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The best programmers don't write code anymore. They write a spec. A test. An eval. T Then they turn the AI on and walk away for hours. It runs. It ships. They review. Evals are the unlock most devs are sleeping on. Here's how top agent teams build them right.

Rohit

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Former CEO of Google, Eric Schmidt: "traditional programming is over, and i'm mourning the identity i built around it" Programmers don't write code anymore — they wake up, assign objectives to AI agents, go to lunch, and let them run overnight For anyone still coding the old way: "stop. it's over"

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they don't write silly toxic ships anymore these days :(

they don't write silly toxic ships anymore these days :(

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I don't think most PMs realize the PRD is becoming obsolete. For the last decade, the PM's core artifact was a qualitative spec. Clear requirements, user stories, acceptance criteria. The engineering team interpreted it, built something close, and the PM spent two weeks reconciling what shipped with what they wrote. The best AI companies replaced that entire loop with evals. A set of inputs your product needs to handle. A task that generates outputs. A scoring function that produces a number between 0 and 1. No ambiguity. No interpretation gap. Ankur Goyal built the eval platform behind Vercel, Replit, Ramp, Notion, and Airtable. An $800M company. He walked through building an eval from zero on this episode and the score went from 0 to 0.75 in under 20 minutes. That's a PM shipping a measurable quality bar before a single line of product code exists. Here's the part that changes the PM role permanently. When the product passes the eval and users still hate it, the eval is wrong. That's on the PM. Evals make PM judgment quantifiable in a way PRDs never did. You can't hide behind "the spec was ambiguous." There's a number now. Six months ago, PM interviews asked "how do you use AI in your workflow." The next wave of interviews is going to ask you to write an eval. The PMs who can encode user intent as a scoring function are building the one skill that survives every model change, every framework swap, every agent rewrite. Write the eval.

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Don't let AI write code blindly. In Antigravity, request an "Implementation Plan" artifact first. Review the architecture, edit the markdown logic, and then approve execution. Control the outcome, don't just hope for it.

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We are in a technological war with China, we really are. There are three countries that spend the most on AI. Number one is the US, number two is China, number three is the UAE. The UAE is friendly to the US, they work on American chips, they work with Nvidia. And so if we didn't give them chips and we starved them from technology, they would simply buy them from Huawei. The problem with that is that the chip is the queen bee. You set a chip out into the ecosphere, all the honeybees gather around it, they're the programmers, and they make the honey, they write the code, they create the value of the hive. Every time the queen bee's DNA is upgraded, all the other bees know how to write that code and make that honey. Do we want American honey out there or do we want Chinese honey?

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BREAKING: Replit just launched mobile apps. Now you can build in Replit ⠕ and submit straight to the App Store for review. Describe your app → build it on Replit → test on your phone → publish to the App Store. I built a unicorn pet app for my niece: - Worked with Replit Agent to build it out - Scanned a QR code to download and test on my phone - One click to send to App Store Connect for review - A couple submissions later, it's live in the App Store! 🙌 I didn't write a single line of code! Just described what I wanted to Agent. Amazing! 😅 Go build something!! 👇

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