"How many tokens did you burn?" is the new "How many hours did you work?" Both measure activity, not value. There are two kinds of AI leverage and they look identical on a contribution graph: Leverage through understanding — you know the domain, you know which tradeoffs matter, AI removes the friction between insight and implementation. Leverage through abstraction — you don't fully understand the system but you generate enough volume that things seem to work. Green tests, big PRs, impressive commit graphs. The tell is what happens at 3am when something breaks. One builder knows where to look. The other is staring at hundreds of thousands of lines they didn't write. The human work doesn't shrink. It concentrates. The decisions about what to build, why, what constrains it, and what will go wrong — that's the whole game now. AI made everything else cheap. It made that part more expensive. Whatever you don't inspect will break. That was always true. AI just raised the stakes.

“When execution is nearly free, taste becomes the moat but how a company organizes to make taste evident is still being decided.” Whether they’re called product managers in the future or not, this is precisely the role they should be playing in these companies. At some point you can’t have a complete roadmap free for all because your constraint isn’t token output it’s customer reception to your features.

Vibe coding builds demos. Specs builds products. Two development styles are emerging. One starts with prompts: - Open the AI tool - Describe the feature - Iterate until it works It’s fast. It feels magical. The other starts with a spec: - Define the system - Outline the architecture - Clarify product requirements Then let AI generate the code. Both move quickly at first. But as complexity grows, the difference shows. Because AI does one thing extremely well: - It amplifies whatever discipline already exists. With structure, it accelerates the build. Without structure, it accelerates chaos. AI didn’t remove the need for solid system architecture. It made it more important than ever.

Bullish on spec-driven development.

Something I keep coming back to: we gave code real infrastructure decades ago — version control, branching, merging. The thinking that shapes the code? Still scattered across Slack, markdown docs, and people's heads. Feels like a gap that only gets bigger as agents get faster. Agents are getting good enough that the wrong decision now propagates at machine speed. That's a different kind of problem than we've ever had.

I went through this exact thing about ~8 months ago. Everyone must pass through the phase of AI existential dread and developer ego death. After much internal deliberation I've come to the realization: The genie is out of the bottle, and instead of just three wishes, it comes with 𝗶𝗻𝗳𝗶𝗻𝗶𝘁𝘆 𝘄𝗶𝘀𝗵𝗲𝘀 😅 So, the focus changes from the artisanal line by line code crafting and shifts into deeper architectural & product decisions, that 𝗜 𝗱𝗿𝗶𝘃𝗲. It's now 99% product planning & research around edge cases/what's possible/competitors and like 1% typing syntax. Instead of the 75% code / ~25% planning of yesteryear. Once you see it, you see it.

Writing code by hand used to be where developers found clarity. While typing out every line, you naturally thought about the data flow, edge cases, naming, structure, props, etc. Bugs often got caught before the code even ran. Now, AI generates code at lightning speed. If your thinking isn’t clear, you will spend your day debugging AI hallucinations instead of solving actual problems. Clear intent is the bigger bottleneck now.

The best builders using AI spend MORE time on intent than they did before AI. The .md spec iteration — shaping what gets built, with the agent, before building — is the highest-leverage hour in the day. The thinking isn't overhead. It's the product. Code is just the output.

Causation in a Nutshell buff.ly/2mw5hAX

Important #longread from my colleague Michael Jordan with a measured academic look at AI hype and computational/statistical reality and opportunity around Data, ML, and yes, AI. medium.com/@mijordan3/artifi…

1997: World's best human chess player gets destroyed by computer. 2017: World's best chess computer gets destroyed by Artificial Intelligence program that had only learned about chess a few hours earlier. x.com/bramcohen/status/93842…

Don’t Tax Options And RSUs Upon Vesting! avc.com/2017/11/dont-tax-opt…

I'd rate this one star out of 10000000, at best.

Be eclipse smart -- eye damage can happen in seconds: qz.com/1057997/what-happens-…