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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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690,326 просмотров • 2 месяцев назад •via X (Twitter)

Образование Наука и технологии

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LeetCode is dead. Developers don't write code line-by-line anymore. They orchestrate AI agents working in parallel, review AI-generated code, and make architectural decisions. That's the job now. But most interview processes haven't caught up. They still test algorithm memorization instead of AI fluency, code review, and judgment. We're building assessments for next-gen hiring that mirror how developers actually work. Here's how we think about it:

LeetCode is dead. Developers don't write code line-by-line anymore. They orchestrate AI agents working in parallel, review AI-generated code, and make architectural decisions. That's the job now. But most interview processes haven't caught up. They still test algorithm memorization instead of AI fluency, code review, and judgment. We're building assessments for next-gen hiring that mirror how developers actually work. Here's how we think about it:

HackerRank

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Today, teams ship AI-generated code faster than they can verify it. AI will write most of the world's code, Momentic will make sure it works. We've raised a $15M Series A led by Standard Capital to build the definitive source of truth for software.

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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"

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.

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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Google Antigravity

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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?

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?

Kevin O'Leary aka Mr. Wonderful

24,193 просмотров • 10 месяцев назад

Andrej Karpathy's advice for beginners getting into AI: "Put in 10,000 hours of work." He's right. But most builders waste the first 1,000 hours on the wrong things. They write code before understanding context windows. They build agents before understanding token limits. They ship products before understanding what models can't do. The builders who compound fastest aren't the ones who code the most. They're the ones who understood the fundamentals before touching a single line. These are the 10 concepts that make the first 1,000 hours count ↓ Bookmark this before you start.

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🚨 Jeffrey Epstein says the best traders act on intuition they don't fully understand "If you talk to really experienced and successful traders and you ask them how they know what's going on, they can't give you an answer. They don't know. They feel it. They can feel the way the market's moving. They can feel the way the stock's moving. And that these are not very well-defined terms. Great traders feel it and then act on their feelings. That's the difference. Many people feel it but are afraid because they want a mathematical justification before they take that next step."

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