2026-11-13 08:00:00
Disclaimer: I am not saying Jensen did nothing. The affairs are real. What I want to write about is how the crowd reacted, because I think René Girard explains this week better than any of the hot takes on Twitter.
A quick Girard primer:
Now apply this to the AI trade, which might be the most mimetic market we have ever had. Every hyperscaler buys GPUs because the other hyperscalers are buying GPUs, and every fund owns AI stocks because every other fund does. Sequoia pushed out Roelof Botha because the firm felt it had missed the AI wave. That’s how much pressure there is to want what everyone else wants. And for two years we’ve all been worried about a bubble. That is a Girardian crisis: a lot of built-up tension and nowhere for it to go.
The next step is finding the scapegoat.
Girard noticed that scapegoats usually come from the edges of a community, either the outsider or the king. The king makes the classic victim because he sits above everyone and is completely alone up there. In the AI economy that was Jensen, with the leather jacket, center stage at every keynote, and the kind of welcome usually reserved for heads of state. But to a lot of people he is also an outsider, an Asian American who could easily be painted as someone having an affair with a Chinese spy.
That last part matters, because the accusations fit what Girard called the ‘stereotypes of persecution’. He kept finding the same pair in medieval persecution texts and in old myths: sexual transgression, which breaks the order of the community, and contamination from a foreign enemy. Here you get an affair and an alleged spy. Accusations like these feel bigger than one person, as if the whole group is under threat. It also helped that plenty of people in power disagreed with Jensen on open source and on trading with China, and they were not going to waste the moment.
The board, the press, the market and Twitter all landed in the same place at the same time, and you could watch the noise build across every mainstream publication. The reaction was wildly out of proportion to what actually happened, which is what you’d expect if the crowd was really dumping two years of bubble anxiety onto the one person everyone could see. In 2025 everyone wanted to be Jensen. Now people want him gone.
So what comes next? If Girard is right, sacralization. Steve Jobs was pushed out of Apple in 1985 and came back a god, and my guess is Jensen’s story turns into myth whatever happens: the man who built AI and the man who might nearly broke it. Peter Thiel, who studied under Girard at Stanford, argues that founders are modern sacred kings, worshipped and then sacrificed, sometimes by the same crowd. We have never watched it play out this clearly in a single week.
2026-11-11 08:00:00
We’re all gamblers in this economy.
Gambling (n.): Staking something of value in the hope of gain.
The guy in his basement betting on a sportsbook. (Sorry, making a prognosis on what is going to happen.) The guy drawing triangles on TradingView. (Technical analysis.) The banker asking Claude for his 10th DCF analysis of the week. (Running scenarios.) The dev on his third Codex subscription this month. (Hoping Papa Sam doesn’t raise token prices again this year.) The designer generating variations on his infinite canvas with Emil’s UI design skill. (Exploring the design space.) The video editor on Higgsfield generating AI slop. (Who may never be able to cancel his subscription later on.) The Microsoft HR lady drafting layoffs. (With a 20% chance she’s on the next one.)
We’re all pulling the slot machine lever.
The only difference is whether you’re aware of it or not.
2026-05-07 08:00:00
My front-end development process for a new product:
Proven Execution is the baseline. Everything here should be treated as non-negotiable.
1.1 Coverage: All required screens, flows, and components should exist. First the designer creates them, then the front-end dev executes according to design. Considering most developers are one-shotting the first cut, I am less focused on pixel perfect design at this stage, but making sure all the components and flows exist. You can think of this stage as getting the static components in code.
1.2 Functionality: All components should work as expected. This means integrating with the backend API. Making sure the happy flow works. Buttons, inputs, filters, tabs, trading actions, navigation, and state changes should behave correctly. The product should not just look clickable. It should work.
1.3 Correctness: Now you make sure that if the UI matches the designs. Make it pixel perfect. This means layout, spacing, typography, colors, component sizing, visual hierarchy, responsiveness, and designer feedback.
1.4 All States, Edge Cases, and Errors: Every screen should handle real-world conditions. This includes loading, empty, error, success, disabled, pending, partial data, offline, and permission states. The product should behave well when things go wrong.
You can decide to pick 1.4 before 1.3 too.
1.5 Scalability: The front end should be built in a way that supports future versions. Components should be reusable. Layouts should handle more content.
We should not build the first version in a way that makes the second version harder.
With this we complete the first stage.
Product Feel: Once the known product works, we improve how it feels.
2.1 Performance: The product should feel fast. Screens should load quickly. Interactions should respond immediately. Scroll should be smooth.
2.2 Delight: Delight should support the product, not decorate it. Motion, transitions, hover states, confirmations, price movement cues, and micro-interactions should make the product feel clearer, faster, and more satisfying. If motion slows the user down or distracts from the action, cut it.
2.3 Information architecture and copy: The hierarchy should be clear. The copy should be simple. The actions should be obvious. The mobile experience should feel native. A normal consumer should understand what to do without being trained.
2.4 Brand and Product Refinement: Branding is not just the landing page. Once the design system, part of the branding exercise, is ready, it should make everything cohesive. This includes typography, font sizes, colors, spacing, icons, illustrations, motion, charts, copy, empty states, and product personality. I am keeping Brand and Product refinement for later because a lot of companies would not wait for branding before starting on the product development.
2.5 Gamification: Best products feel like games.
Second stage is complete.
User led invention and iteration: As you are closer to launch, you will learn a lot from alpha users.
3.1 UTs: Do usability testing. Watch where users get confused, where they drop off, what they click, what they ignore, what they misunderstand, and what they try to do that we did not design for. User feedback should improve the product. User behavior matters more than internal opinions.
3.2 Invent last, not first: Only now do we add genuinely new things. Solve what others have not solved.
Most teams have all of these things in their heads. What they get wrong is the order. They start with new (invention) because it’s exciting. They debate brand before the product works. They skip edge cases because users haven’t complained yet. They add motion while basic flows are broken.
First, we build the known product. Then we make it better. Then we invent.
Related read: Proven, better, new.
2026-05-06 08:00:00
For much of the 20th century, society was built around bell curves: Average job. Average company. Average return. Average salary. Average investor.
The middle was large because distribution was constrained. Geography constrained jobs. Shelf space constrained products. Regulation constrained market access. Broadcast limited which voices got heard. Capital constraints kept outcomes tighter.
The middle looked big and the extremes were hidden.
Now everything is becoming more power law. Power laws happen when distribution gets cheaper, markets get more liquid, and talent/capital can scale faster thanks to AI.
A handful of companies now capture most of the market cap. A handful of creators capture most of the attention. A handful of funds capture most of the returns. A handful of workers capture most of the income growth in AI-exposed fields.
This was already obvious in venture capital. One fund-returning company mattered more than the entire rest of the portfolio. Then it became obvious in public markets with the magnificent seven.
Now it is spreading into labor, media, trading, startups, creator businesses, and information markets.
2026-05-05 08:00:00
Mark Pincus, the guy who built Zynga, has this deceptively simple framework for product development. He calls it Proven, Better, New.
Every product should start with something proven, make one or two things meaningfully better, and add just a touch of something new. But most people do the opposite. They decide to be original everywhere.
Step one is starting with proven. Proven is the part of the product that users already understand without onboarding. A poker game that behaves like poker is proven. You don’t get extra points for changing those.
Step two is making something better. Better doesn’t need to be flashy. It just needs to matter. It has to be something where nine out of ten people say “yes, that’s better.” Cheaper counts. Faster counts. Fewer steps counts. More fun counts. When Pincus started Zynga Poker, most games made you download something before playing. Every extra click killed half the funnel. He removed the download. One obvious improvement. That one change made the product spread.
Only after that comes step three: new. New is fun. New is where your taste shows up. New is also where almost everything fails. Pincus solves this by assuming new will fail. He budgets for it. He limits new to maybe 20 percent of the product so that even if it flops, the 80 percent that is proven and better still stands. He made Zynga Poker social. Playing with real friends instead of random avatars was the new. It worked. But even if it hadn’t, you would still have had poker and you would still have had no download. The product would still have been useful.
Too many founders cling to new ideas out of ego. They want everything to be new because that feels more innovative. They don’t want to build something the feels like a cheap copycat.
Take Quibi. They tried to innovate on everything. Short-form video. Mobile-only. New content format. New viewing behavior. Nothing was proven. The whole thing collapsed.
There’s a second framework I like to pair with Proven, Better, New. It’s from Slava Akhmechet. He says every feature lives in one of three buckets: gamechanger, showstopper, distraction.
A gamechanger is the reason someone buys your product. A showstopper is something you must have so people don’t reject your product, but it won’t make them choose you. A distraction is everything else.
The pattern he’s seen is that good products have one to three true gamechangers, a bunch of showstoppers that keep you from losing, and almost no distractions.
The hard part in product development is not shipping more. It is telling the difference between something that makes people buy, something that just keeps you in the game, and something that only makes the team feel productive.
2026-05-02 08:00:00
I pay for Claude, ChatGPT, Gemini: all the pro models. I have all the AI vibe-coding workflows set up. I create random POCs all the time.
So when Lenny tweeted about CleanShot X recently, I could have tried to vibecode my own version.
Would it have worked 70% of the time? Probably. Could I have just created the 20% of features I need that would give me 80% of the value? Probably.
But would I make something as polished as CleanShot X? No. Would I fix the dozens of edge cases after the MVP? No. Would I maintain it? Definitely not.
So I just decided to pay the ~$30 for the license.
AI makes building cheaper.
But you still need to put in effort to develop software that has taste and polish. And of course maintain it.
If I take dozens of screenshots a day, it makes sense to pay for an app that does screenshots really well.
And when the world has infinite content and infinite software nowadays thanks to AI, discovery (word of mouth) becomes even more valuable. I know people who bought Tegus and Quartr Pro because of my tweets. I have done the same when people I respect recommend something. Especially from people with a high value-to-shill ratio.
P.S Get CleanShot X.