A Learning a Day

Sometimes the best way to understand what your gut is telling you is to pay careful attention to your energy as you weigh possibilities.

Our reaction to a particular stimulus often says more about our values and state of mind than the stimulus itself.

The same comment can roll off our back one day and ruin our day in different circumstances. And the same setback can feel like a minor bump or a catastrophe – depending on the day.

Our reactions often reveal more about us than the situation.

“The real problem of humanity is the following: We have Paleolithic emotions, medieval institutions and godlike technology. And it is terrifically dangerous.” | E. O. Wilson

I’ve been thinking about this quote a bunch over the past weeks. It is pithy and profound.

The fart walk is an admittedly crude but catchy name that’s become popular recently as a modern rebrand of the post-meal walk.

As I’ve shared a few times over the past months, one of the things I found revelatory from wearing a continuous glucose monitor was the impact of a walk after meals. Taking the time to do a roughly 2,500 step walk – about 1.2 miles or 2 kilometers – goes a long way in managing our post-meal glucose spike. And ensuring that, especially at night, that glucose doesn’t become triglycerides.

These walks have the added effect of reducing bloating by aiding digestion. Which for a lot of people translates to farting and post-walk pooping.

The name is hilarious. But I’m all for a catchy way to label an activity that has almost magical health effects, especially when done at night.

We’ve made it a rhythm now for a fart walk as a family. It’s a lovely way to close the day because it is a win-win-win on health, conversation time, and time with nature.

Here’s to many fart walks in 2026.

Things feel better when we have fewer things in the “I expected that” category and more things in the “wow, that was a bonus” category.

Let the bar be high on how we go about our process and low on the outcomes we expect from them.

Pericles led Athens during its golden age in the 5th century BC.

He invested heavily in infrastructure – the Parthenon, temples, public buildings that still stand today. He expanded democracy and turned Athens into a cultural center that attracted philosophers, artists, and thinkers from across Greece.

But what struck me most about Pericles was his inspiration from Athena – the goddess of wisdom and strategy.

He espoused a brand of politics built on rationality, thoughtfulness, and strategic thinking. Not rhetoric and appeals to base emotions.

This even showed up in his style as a public speaker – he shunned drama for a more quiet and thoughtful style.

As he became a marginal figure toward his passing, Greece ended up in wars against Sparta that drove them toward ruin. They made wagers driven by emotions that were the antithesis of the decision-making Pericles had championed.

He was clearly so far ahead of his time in his approach.

It got me thinking about the habits needed to periodically channel our inner Athena – stepping back to make decisions rationally – are critical.

Especially in a world designed to trigger our base instincts at every turn.

AI was one of the topics that dominated the zeitgeist in 2025. There’s so much happening at any given moment and there’s so much more written about it that it’s hard to figure out how to make sense of it all.

That’s especially the case given the tremendous hype around this technology.

I find it helpful to think of AI in terms of three kinds of bets.

The first is working on a foundation model. This involves a select group of labs – for now, that’s Anthropic, OpenAI, Google, Meta, and a few others. The bet here is “superintelligence” – which I think is just a fancy term for an incredibly dependable AI assistant or agent that every consumer will use to navigate the internet and their digital life.

There’s potentially a tremendous amount of money to be made here. This is already evidenced by the billions of dollars of subscription revenue flowing into these systems. Just imagine what happens when you add advertising revenue into the mix and you can see how lucrative this could be for a lab that figures this out.

But ultimately, the game here is providing incredible intelligence in everyone’s pocket and really owning that market. That’s what every lab is racing toward.

Winning consumer attention is challenging and does tend to have winner-take-all dynamics. So, you also have these labs going after verticals (e.g., Anthropic for coding) as a way to hedge their bets. That brings us to the second category.

The second is Applied AI. This is going to be the vast majority of every other company that is building technology for various verticals/industries or functions. Here, the bet is simple – can you use AI to dramatically disrupt/change how things work in that particular industry or function?

Essentially, this is going to create new categories of winners and losers. New category winners who will get there by completely disrupting existing workflows. There are many industries/functions/verticals with archaic, human-heavy workflows that can all be reimagined – many for the better.

And, again, as you can imagine, there’s a lot of wealth creation that can occur here – proportional to the breadth and depth of the disruption.

The final area is AI adjacent companies. These are companies that provide tools or platforms. NVIDIA is an example of an AI adjacent company. So are the cloud providers – Amazon, Microsoft, and Google Cloud – along with fast-growing data and AI tool providers like Databricks and Snowflake.

In all of these, the bet is that as AI use continues, more and more workflows will need these tools, and these tools will essentially take a percentage of the AI economy.

I call these out in these three buckets just because this is the bet you’re making when you invest in one of these companies or when you decide to work at one of these companies. And it’s helpful to be clear about what you’re betting on.

For example, I know someone who was choosing between working at a lab or an applied AI company. It became a lot easier for this friend to figure out what they’d be interested in once the central bet was clarified.

This is not to say that these bets will all work. There are a collection of other factors – whether the energy needed for all this will be built out in time, whether AI will actually disrupt workflows in the timeframe being bet on,, and so on.

They are called bets for a reason.

Best to go in with clarity of thought and eyes wide open.

Most regrets tend to be about shots not taken versus shots taken that didn’t work out.

We remember the opportunity we didn’t take, the bet we didn’t make, and the conversation we didn’t have.

Failure at least gives us a story and a lesson.

But inaction just leaves us wondering what might have been.

Take more shots.

When you step outside on a winter day, the thermometer might say 20°C or ~70°F. But, if there’s a wind blowing, it’ll feel a lot colder because of wind chills.

It is fascinating to dig into what happens. Our body generates heat and creates a thin layer of warm air around our skin. On a calm day, that layer stays put.

But when the wind blows, it strips away that warm layer. Our body has to work harder to replace it, resulting in us losing heat faster. That’s what the wind chill measures – how cold it feels based on accelerated heat loss.

It is worth thinking about this for a second – we walk around with this invisible layer of insulation that we don’t even know exists.

Our bodies and this world never cease to amaze me.

Gokul Rajaram recently shared a post I found insightful. While intended at startup leaders, it is broadly applicable to anyone interesting in building technology products as, simple mental model aside, the central message is “be clear why you exist and measure what matters.”

Sharing in full below – thank you for sharing, Gokul.

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Every startup needs to make a choice: is their product a dashboard product or a pipes product?

Dashboard products are used directly and regularly by end users as their primary interface for accomplishing tasks. The goal for these products is to get customers to live in the product. The primary North Star metric for these companies is active users (daily / weekly / monthly, depending on the natural frequency of customer usage for the category). Facebook’s first product (aka Facebook :)) was a dashboard product.

Pipes products are used in the background to process transactions, data, payments, etc, and customers rarely interact with them directly after initial setup. The goal for these products is to for their customers to send as much of their data / payments / etc through them. Their North Star metrics is a volume metric (eg GPV). Databricks’ core product is a pipes product.

Companies can have both types of products in their portfolio. For example, ChatGPT is a dashboard product while OpenAI’s APIs are a pipes product. However, a given product has to determine which camp it’s primarily in.

This choice dictates product development, growth strategy, and org structure. For example, dashboard products require heavy investment in UI/UX polish, engagement features, and retention loops, while pipes products prioritize reliability, throughput, integration breadth, and seamless embedding into customer workflows. Dashboard products have consumer-style growth teams focused on activation and habit formation to grow [DWM]AUs, while pipes products focus on making their product invisible infrastructure that “just works” and on capturing more and more of their end customers’ volume.

Most teams fail by mixing the two too early — chasing DAUs while selling pipes, or overbuilding infra for a dashboard.

Clarity on where value accrues should come before features, metrics, or hiring.