipline, accuracy, customer trust, and compliance from day one, allowing growth to happen more organically as the foundation strengthens.

The lesson here isn’t that funding is bad. But it’s pretty clear, chasing growth metrics without building a fundamentally sound, compliant, and customer-focused operation is like trying to serve a stew that looks done on the outside but is raw in the middle. It might impress briefly, but it won’t taste good and soon enough - it’ll get tossed out when no one is looking.

I want to start this write up with a story about the Indian Railways. After the British left in the mid-20th century, they left behind an extensive (but awkward) railway infrastructure. Not just the tracks, but also the rolling stock itself. The colonial era left a multi-tiered class system for carriages (a local Indian couldn’t just walk into First Class, even with money), and post-independence, the concept of luxury took on an interesting meaning.

For Indian Railways, the priority was egalitarian growth benefiting the “common man.” It was deemed more functional to build more ICF carriages equipped with fans and open windows, rather than fewer coaches with higher amenities like air conditioning or proper restroom plumbing. I appreciate and understand the reasoning behind this, and eventually, some coaches did get air conditioning. A lot had to do with what the new soul of the country needed to care about. The saying went that India was a developing country, and AC (or even higher speed rail services as an offering) was considered a luxury.

Let’s keep this “concept of luxury” in mind as we talk about the main topic today - Diffusion Models. I promise we’ll tie it together in the end!

So turns out diffusion models aren’t just for pictures anymore?

For those not really in the middle of all of this on a frequent basis, you’ve likely come across Stable Diffusion. It was created by a company called Stabilty AI, which has a platform you can go use today to commercially do a ton of media-related workflows.

It uses a technique that starts with a vague idea and refines it over several iterations (or “steps”), getting closer to the desired image. Often, it’ll start heading in one direction and end up producing something completely different by the end.

Below is an example I made of how this technique could end up with an image for a WPA-style advertisement of Havana, Cuba over 60 steps. Step 2 is quite different compared to the final output on Step 60.

Since then there have been a ton of competing services and model frameworks that have come out to work on this space. As you see above, I personally use Flux Schnell locally on my computer for a lot of image generation workflows for the restaurant’s email marketing campaigns that we’ve talked about before. I probably could use one of those commercial services, but honestly, I don’t want to pay for one more subscription and these open-source models are pretty damn good these days! If I had a real need as a brand or marketing person for my day job, I’d likely force my employer to shell out a few dollars to make my life easier for sure.

But that’s for image generation and as I said at the top of this post, looks like there are other use cases popping up. So without further suspense, looks like a team of researchers in Hong Kong have come out with their own diffusion-enabled text generation model! It’s a new take on how we use LLMs today.

They call it Dream (Short for Diffusion Reasoning Model)...and of course they did. God bless these nerdy researchers by sometimes having AWESOME names for the stuff they make.

Dream is able to do the same thing as Stable Diffusion for images, but with text generation instead. This isn’t how our brains typically work, so the easiest analogy I have is imagining you have the idea for a book (or maybe even a newsletter 😉). Instead of writing linearly, you might write the first sentence and the last sentence simultaneously, then fill the space between with placeholder text - like Lorem Ipsum. After that, you start to fill in the first sentence of the fifth paragraph and the 3rd word of the second paragraph at the same time. And you keep this going on and on until you’re happy with the final product, or you get tired of writing this way.

The one from their paper shows is pretty good too!

This is nuts! But why would someone even go off and research something like this? If the current LLMs aren’t really broken (at least in the way they generate text), then why fix it?

Well, it turns out you get to tweak a lot of things upfront before kicking off a job, with the most important being performance and quality. Just like how you can configure how many steps a diffusion model takes to get you that image you’re looking for, you can give the text model the same configuration to get the body of text you’re looking for.

I would love to play around with this Dream model locally, but even though it’s a 7B parameter model, the GPU requirements are quite high, and I don’t have that in my little home office. Luckily, my old colleague at AtlasAI, Stefano Ermon, just created a new startup called Inception (not to be confused by Inflection, of course, the startup that got acquired by Microsoft). I’ve been trying out their own diffusion text generation model, and it works similarly.

These technologies are evolving pretty fast. I even asked Inception’s tool to make an animation of a helium element with its two electrons orbiting the nucleus. It just did it, and it even took the liberty of running the JS file in the browser window and showed me the output!

So far, I want to reiterate that this won’t eliminate developers. Instead, it will certainly supercharge their ability to get complex things done much faster – especially those tasks that might otherwise feel trivial or low-priority.

More practically, let’s get back to the “concept of luxury” from the top of this newsletter. In tech, we talk about this in terms of “nice-to-haves” and “ruthless prioritization” instead of “it’s a luxury we can’t afford.”

Imagine if I asked a developer to make me that helium element animation as a custom loading animation for a web app while we were also trying to get a super important feature out the door. That dev would have killed me in the past for even suggesting that as a request, but now...even I, a simple village idiot, could get us 90% of the way there with no distraction for the engineering team. Efforts like this can make the fit and finish of any product much easier to accomplish.

People value that fit and finish of products they interact with. It’s why many developers prefer Macbook Pros over clunky Alienware laptops. But there are simpler examples too. I’ve come across so many employees at healthcare facilities, UPS stores, restaurant warehouses, and many more that all use really clunky software tools. Tools that certainly aren’t given the love of fit and finish because it’s deemed unnecessary — they’re a luxury a software vendor didn’t need to care about.

When the development time for something like a custom loading animation is anywhere near the time needed for a core functional improvement, that “luxury” is always the first thing tossed out in favor of utility. I think we’re arriving at a point where for a decent chunk of software design needs (and soon enough after that, industrial design and infrastructure design), we won’t have to make a false choice. Even internal tools could look almost as good as production-grade tools. Maybe we won’t fall into the trap of asking if something is “truly necessary” just because its improvement is non-material.

Thankfully, that parallel is also relevant to the Indian Railways today. There was a hot debate recently about the Indian Government prioritizing the first high-speed rail corridor in western India vs using that money to deploy a train safety system called Kavach across all Indian trains. It’s the modern version of the Air Conditioning debate from 50 years ago. (Note: there are 13,198 trains that run in India daily across 7,300 stations carrying 6.9 billion passengers. Yeah...its a lot haha)

I don’t want to get into a financing debate (even though 81% of the money for the high speed rail project is financed by a 50 year Japanese Infrastructure loan at .1% interest), but rather a values debate. In our day-to-day, we need to try to stay away from these false choice and zero-sum traps. Rail service, just like any B2C business, relies on a good hard product (infrastructure, equipment, reliability, etc) and a good soft-product (amenities, comfort, service, etc). In a country like India, you need people to want to take rail as an option.

More importantly, for us, all products deserve to be built with the fit and finish we want to see to enjoy using it. Now that these different types of models and services exist, product managers should deeply care about finding ways to make a wonderful experience today, not some quarter in the future. They should do this by taking on a deeper partnership with their engineering teams.

I’ve had to rewrite this post a few times because things are moving so fast in this space, and my frustration with bad product marketing regarding Agents keeps making me want to throw my laptop out the window. This post is the first of two parts: a harsh, realistic take on what’s been happening. The next post will take an optimistic look at what’s possible, thanks to a ton of open-source activity keeping this field a really fair game for most people.

The “Agent” Problem

This is going to start with a pretty basic hot take: “Agent” is a dumb name. I don’t think anyone asked for a name like this, and it doesn’t communicate what they are in any meaningful way to the user. It’s about as descriptive as “AutoPilot” was when Tesla first launched it (not to be confused with “Full Self-Driving Mode,” which isn’t fully self-driving either). We’re essentially forcing this concept down people’s throats before it’s even fully ready.

I’ll spare the rant about how a once-useful-in-moderation culture of “shipping it fast” in the SF Bay Area has now led to a ton of terrible externalities for paying customers. Let us focus on what an Agent is supposed to be.

What the hell is Agentic AI?

Agentic AI is supposed to describe an autonomous system that can make decisions and perform tasks without human intervention. Seems simple enough. So, what do we have out in the market these days?

If I had written this post eight months ago, I’d have said...not that much in terms of agents or their usefulness. Barely anyone knew what MCPs were, let alone what they could be integrated with to create an agent.

If I had written this post at the beginning of 2025, I’d have some helpful things to write about, but honestly, it would have been pretty early days. Maybe I would have referenced one of 50 Satya Nadella interviews to show where a possible future was.

Well... it’s early April 2025, and almost every LinkedIn post, half my algorithmic Instagram feed, and every other Chad-bro podcast would have me believe that not only is the Agentic AI future here, but apparently I’m quickly lagging behind if I don’t use Agents immediately! Apparently now it’s possible to run your entire business using agents managing other agents to do all the “boring stuff of running the company.” Seriously, this link above is the epitome someone cheering for late-stage capitalism in the worst way.

I suppose it’s too bad you can’t have Customer Agents who can just give you money in just as deterministic a manner as Worker Agents. It’s only a matter of time, I suppose?

We’re going to see less people filing tedious reports or quietly spending late-nights doing research for a big initiative so they can get their evenings back. I hope it brings the virtue of living more life doing literally anything other than “working long hours.”

The Current Reality

Here are a few things actually possible right now:

• Local Chain-of-Operations: Zapier and IFTTT started this trend a while ago for work and personal use using cloud services. Now, we’re definitely seeing some potential for non-engineers to build sophisticated automated workflows. AI transcription services like Otter or Abridge are everywhere, but with security and privacy concerns over where a service is hosted, it’s a hell of a lot safer to have recordings done locally on a computer when everyone is in a room collaborating. The automation isn’t fully there yet, but it is now possible as soon as you save a recording to use Aiko to kick off a workflow on your computer to transcribe the audio and turn the transcription into a distilled Notion or Confluence doc that ignores the less-official parts of the conversation and doesn’t track the linguistic profile of employees. This was historically a responsibility of Scrum Masters and Project Managers, but now it’s a complex responsibility that can be largely offloaded.

• Knowledge Management Tools Offering the “Easy Button”: So many knowledge management providers (like Notion or Confluence) have their own “AI” offering that (with your permission) is more than happy to connect with your work messaging apps and other sources of information to give you more helpful context than no ordinary search bar could do in the days of yore. In this situation, you as a customer have no idea that there may be “Agents” (or likely pub/sub configurations) in the background handling all this indexing, RAG-ing, and re-tuning for you. You just get the benefit of getting a much more substantive answer to your question than before.

• Automated Review/Comment Moderation: For SMBs, you can have an automated configuration that monitors social media, Maps, or Yelp listing comments and does the first level of interactions with customers before bringing only the most important ones your way. EmbedSocial or Reviews.io are examples of such offerings, but honestly, as someone with a small business, we don’t actually use these to fully automate anything. We stop the automation at drafts-to-review before a human actually presses Send or Publish. It doesn’t have to do with trust or hallucinations (maybe a little bit), but it’s more to do with the importance of handling people relationships. Automation here does kill the last vestiges of authenticity available on the internet, and our customers are relatively quick to pick on it. We’re constantly editing the final review comment before we post to make sure the right intention is communicated.

It’s all just fu#$king Workflow Automation with a more hip name.

There are a few more concrete examples, but this is all still quite early days.

The Danger of Removing Agency: A Recipe for Disaster

It’s all just fu#$king Workflow Automation with a more hip name. The difference this time is that way more people are going to be able to configure way more of their workflows. They’ll be able to treat more of their complex work life like configuring a go-to-bed routine in their Apple Shortcuts app. (Also, let’s be honest, most iPhone users haven’t even touched the Shortcuts app. If you have, nice!)

The whole problem I have with the label “agent” is the concept of agency itself. These “agents” often lack the context and nuance to make truly informed decisions.

I want to be clear: what this is leading to is a good thing—but not for the reasons that 10x productivity podcasters are telling you about or the Equities Analyst at Goldman Sachs is thinking about. This isn’t about reducing the number of expensive workers or only focusing on the “fun” parts of the business. We’re going to see less people filing tedious reports or quietly spending late-nights doing manual deep research for a big initiative so they can get their evenings back. People will likely become more educated about more topics a lot faster than ever before. I hope it brings the virtue of living more life doing literally anything other than “working long hours.”

That being said, decisions related to bookkeeping, back office work, task allocation, marketing campaigns or software architecture just simply aren’t going to be given over to AI Agents regardless of the fetish many have right now. The whole problem I have with the label “agent” is the concept of agency itself. Liability lawsuits aside, no one is going to allow the most important decisions to be made by an AI agent, and likely, only some of the less important decisions will be handed over.

I wish I was being alarmist. Really, I hate this feeling of having a tin-foil hat on my head, but even handing over the less important decisions can be a recipe for disaster if we’re not careful. As technology becomes more integrated into our workflows, it’s tempting to cede control to automated systems, thinking they’ll be less biased or impartial. However, research suggests that removing human agency, even in seemingly minor decisions, can have negative consequences:

• Erosion of Skills: Relying too heavily on automated systems can lead to a decline in critical thinking and problem-solving skills. When we outsource our decision-making to machines, we risk becoming overly reliant on those systems and losing our ability to think for ourselves.

• Loss of Context and Nuance: These “agents” often lack the context and nuance to make truly informed decisions. They may be able to process data and identify patterns, but they can’t understand the subtle human factors that are often crucial to making the right choice.

• Unintended Consequences: Even well-designed automated systems can have unintended consequences. By removing human oversight, we increase the risk of unforeseen problems and negative outcomes. Air Canada accidentally offered a customer a discount they didn’t intend on providing. Now try being the Customer Support rep having to deal with that issue on the phone after the fact.

So what will Agents be used for? Grunt work. In fact, if there was a job at risk for Agentic Automation, it’s probably that Equities Analyst gig at Goldman that I mentioned earlier whose sole job is to do repetitive spreadsheet math and financial analysis. On the operator side, an AI Agent could handle asynchronous communication and coordinate different company functions. But do you really think any leadership team is going to cancel their executive offsite because of it? No! They’re going to go on that retreat...and they should! Even though it means being away from their families for a week, it’s likely going to be fun, and any chance people have of building a more cooperative relationship with others should be explored. No AI Agent is going to by default be privy to the good conversations at that offsite, and I want to discuss that irony for a little bit.

This whole thing is going to have to be a two-way street. Each of those offsite conversations about AI strategy are driven by a premature decision to utilize AI to cut costs first, and it appears decisions related to using these new technologies to generate an upside are secondary. I’ve been in enough board-level discussions for the last year in a handful of companies and non-profit institutions where this is a very real discussion. We can’t ask AI to handle the undesirable work, then turn to our own staff and have fewer of them to manage more of the AI deployments. We’re already writing more code with security issues the more we have AI assistants helping engineers.

Yes, I can buy the argument that all of these “agents” will be a step function better in a few short months than they are today, not just incrementally better. But the world is literally filled with products, services, and companies being brought to their knees based on edge case scenarios or what were once considered low-probability events. The more we let AI “agents” opaquely automate tasks, the more likely we are to face unexpected and potentially catastrophic consequences throughout the organization. If at that point we have less human capacity to go and solve the issue, almost every company that over-optimized on labor cost will actually end up paying significantly more to correct the issue, let alone continue staying in business for years to come.

Counterarguments: The Allure of Automation

Of course, not everyone agrees that Agentic AI is just workflow automation. As I did my rant with friends and colleagues over the last few weeks, there were some compelling arguments in favor of its potential:

• Increased Efficiency and Productivity: Agentic AI could automate many time-consuming and repetitive tasks, freeing up human workers to focus on more creative and strategic activities. (This assumes you’re retaining a good chunk of that human capacity, though.)

• Improved Decision-Making: By analyzing vast amounts of data, Agentic AI could help us make better, more informed decisions with less blindspots. (This one feels right? I imagine there will be less excuses of not knowing enough when making a strategic decisions. Research is way easier to conduct now.)

• New Possibilities: Agentic AI could enable us to do things that were previously impossible, opening up new opportunities for innovation and growth.

However, even if these arguments hold their merit, it’s important to approach “Agentic AI” with a healthy dose of skepticism and a clear understanding of its limitations.

So...that’s why I think Agents are a dumb name for what is otherwise just another flavor of “workflow automation.” And yes, I get it. It’s hard to raise money on “workflow automation,” though. It’s hard to promote your LinkedIn profile by having “workflow automation” in your title instead of “Generative AI @ {techCompany}.” That Equities Analyst asking questions on earnings calls wants to hear a somewhat believable case that your company is investing in AI capabilities to streamline cost centers, and saying “workflow automation” isn’t gonna be enough for him anymore. He needs to hear about that delicious flavor of the week: Agentic AI. Wishful thinking, but I really hope we stop playing this game.

In the next post, I’ll explore the potential for open-source activity to create a better future, where this helps actually individuals and small businesses, rather than just reinforcing the power of larger institutions. These things are finally reducing barriers to entry for smaller players to compete with everyone from the slightly larger players to the really large players. I’m envisioning independent restaurants being able to offer a much better service to their customers by having the owner/operators manage their digital life a lot better in this future—something that was only possible by having a larger restaurant group before or by having really expensive SaaS subscriptions. Similarly, I think a boutique consulting firm is going to be able to take on more ambitious projects which would have been only possible for larger systems integrators like Accenture or E&Y before. That’s a world I want to live in, where larger players lose more of their pricing power and means to execute to give way to smaller players to compete (obviously, not by their choice 😉)

Could the secret to building a product your customers actually love be hiding in your customer support queue?

To be clear, not all customers are created equal, and it does make sense to prioritize. You can’t jump through hoops for every user who isn’t really invested in your company or product. But it’s easy to hide behind that justification when you’re avoiding the real issues. Those recurring problems that drive your support team (and your customers) absolutely bonkers.

We all say we’re customer-centric. We slap “user-first” on our mission statements, conduct user research, and maybe even attend the occasional customer support sync. We might do our bi-weekly check-ins with the support team, nod along to their reports, and then promptly forget about it as we dive back into planning the next shiny feature. We might even hop on a call with a frustrated customer to say, “It’s on the roadmap for later in the year!” (It might not be.)

The truth is, it’s easy to think you’re customer-centric when you’re not the one dealing with the daily barrage of support tickets, angry emails, and frustrated phone calls. And that disconnect can be deadly for your product.

Incentive alignment is a tricky beast

For a lot of reasons, you might not solve customer problems right away. Some are good, others...not great.

Good Reason: Maybe you’ve confirmed that an issue only affects a tiny fraction of your users. (Yeah, we’ll add a note to the FAQ and call it a day.) Or maybe solving the problem would require a massive engineering effort that’s just not worth the ROI. (We’ll file that one under “nice to have...someday.”) For example, let’s say your system freaks out when a contract renews on February 29th. You might solve it at the contract level by adjusting the signed date. Or, if it’s a deeper issue, you might just flag those end-of-February contracts and deal with them manually. It’s not ideal, but it’s a pragmatic solution.

Not Great Reason: The elephant in the room, those messy, legacy issues that everyone’s afraid to touch. The ones that would require unraveling a spaghetti code of temporary fixes and confronting some uncomfortable truths about past decisions. Ignoring them won’t make them go away. But, let’s be honest, it’s a lot easier to pretend they don’t exist when you’re not the one fielding the angry phone calls. You intellectually know the problem exists, but you don’t feel the frustration of a customer whose workflow grinds to a halt because of your broken product. And that makes all the difference.

We often talk about the lack of user empathy in the product world, but the best way to build it is to trade the fancy product roadmap for a customer support headset

The Commercial Disconnect

Of course, not all customer needs are created equal. Sometimes, fixing a customer problem means creating a premium feature – something your commercial strategy dictates you should charge extra for. An example of this is CVAT’s on-prem solution. They offer Meta’s SAM v2 model for faster image labeling, which is a huge win for their users. But they don’t give it away for free; you have to upgrade to the Enterprise license to get it. Is that greedy? Maybe. But it’s also a smart business decision. They’re testing “willingness to pay“ and ensuring they can continue to invest in improving the product. The key is to be transparent with your users about why you’re charging for certain features. Explain the value they’re getting and how it benefits the overall product. Don’t just hide it behind an upsell and hope they don’t complain.

But beyond these pricing considerations, there’s a deeper disconnect at play. We often talk about the lack of user empathy in the product world, but the best way to build it is to trade your fancy product roadmap for a customer support headset. Because let’s face it, most PMs have seldom been in the hot seat – the customer support seat.

Customer support teams (or “Customer Success” at the hip and cool places) are on the front lines of customer experience. Their sole job is to deal with problems and solve them ASAP to keep those customers happy. Every support team I’ve worked with has a core group of people who genuinely thrive on that! (I’m thinking about you - Ian Schuster, Paris Good, Lokesh Paliwal, Shashank Kaushik, and Anthony Secco, to name a few) They’re also the ones who have to manage the really pissed-off (and sometimes entitled) customers, knowing full well that some problems are simply unfixable.

A PM might get brought in on 1 in 50 of those “impossible” cases. And that’s by design. If PMs spent all their time firefighting, they’d never have time to build a proactive product strategy. But that doesn’t mean we can afford to be completely disconnected from the daily realities of our users.

So, how do we bridge this gap between these two functions? The answer depends on the size and stage of your company:

Embed one PM with the support team for a week at a time. Think of it like an on-call rotation. Engineers do it by default, so why not PMs?

Small Companies: Let’s be real, you probably are the customer support team. When you’re just starting out, every customer interaction is make-or-break. You’re incentivized to pay attention because one lost customer could sink your whole year. The key here is to document those early customer interactions. Create a system for tracking common problems and feature requests, so you don’t lose that valuable knowledge as you grow.

Growth-Stage Startups: This is where things get tricky. You’re starting to formalize roles and responsibilities, and it’s tempting to offload all customer support to a dedicated team. But resist the urge! I’ve seen too many startups where PMs start shifting their focus to new features and “high-impact” projects, leaving customer support in the dust. They’re still building things, for sure, but they’re prioritizing the new over the necessary. The biggest warning sign? When team members start prematurely calling for rigid role definitions. (Translation: “I don’t want to deal with that anymore!”) Don’t fall into that trap. What works best is leadership alignment. Make it clear that customer support is everyone’s responsibility. Otherwise, your team will always default to the excuse: “We can only work on revenue-generating things right now. We have a target to hit!”

Large Companies: In larger organizations, there are often good connections between support and engineering, but a million layers of bureaucracy to get anything prioritized. One solution I’ve seen work well is shift rotations: embed one PM with the support team for a week at a time. Think of it like an on-call rotation. Engineers do it by default, so why not PMs? It breaks down silos fast. Of course, you need to free up capacity for this, and that requires leadership buy-in. This has to come from the top, or no one will feel comfortable stepping away from their “real” work.

A large distance between Empathy and Compassion

You’ve likely heard your colleague say something like “I love our support team, such great people! But I wouldn’t touch that job with a 10-foot pole. It’s just not my thing, you know?”

Look, I can buy the argument that some people are better equipped or built for a type of job or role. I definitely don’t have the relentless optimism a sales person will carry to deal with 10 rejections a day. However, if we’re being quite honest with ourselves, the real reason we’ve heard or said the above is because we like working in a job where the real consequences of our actions are externalized and the benefits of a successful outcome are more likely to be received by us first. We did create the superb strategy, after all. We’re the mini-CEO of the company! 🙄

Sure, sales gets that fat commission. Maybe the real CEO will take credit for what you and your team did, your boss will too. But this is how you’ll get promoted and a pay bump. A year from now, you’re likely working on a different team or product with a different set of responsibilities, but someone is going to be left holding the bag to deal with the problems you left behind. Another engineering team, another PM, and also...the entire customer support team.

The Enduring Product

I’m not saying you need to cover every single edge case or write a million smoke tests before shipping a new feature. I’m also not saying you should spend five months building something that should take five weeks. And I’m definitely not saying you need to stay a PM on the same product for five years. What I’m saying is: True ownership comes from building an enduring product. A product that customers are willing to recommend to others. A product that generates the fewest support tickets per user, per company, per dollar. (There’s probably a good non-NPS metric to track in there somewhere.)

So, for however long you’re in charge of a product, take the time to understand what customer support has been dealing with. Put yourself in their shoes. And, most importantly, demonstrate how you’re fixing those problems. You’ll be a better PM for it. You’ll build more allies across the organization. And you’ll build a network that might just save your butt five years down the line, in ways you can’t even imagine right now.

If you’ve made it this far, thanks! Now pick one recurring customer support issue and make it your personal mission to solve it within the next month. Work directly with the support team to understand the root cause, brainstorm solutions, and implement a fix. Not only will you make your customers happier, but you’ll also earn the respect of your colleagues.

The promise of something like A/B testing is seductive: data-driven decisions, optimized conversions, and a clear path to growth. But the reality is, most teams are doing it wrong. The core problem? Sample size. More specifically, how much sample size actually matters.

I found it surprising that the first (known) version of A/B testing started as a way to promote beer in the early 1900s? Schlitz Beer, out of Madison, Wisconsin, hired a man named Claude Hopkins to help grow the brand nationwide. It was pretty clever for its time - to test messaging and revenue attribution to marketing spend. It wasn’t perfect (I doubt the Don Draper types would utter the words “statistical significance” that often), but even they needed a mountain of data and information to make it work. And unless you’re in e-commerce or social media today, you probably don’t have that kind of user base to achieve said statistically significant results.

Let’s look at a small example of where optimization falls apart, and then a big one where it actually works.

Restaurant Email Campaigns

As I’ve mentioned before, I’m an investor in a restaurant. In general, it helps me have a pretty applied look at consumer behavior, price discovery, and microeconomics. We’ve been sending out weekly email marketing campaigns for about six months now. The workflows are mostly automated (except for the copy pasting, image uploads, and hitting “send”), and we’ve sent over 84,000 emails so far.

With that many emails, you’d think we’d have found some sort of causal relationship between what we promote, the CTAs we use, and the content itself. But nope, none whatsoever. Take a look at some of the campaigns below:

We send roughly 3000 emails each time and see about the same open rates. And yet, the sales attribution is all over the place. Just to double-check, I went back and looked at each campaign’s conversion funnel. The click-through rates (CTR) range from .5% to 2.3%, but there’s no causal link to sales performance.

Does it mean email marketing is a complete waste of time? Not at all. For us, it serves a very specific purpose: a weekly reminder to our patrons that we actually exist.

Here are two extreme examples:

The wings promotion, which brought in $2k in attributable sales, had a terrible CTR (.43%) and almost no downstream engagement.

The “Thank You” email, which generated just $10 in sales, had a decent CTR (1.67%) and even a few personal emails thanking us for improving the service.

To really nerd out, I ran an r-squared analysis across all 84,000 emails and couldn’t get a better result than .09 (technically, .088) relating open rates vs revenue per campaign. It was worse for CTR vs Revenue per campaign. For the record, those are terrible numbers.

Does it mean email marketing is a complete waste of time? Not at all. I mean, we could just be terrible marketers, but for us, it serves a very specific purpose: a weekly reminder to our patrons that we actually exist. It’s a recurring awareness campaign, a way to stay top-of-mind without breaking that social contract we’ve established. Customers might order online, book a table, or even just stop by to say hello and tell us they’ll be back later in the week (and seriously, this actually happens). So now we just have fun with our emails and don’t obsess over the performance metrics at all.

But how does this relate to you? Well, dear product person (potentially hiding behind your Product Marketing Manager), especially if you’re in a B2B situation, you’re likely dealing with similarly small, segmented customer lists and an email cadence that’s probably no more frequent than once a week. At that level of scale, something like A/B testing is likely going to give you very little statistical significance and you’re probably kidding yourself to think you’re finding any real insights. Instead, you’re better off focusing on building a good product, establishing a consistent tone/brand in your communications, and connecting with your customers on a human level.

Don’t worry about the direct ROI of every single email or test. As long as it’s not sucking up a disproportionate amount of your budget or resources, consider it an investment in an intangible asset – and tell your management that Deven said so. (Also, send them a link to this article so you can cover your butt!)

Facebook - Experimentation on a Different Planet

Let’s talk about Facebook’s iOS app. It’s been a while since I chatted with members on their iOS engineering team, but last time we spoke a few years back, the source code was already a staggering size. I’m talking 7 GB before it even gets compiled into a binary! I can only imagine it’s much larger now, with countless teams contributing code.

But the truly mind-blowing part is their testing infrastructure. I think it had something like 6,000 tests running constantly within the app? Performance tests, UX experiments, you name it. They’re tweaking everything, all the time.

Of course, they can do this because they have access to a third of the world’s population using their app. This works because of their insane scale, but it probably started working when they had just a few million users. They have entire teams dedicated to this kind of over-optimization, focusing on everything from increasing user conversion to boosting the percentage of chats using end-to-end encryption. And it’s not always directly about making more money; it’s about driving key company priorities - like making sure their users migrate to Threads.

You, dear PM, likely aren’t at Google, Meta or the like. Even if you are, you might not be on a Product that can tap that much user engagement within that company.

So if over-optimizing isn’t the holy grail for most people, what should you be doing?

Great Products Don’t Start with Math Experiments

It’s definitely not about blindly following personas, relying on gut feelings, or just building it and hoping they will come. There’s nuance, for sure, but it largely boils down to three key things:

1. Nail the Essentials (and Resist the Urge to Over-complicate): Focus on locking down the core functionality that your actual users are begging for. Then, resist the urge to mess with it too much. When we were building MGP to support the largest mapping and government customers on the planet, we were bombarded with requests from every direction. As one Sales Engineer yelled into my Teams chat (in ALL CAPS, naturally): “Make sure you have usable analytics!” Another well-meaning senior engineer chimed in: “I found three [not-so-big] customers who really want this one feature my team and I designed. Can we put it in there for launch?” But meanwhile, our 25 largest customers were unanimously screaming something to the tune of: “Can you just... find a f#$%ing reliable way to give me the data I want, when I want it, without making me create 5 different accounts or sign 3 contracts to do so?!” So that’s what we focused on: one single identity to access any content across all of Maxar, two client apps (one simple and one Pro-mode), open well-documented APIs to support streaming and downloading of ALL content types, and most importantly - everything finally under one contract vehicle the customer could actually sign.

2. Focus on 1-2 Financial Targets (and Ruthlessly Prioritize): Keep your eye laser-focused on the prize. What are the most important financial goals for your product? What are the metrics that truly matter? Everything else is just noise that will distract you and your team. I can’t go into too many specific details, but I can tell you that we had two big, overarching goals for the new platform at Maxar: First, Move all existing customers (and their existing revenue) to the new platform as quickly as humanly possible. Thankfully, there wasn’t too much friction here, internally or externally, once we built up some momentum. Second, Make sure we increased our overall book of business by XX% by offering a true value-add that would be universally recognizable by both our largest and smallest customers. That’s it. Everything we did was ruthlessly prioritized against those two goals. It helped us avoid chasing every new shiny thing. More importantly, establish trust with our customers and with our internal customer-facing teams (sales, customer success, reseller relations, technical support, etc.).

3. Match Simplicity (or Complexity) to Usage Patterns: Recognize how frequently your product is used and design accordingly. Don’t force simplicity where it hurts, and don’t overcomplicate where it’s unnecessary.Think about Excel. There are definitely times when you need customers to just come in, do something quickly, and get out. But what if you were trying to do really intricate macros, and the next software update made Excel look like Numbers?

Ignoring the oddities of AppleScript vs VBA, you’d probably blow your brains out and have your Microsoft account manager on the phone in 10 seconds. There are often times when a tool doesn’t need to look “clean and minimal,” and oversimplifying it actually hinders power users who rely on it on an hourly or daily basis. The workflows themselves need to be simple and efficient, but the tool itself might need to offer a rich set of features and options to support complex tasks.

Remember the People

Ultimately, the best product decisions aren’t always driven by data. While data is undoubtedly valuable, it’s just one piece of the puzzle. Sometimes, the most impactful decisions for a product come from empathy, intuition, and a deep understanding of your users’ needs. It’s about resisting the urge to over-optimize every tiny detail and instead focusing on the bigger picture: solving real problems for real people. So, take a moment to reflect on your own approach to product development. Is data guiding you, or is it clouding your view of the human element that truly drives product success? Are you so focused on optimizing the trees that you might be missing the forest?

So I know that’s quite the provocative title for a newsletter post. This post will start out about day-to-day product management and then it’ll go into a slightly larger sphere and topic. I’ll try to make it as easy of a line of thinking to follow as possible.

It’s common for PMs to have adversarial relationships with other PMs. Sometimes, there is limited engineering capacity and all things can’t be built all at the same time. Most of the time, you like your coworkers enough that you come to some sort of compromise between yourselves or...also with a third party. An example being a Senior Leader conceding that one PM won’t be able to demonstrate significant movement towards their OKR, KPI or any other acronym that’s hot these days. This way it’s known that come performance review season, this won’t be held as against them for some of the acronym measurements as there just wasn’t a way to prioritize everyone’s roadmap given the constraints.

The Zero-Sum Trap

But other times, that compromise doesn’t work out. You have PMs engaging in zero-sum activities to ensure the survival of their own product strategy. This is also quite common, and I’m the last person to judge here. Given the constraints, who wouldn’t want their product or the team they’re responsible for to succeed? After all, a couple of missed marks could mean the difference between a promotion or regrettably being put on a spreadsheet (metaphorical or literal) for the next round of layoffs. This is an outcome no one wants, certainly not your manager or your senior leadership, but in the current climate, quite the in-vogue thing to do.

It felt like a battle royale. The first meeting was a mess. We had flown people in from all over the country, and it mostly resulted in a lot of shouting. When we walked in after lunch, we had to change the dynamic.

The Proactive PM: Taking Control

Okay, so we’ve established that the zero-sum game is a real thing. But we’re not helpless! As PMs, we’re supposed to be proactive problem-solvers. So, let’s focus on what we can control:

• Get People to Work Together For Real: I’ve been in situations where things got...heated. I remember one pricing strategy discussion with a dozen PMs, all fiercely advocating for their own product. The goal, of course, was to figure out the best way to price things to everyone’s benefit. But in the moment, it felt like a battle royale. The first meeting was a mess. We had flown people in from all over the country, and it mostly resulted in a lot of shouting. When we walked in after lunch, I knew we had to change the dynamic. I started by reminding everyone that our ultimate goal was to make the company successful, not just our individual products. We needed to focus on increasing renewals, even if it meant making some compromises. For example, Company A used to buy Product 1 for $100/year. Instead of losing them or accepting a lower price renewal, we offered them a bundle of Products 1, 2, and 3 for $130/year. Product 1’s revenue might have looked a little smaller on paper, but the overall deal was better for the company because it improved revenue retention and likely led to future upsells. The key was shifting the focus from individual wins to collective success, aligning incentives around shared goals like margin expansion and long-term customer value. I was lucky that most of the people in the room were my direct reports, but even without that authority, the outcome could have been the same – it would have just taken more time and patience, as long as they saw my conviction.

• Prioritizing Your Well-being: This is going to sound cheesy, but take care of yourself. Burnout is real, and it makes you a worse PM. Set boundaries, take breaks, and find healthy ways to manage stress. I can’t tell you how many times I’ve had to remind certain members of my team of this. In the thick of it, you might just feel some combination of imposter syndrome, sheer ambition, and a need to prove yourself. This will absolutely lead to exhaustion and you don’t want to deal with it when it’s too late (frankly, you’ll be in denial by then.)

• Manage People in Every Direction: Being able to influence people, regardless of their position, is a superpower. As a PM, you’re constantly negotiating, persuading, and collaborating. This means understanding different perspectives, communicating effectively, and building trust. Whether you have direct reports or not, mastering these skills will make you a more effective and respected PM. Think of it as building a “coalition of the willing” around your product vision. For example, imagine you need engineering to prioritize a small but critical feature for a key customer. You could demand it, pull rank, or try to guilt-trip them (we’ve all been there). Or, you could take the time to understand their workload, explain the impact on the customer, and find a way to make it a win-win for everyone. Maybe that means offering to help with documentation, testing, or even just bringing them coffee and listening to their gripes about the build system or the CI pipeline. You could also offer to help write test cases, clarify requirements, or even just clear their schedule for a few hours so they can focus.

• Be Likeable, But Don’t Be a Doormat: You need to be able to have allies everywhere and at any time. Life is about dealing with information asymmetry of all kinds. You never know who is going to show up for you, who is going to ghost you, or worse, who will actually undermine you in the future. It is in your control how much people will show up for you, but it’s not for free. Building bonds and maintaining relationships takes time – time that could be spent towards family, friends, or pets (though I do feel differently when my dog just refuses to poop and play around when its freezing cold outside). You’ll have to choose how many non-workday coworker conversations you’re willing to have. The most successful people deliberately figure out what relationships are worth taking time away from all your loved ones.

• Help Others Without Expecting Anything in Return (Not Even Secretly): You want a good village around you. You might not have the full skillset to help another team member, but there is likely a way to help when help is needed. I’ve worked with my friend, Zara Khan, on a large BD presentation she was going to have with a major Agriculture company after hours when it had nothing to do with my work. The only incentive I had was that I’d have a friend to eat dinner with right afterwards. A colleague in FP&A years ago, Judy Hao, helped me with some complex sales reports that would have taken me a week to compile. She did them in an hour, even though I’m sure she was slammed with her own priorities. I still remember that (Thanks Judy.) You can be someone’s “Judy” too. These impressions are lasting and carry forward goodwill for moments you can’t ever predict. It’s what we do to help our village.

• Cover your economic foundation: This isn’t easy for a 25-year-old with no major responsibilities OR for a 45-year-old with a family. The key is to build antifragility – the ability to not just withstand shocks, but to benefit from them. (we talked about this in a previous post) This takes time and might mean sacrificing some upside or fun in the short term. If it is possible, try and find ways to live below your means. Every month of financial runway you can build for yourself can give you that much freedom to not operate out of fear. Think of it as building a financial “buffer” that allows you to take risks and pursue opportunities without being paralyzed by anxiety.

Systemic Issues (The Bigger Picture)

But money can be borrowed. Time, on the other hand, is a truly limited resource. You can’t leverage it.

Of course, even with all these individual actions, the current system often feels rigged. The incentives aren’t aligned to encourage collaboration and long-term thinking. As Scott Galloway likes to say, America embraces “full-body-contact capitalism,” but unfortunately...it often pushes employees to focus on the lowest common denominator: win at all costs, get that promotion at all costs, keep your job through the next round of layoffs at all costs. It feels less like a fair game and more like survival of the harshest and luckiest.

I don’t have a solution to this. It’s a systemic problem, and individual actions can only go so far. But it’s important to acknowledge the adversarial dynamic between labor and capital. In more egalitarian societies, cooperation is often prioritized over one-sided growth. In the US, that’s not always the case. We often prioritize capital (and the return of capital), arguing that investors take on the most risk. But money can be borrowed. Time, on the other hand, is a truly limited resource. You can’t put leverage on it. Your kid’s birthday only happens once. Your anniversary dinner only happens once (a year). Time should be valued higher. I have a strong feeling that work culture in the US trickles down (sighs.) from having a value system like this.

The AI Wildcard

And now, we’re facing the rise of AI...whatever that means. Will this exacerbate the problem, leading to even more pressure on workers and a greater frequency of zero-sum games? Or can we find a way to use AI to create a more just and sustainable future? The answer depends on the choices we make at the company and societal level. I have ideas, but they’re at best half-baked. Maybe I’ll flush them out enough to talk about them one of these days.

The last three years have been a wild ride, watching PMs adopt and sometimes abuse new tools (especially fancy schmancy AI tools) to make their lives easier. As someone who’s managed my fair share of product folks, I’ve seen it quite a lot. Whether you’re running Product Ops, a market-facing team, a core engineering group, or something in between, here’s what I’ve learned - I’m loosely going to nickname three types of PMs in the “AI” age that I’ve seen. There may be others, but for today we’ll talk about these:

• the Outsourcer: Those who blindly trust AI to do their jobs for them (like the one who phones in their customer or market research, or “auto-writes” stories based on a standard template. You know...the one who thinks they’re a “10x PM”)

• the Apprentice: Those who use AI as a learning tool and a way to improve their craft (like the one who uses vision or multi-modal models to prototype designs because there may not be enough designer capacity in the company to help them immediately)

• the Orchestrator: Those who understand that AI is a tool, not a replacement, and use it to amplify their own strengths and fill in the gaps. (like the one who uses a model to help write a six-pager or PRD, but then has other models review the work, perhaps goes back and forth with them)

I want to offer two ways we can avoid being an Outsourcer and become an Apprentice or Orchestrator (depending on whats needed in the moment). Before we dive in, let’s be clear: PM certifications or Extension Degrees aren’t helpful for this. They might help you land a job because HR departments and Hiring Mangers still look for this, but they don’t guarantee you’ll be a good PM. They’re more like building construction codes – they set a minimum standard, but they don’t teach you great tradecraft. So, let’s skip the theory and focus on real-world examples.

Write Better Stories

If you’re a PM, write better stories damn it. More human. More relatable.

Whether you’re an engineer, a project lead, or a PM yourself, you’ve likely come across the “As a User, I would like to get the ability to do X when I enter this part of the tool. See requirements and acceptance criteria below.” stories. They suck. PMs hate writing them. Engineers hate reading them. And the future PM and Engineer who needs to reference them 10 months from now will hate looking for them to cover their ass. And if that person in the future is you, you’ll doubly hate it if you’re on the losing end of a dispute.

Stories are meant to be just that...they’re stories. We should write them in a narrative form that actually provides context. They’ve also been much harder to write in human form because it requires quite a bit more time than most PMs are willing to spend. It’s also not something that can be templated for quick and easy writeups that our 10x PM friend likely wants.

That same sentence above could easily be written as “One of our Solutions Engineers, Jamie, uses our platform to do a lot of things on a daily basis. They recently helped Brenda at “Brenda’s Paninis” get all her gourmet sandwiches made in top quality in under 10 minutes on average. But sometimes, when the lunch rush is at its peak and customers are getting hangry, those 10 minutes really matter. Jamie really needs to be able help trigger a customer SMS notification to let Brenda’s customer’s know their panini is almost ready. They need to be able to send that SMS fast so no sandwich goes cold. Let’s try to support all the Jamies out there. It may not always be paninis, but you and I both likely want our next ramen or burger made that much faster. They don’t need all the bells and whistles, but clearly they need to make sure those SMS notifications get sent reliably, or at least in this case, Brenda just might lose it. Additional details below: (technical details)”

Does this feel like it adds fluff? No doubt. But will an Eng Lead actually enjoy reading this requirement? Absolutely. Will that Eng Lead reviewing your ticket message you a 😂 emoji or a Denzel Washington My Man GIF* after reading that story?

Maybe...probably not if they’re GenZ though. They’ll use 💀 for some nihilistic reason I don’t fully understand.

The revised story I wrote was a little funny and it also talked about what the end-user actually had as an outcome from that product so the engineers know a bit more about what’s going on. A small tidbit outcome like this across 300 user stories can slowly build customer intimacy on the engineering team that no Customer Feedback meeting or All Staff Presentation could compete with. So it’s just a simple plea from myself. If you’re a PM, write better stories damn it. More human. More relatable. It’s never been easier to do so and you’re likely smart enough to get a (company approved) LLM to help you with this.

Here’s how an Apprentice and Orchestrator might approach this:

• Apprentice: Uses an LLM to rewrite the standard “As a User...” story into a more narrative form. The story would stop being generic and gets a strong connection to the user’s actual needs for anyone reading that story.

• Orchestrator: Leverages the company’s internal AI tool to integrate with Salesforce, pulling data on how much $ in existing sales contracts could benefit from the SMS notification feature. They may even go as far as calculating contract renewal risk in dollar terms if this feature doesn’t get built out, presenting a compelling business case to leadership. This kind of math used to take forever, but now, you can just have an LLM do most of the work and then review it at the end.

Just make the life of your nearby team members better. Your Product Marketer can be closer to the product and the Engineers. Your Engineer can be closer to the Customer.

Why is it taking so long to ship?

It has never been easier better understand code for a PM who doesn’t code, but wants to be just a little bit more technical. Largely, you might want to know the contents of a repo that runs the product or feature you’re responsible for since...it’s what you’re responsible for.

I mean, it could be because you’ve heard “gah, we’re still seeing race conditions when we merge and run the updated code.” from your engineer for the 10th time now. Then you’re pulling your hair for why that’s a problem and not another reason your product is ready to sell to F1 teams. But likely, you’re just annoyed you’ll have to tell your boss or your 5 most important customers that they’ll still have to wait before the new thing can get shipped for them to use.

You can use Cline or some other open source tool with a little bit of upfront setup to better understand the code. Below, I just downloaded the Ollama repo from Github and asked Cline (connected to the Gemini API, but you can also use local models too!) to explain something inside the repository to me. It’s a simple example, but the sky is the limit for how you can make this work for you. Mostly, though, you might want to use this to help you learn more technical concepts inside your codebase at your own pace.

Why go through all this? Well...you might have an engineering team who would rather focus on fixing an issue than to have to hop on a meeting to explain something to “Senior Leadership” taking time away from solving the problem. This helps you be a better first line of defense for your team. (NOTE: The lesson here isn’t to gatekeep important, perhaps consequential, discussions from your engineers. It’s to give them an option to opt-out should they trust you enough to handle things on their behalf)

Here’s how an Apprentice and Orchestrator might approach this:

• Apprentice: Uses Cline to explore the codebase, hoping to understand the basic concepts so they can participate more effectively in technical discussions. They document their findings and share them with the team, hoping to spark some knowledge-sharing. This newfound (and still limited) knowledge helps them have more productive conversations with both senior leadership and the engineering team.

• Orchestrator: An Orchestrator might go a little beyond this. While contributing to external-facing codebases is generally a bad idea for a non-engineer, there are plenty of places where internal tooling can be improved. An Orchestrator might identify a need for a better internal tool or an open-source one and then use AI to accelerate the development process, working closely with engineers to bring their vision to life. My colleague, Chris Holmes, is a perfect example of this. He even published a tool to download GeoParquet data from cloud sources via QGIS, built using Cursor and Claude. He published his journey of making it happen that you should take a look at.

Look, obviously AI isn’t going to solve all our problems. The real challenge for us as product managers is to use these tools to do things that actually make a difference. It doesn’t even have to be done at scale. Just make the life of your nearby team members better. Your Product Marketer can be closer to the product and the engineers. Your engineer can be closer to the customer (without actually having to talk to them, unless they really want to). Challenge the way things have always been done. Create products that are not just innovative, but also ethical, responsible, and human-centered. And maybe, just maybe, in the process, we can become better leaders, better teammates, and better people.

I wanted to wait until I could get a few Product-related things published before I posted something like this, but I recently stumbled upon a video from food youtuber Internet Shaquille about sports betting that really got me thinking. (You can watch it here if you’re curious.) The gist is that sports betting is surprisingly detached from sports knowledge, relying heavily on stats and probability. More alarmingly, it’s a largely unregulated space where platforms can ban you for being too good. If you’re active on one of those platforms for more than a few weeks, it’s because you’re likely to lose money than win anything of significance.

Shaq’s concern is that this is being pushed on people so effectively that we may not be aware of the societal problem until it’s too late. This reminded me of tech (and I mean “tech” broadly, from engineering teams at United Airlines to Instagram), where individuals often have little chance against the strategies of large companies. Think about dynamic pricing or customer retargeting – complex topics with potential regulatory pushback. They’re also things I’m not fully qualified to talk about.

But today, I want to focus on something different: the human side of what we do with our money after we’ve earned it. If you’re reading this, you’re likely in your peak earning years (25-50), but that doesn’t always mean smooth sailing. Perhaps you’re stuck in a job that pays the bills but slowly drains your soul. Or maybe you’re facing the uncertainty of unemployment, navigating the stress of job searching and financial insecurity.

Forget the usual platitudes (”time in the market vs timing the market,” “index funds, rest and vest,” etc.). Let’s really dig into the motivations behind how people spend and “invest” their money – especially when the stakes feel higher than ever.

Whether it’s you or friends you’re seeing dive into sports betting, crypto, or individual stocks, or you’re watching the next generation grapple with these choices, it’s our money, and in times like these, it’s especially important to talk about it. After all, wealth is like good thyme... always well spent! (my one and only forced dad joke, I promise)

I see three main categories, though there are definitely more:

1. Lack of Market Context: Bull Markets Make Fools of Us All

There’s nothing like the feeling of refreshing your portfolio and seeing you’re $5,000 richer than when you went to sleep. That optimism is intoxicating.

This next section may seem obvious to you, as it did to me, but the truth is, when you’re in it, it’s almost impossible to pull yourself out. We know the following in theory, but it’s worth exploring anyways.

If you’re under 30, the 2008 Financial Crisis is probably just a chapter in a history book. And if you discovered crypto during the pandemic boom, you haven’t truly felt the sting of a crypto winter. (Unless you’re actively building in the Liquidity, Treasury, Wallet, Brokerage, or Transactions space - if so, then you know more about crypto, and most definitely more than I know about crypto.)

I know – everyone says “just DCA, set it, and forget it.” It sounds so simple, right? But speaking from experience, there’s nothing like the feeling of refreshing your portfolio and seeing you’re $5,000 richer than when you went to sleep. The optimism is intoxicating – you start thinking, “I’ll be another $2,000 richer by tomorrow!” No one is immune from the sports betting tendencies we talked about.

That’s the bull market talking.

I’ve been through four cycles since 2007, and each one has taught me a somewhat painful lesson. Bear markets are brutal and watching it happen to someone else on the news will give you no real context. You don’t know when they’ll start, how long they’ll last, or if you’re going to be the genius “buying the dip” or the idiot who didn’t know when to quit. Volatility only helps if you’re making controlled, almost algorithmic bets over a long timeframe (and maybe with a tiny bit of leverage, but that’s a dangerous game). Otherwise, it just crushes your mood (at best) or your net worth (at worst).

2. Building Antifragility: Navigating a World of Disorder

Our risk tolerance changes as we go through life. What seems like a great idea as a young, single adult just starting out in a tech job with nothing too lose might not be so appealing when you have a partner, a pet, or children to think about. Likewise, losing a chunk of your portfolio after having built so much can shake your confidence for years.

They’re convinced you’re one lucky trade away from early retirement. It’s like thinking you can win a Michelin star by microwaving a frozen dinner.

But enough people I know in life have successfully side-stepped the rat race with a crazy amount of discipline. Nassim Taleb calls this “Antifragility” – the ability to not only withstand external shocks, but to benefit from them. It’s about avoiding trends, not blindly accumulating risk, and being ready for asymmetric opportunities. It’s often a boring strategy of doing business as usual until it’s time to act decisively.

Think of it like this: one group of investors opens five trendy poke bowl restaurants, taking on debt, a large staff, and perhaps franchise royalty payments. They’re riding the wave of the latest food craze. But as demand slows down...they’re forced to close - immediately and violently. Another family runs a local, beloved Ethiopian restaurant, serving classic dishes passed down through generations. They own their building, have a loyal customer base, and weather every storm because they’re not chasing the latest fad.

But they don’t just survive those storms – they thrive. When a new wave of health-conscious customers arrives, they highlight the naturally vegan and gluten-free options in their cuisine. During an economic downturn, they offer discounts to community workers becoming an even more integral part of the neighborhood. And when a nearby restaurant struggles, they conservatively acquire the failing restaurant’s assets at a discounted price, expanding their capacity and reach without taking on excessive risk.

Now, I’m not suggesting you go out and start buying restaurants (unless you have a passion for injera!). The point is that adopting this mindset of measured, opportunistic growth can be beneficial in other areas of your life. It’s about building a foundation that can withstand shocks and then strategically capitalizing on opportunities when they arise.

3. The Empathy Gap: Your Comfort Number Isn’t Everyone Else’s

You might be tempted to skip this section, thinking, “I already know what’s best for me.” But before you do, consider this: in our increasingly isolated world, it’s easy to lose sight of the diverse financial realities people face at different stages of life. With fewer “third spaces” to connect and share experiences, we often struggle to understand perspectives beyond our own.

Those who achieve financial success often unintentionally impose their worldview on others, sometimes for better, but often for worse.

So, resist the urge to skim. Invest the next few minutes in stepping into someone else’s shoes – even if they seem radically different from yours. It might just challenge your assumptions and help you adjust your own risk profile. These are all friends of mine, but the age and titles have been slightly adjusted to respect their right to privacy so you can’t reverse engineer them from my LinkedIn profile.

We all clutch our pearls (or wallets) at different numbers – $50k, $500k, $2 million. But the moment that happens, a switch flips, and it’s less about aggressive growth and more about preservation. And while there’s nothing wrong with that, it’s important to remember that your “comfort number” is just that – yours.

But here’s the catch: those who achieve financial success often unintentionally impose their worldview on others, sometimes for better, but often for worse. This leaves those in the middle without a clear gauge of whether they’re on the right track.

So, before we dive into specific scenarios, let’s just take a breath and acknowledge that we all have blind spots. Our own experiences inevitably shape how we see the world, and that includes our financial perspectives.

Scenario Breakdown

23, Fresh Out of School, Less Than $50k Invested: They’re living on instant ramen and dreams, glued to r/wallstreetbets, convinced they’re one lucky trade away from early retirement. It’s like thinking you can win a Michelin star by microwaving a frozen dinner. Not happening, boss.

• Financial Priority: High-risk, high-reward investments with the goal of quick gains (and paying off those student loans...eventually).

• Fragility: Highly vulnerable to market downturns and bad financial advice.

• Antifragility: They’re treating every “YOLO” trade as a learning opportunity after the last two years. Documenting wins and losses, analyzing mistakes, and using that knowledge to develop a more informed investment strategy.

28, Director of Product Marketing at a Series D Startup: Hustling 60+ hours a week, drowning in VC buzzwords, and secretly wondering if “democratizing AI-enabled ERP solutions” is actually making the world a better place. Also, secretly terrified of the Patagonia Vest Recession finally catching up to them.

• Financial Priority: Paying down student loans, keeping up with rent in a HCOL area, and pretending they’re not living paycheck to paycheck.

• Fragility: Heavily reliant on a single job, no way to get a line of credit based on equity position in the company and very vulnerable to layoffs in a currently volatile industry.

• Antifragility: They started a “f#%k you fund” – only promising to do 40 meaningful hours at work and instead will focus on a side hustle or investment account that generates enough income to get the freedom to walk away from a toxic work environment. They’re basically building their own personal parachute.

35, Great Job, Medium/High Cost of Living: Staring blankly at their laptop screen, fantasizing about quitting to backpack through Southeast Asia, learn pottery, or finally write that novel. (But $3,800 in rent is due next week...)

• Financial Priority: Saving enough cash to escape the 9-to-5 grind, even if it means sacrificing long-term investments (and ignoring the nagging feeling that you’re falling behind).

• Fragility: Dependent on a single source of income and vulnerable to burnout and dissatisfaction.

• Antifragility: Instead of quitting cold turkey, a friend of mine has started experimenting with “mini-retirements” – taking a week or two off to pursue your passions and see if they can turn them into a viable income stream.

42, Principal at a Management Consulting Company, Two Kids in Elementary School: Spending weekends reviewing client decks, attending partner meetings (virtually, of course), and secretly wondering if you’re actually making a difference in the world, or just helping corporations become more efficient at extracting value.

• Financial Priority: Maximizing firm profits, securing new clients, and ensuring a comfortable retirement.

• Fragility: Dependent on the firm’s success, vulnerable to economic downturns, internal politics, and constantly battling burnout from demanding clients and travel schedules.

• Antifragility: They’re leveraging their consulting expertise to write a book on a niche topic within their industry and investing in couple of early-stage companies that are specifically disrupting the consulting model. They’re basically creating a “put option” on their career which I thought was really freaking smart.

58, Empty Nester, Mortgage Almost Paid Off: Finally has some breathing room, but now they’re obsessing over optimizing their 401k, terrified of outliving the savings on hand, and wondering when they should finally take those extended vacations with their partner to another country.

• Financial Priority: Catching up on retirement savings after years of putting the kids first, and desperately hoping Social Security will still be around when you need it.

• Fragility: Overly focused on financial security and potentially missing out on opportunities for joy and fulfillment.

• Antifragility: This isn’t happening just yet, but they’re hoping to “un-retire” soon – they’re hoping to find a part-time job or volunteer opportunity that allows them to use their skills and experience to make a difference in the world, but can drop things on a moment’s notice when its financially opportunistic to drop their work and ship off to that country for a couple of months.

So, there you have it. From YOLO trades to exit strategies, everyone’s cooking with different ingredients.

The key? Let’s ditch the tunnel vision. Maybe take a little antifragility from someone else’s phase in life and it might do us all some good.

It’s less about some sci-fi future and more about finding small, practical ways to reclaim my focus and, dare I say, sanity. I’m not suddenly living on a beach sipping margaritas (though that is tempting), but I’m finding pockets of time and mental space I didn’t know I had. This says something larger about who might eventually benefit from all these investments made into what we’re broadly calling “AI’ these days.

Here are a couple of examples of where this curiosity has led me:

Email Marketing: Saving Our Cuban Restaurant (and My Sanity) with a Little AI Magic

I’ve got a soft spot for small, local businesses. A while back, I invested in a neighborhood Cuban restaurant. The financials were pretty good prior to my investment. More importantly, the food is incredible (best cubanos in this part of town!), the atmosphere is warm and inviting, and the staff is like family. But they were struggling to find the time and resources to effectively market themselves.

We all know how important email marketing is for staying top-of-mind with customers, announcing specials, and building loyalty. But for a small restaurant, it’s often the last thing on the to-do list. The staff is busy prepping food, serving customers, and keeping the place running smoothly. Hiring a marketing agency was too expensive, and trying to manage it all manually or in-house was a time-consuming nightmare. Which is why they hardly did it!

Could we have done it the old-fashioned way? Sure. And also in 30 seconds for next to nothing? Absolutely not.

There had to be a better way. I wasn’t looking for a silver bullet, but I was hoping to find a way to streamline the process and make it more manageable for myself.

After a bit of trial and error, I stumbled upon a workflow that works surprisingly well. I won’t go into how in this write up since that could be a rabbit hole of its own, but we’re semi-automating our email campaigns, allowing the staff to focus on what they do best: creating delicious food, cocktails, and providing an exceptional service.

Here’s how it works: Each week, the manager and staff spend a few minutes scanning local events, holidays, and any special promotions we want to highlight. Then, we use that information to automatically generate a short, engaging email (under 180 words) for our subscribers with the tone and brand identity that the restaurant had already cultivated. The “context length” in this one conversation that’s been ongoing with an LLM keeps the essence as we write more copy.

The real magic? Instead of hunting for stock photos that almost capture the right vibe, we use Flux to generate custom images. For example, if we’re running a campaign around the Bank of America marathon, we can generate an image of a runner of Latin-descent sipping a mojito post-race. Try finding that in a stock photo library!

Could we have done it the old-fashioned way? Sure. And also in 30 seconds for next to nothing? Absolutely not.

And where does that saved time go? Honestly, to whatever I feel like doing. Polishing glasses at the restaurant, squeezing in a workout, or just closing my eyes for 20 minutes while listening to nature lofi music. It’s a small win, but it makes a difference.

(A Note to Product Marketers, but also the Product Managers hiding behind them: I keep thinking about the AI-powered SaaS products aimed at SMBs. There’s definitely a willingness to pay for value, but the price point has to be right and half baked tools are just as bad as single-utility gadgets in any kitchen. My goal is always going to be to reduce operational costs and empower the staff to focus on the customer experience. There is no way a subscription SaaS product could replace just the minutes I now spend creating targeted, cost-effective email marketing for almost-free. I can find ten other examples like this, too, by the way, and it’s probably the reason why most restaurants use, but at-best tolerate Toast, Clover or Square and their bloated offerings)

Healthcare Advice: Without Getting Lost or Annoying Your Doctor (or Wife, in my case)

Okay, this is where things get a little more delicate, and I want to be super clear: I’m not suggesting we replace doctors with AI! The human element in healthcare is irreplaceable. But I am fascinated by the potential to improve the patient experience and make the healthcare system have more effective outcomes. For doctors, they’re already using AI-enabled scribe software to securely record a conversation between a patient and a provider and auto-summarize charting notes for final approval. But what about the patients?

It’s like having a knowledgeable and patient friend who can help you understand basic medical information and guide you toward the right resources.

I’ve been using Pathway Medical for a while now. Initially, it was a helpful resource for accessing medical research, similar to UpToDate. But honestly, the language was often dense and hard to understand. I found myself constantly turning to my wife (who works in healthcare and hates how often I bother her with these questions) to help me decipher the medical jargon and understand the implications of the research.

That’s where Pathway’s AI chat feature comes in. It’s like having a knowledgeable and patient friend who can help you understand basic medical information and guide you toward the right resources. I’m talking about those “Tier 1” questions that don’t necessarily require a doctor’s appointment but can still cause anxiety and uncertainty.

For example, instead of frantically Googling “sudden rash after trying new laundry detergent” (and inevitably landing on a worst-case-scenario diagnosis), I can ask the AI chat, “I have a mild rash after switching laundry detergents. Could it be an allergic reaction, and what are some simple remedies I can try at home?” The AI can provide helpful information, suggest over-the-counter treatments, and tell me when to seek professionals. See below:

This kind of AI-powered support can potentially alleviate the pressure on urgent care clinics and ERs by addressing those low-acuity cases that often clog up the system.

Again - The key is to use these tools responsibly and understand their limitations. AI can be a valuable resource for preliminary information and guidance, but it should never replace the expertise and judgment of a qualified healthcare professional.

So, that’s my ongoing exploration in a nutshell. It’s been less about finding magic bullets and more about discovering unexpected ways to simplify my life and free up my time. I’m still very much in the “experimenting” phase, and I’m curious to hear what others are discovering. The next few years are definitely going to be interesting with all this “AI” stuff.

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