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AI agents are writing more code. How can developers ensure that code is correct? Microsoft Research’s Proof-Driven Development (PDD) Kit explores a more rigorous approach: it translates a developer’s intent into a formal specification, then uses formal verification to prove that generated code meets it. PDD Kit works with... show more

Microsoft Research

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63,315 次观看 • 2 天前 •via X (Twitter)

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Microsoft Research 的头像

Microsoft Research2 天前

Join @GitHubUniverse Oct 28–29 in SF or online. Explore AI, security, and open source with hands-on sessions, product updates, and devs from around the world.

Harry Nicholls 的头像

Harry Nicholls2 天前

I think this is the future of software development until we solve program synthesis. Love the idea of bringing formal methods in by default, and making proofs legible to those who aren’t experts will be challenging.

kevin joo 的头像

kevin joo1 天前

@VictorTaelin they are starting to catch on!

H.M Gowda 的头像

H.M Gowda1 天前

simply call PRD.

EDDY VU 的头像

EDDY VU1 天前

Bringing formal verification into the agent loop is huge, especially for catching subtle edge cases unit tests consistently miss.

Lachy 的头像

Lachy1 天前

if the ai drafts the formal spec and i approve it, what catches a spec that is valid but quietly weaker than what i meant?

AxleMode 的头像

AxleMode2 天前

The mutation check in the demo is the bit worth copying: show the deliberately broken versions failing beside the proof result.

Nur Hasan 的头像

Nur Hasan1 天前

How is it different from PRD?

安叫兽|Bird🕊️ 🔶 BNB 的头像

安叫兽|Bird🕊️ 🔶 BNB1 天前

先把意图写清楚这步挺关键，不然验证再严也可能证明错东西。

Humanity Labs 的头像

Humanity Labs1 天前

Formal verification is a strong answer for code. Business work needs its equivalent: explicit standards, logged decisions, exception routes, and a human outcome owner. “The agent completed it” is not the same as “the result is acceptable.”

NextSignal 的头像

NextSignal1 天前

形式化验证过去最大的阻力，是写规范的人力成本比写代码还高。这套工具真正的考题在上一层：证明能保证代码符合规范，但规范本身写错了、或者根本没覆盖真实需求，证明照样成立。所以最难自动化的不是验证，而是把「到底想要什么」说清楚——这一层最后还是得人来守。

Kim Noël ⚡ 📖 的头像

Kim Noël ⚡ 📖1 天前

@grok is this like Lauren tan 's pstack?

Diego Alejandro R 的头像

Diego Alejandro R1 天前

We need more and better tools to review written code by AI

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41,419 次观看 • 22 天前

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Creator of C++, Bjarne Stroustrup: AI-generated code isn't ready — it generates more bugs, more bloat, more security holes, and is nearly impossible to validate "senior developers are already retiring rather than deal with it" The problem is that even a small prompt change can shift the entire codebase in unpredictable ways

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1,752,400 次观看 • 5 个月前

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Moonsong Labs 🌙

21,532 次观看 • 1 年前

“In the last 4–5 months, we stopped typing code.” Cognition CEO Scott Wu says almost all coding at Cognition is really just done through prompts now: “The code that we check into GitHub, how much of it was typed by a human at this point? Almost none.” “Now it looks a lot more like: how do we optimize testing, review, and planning - not how do we make AI good at writing code based on the prompt you give. At this point, it’s frankly already done.”

“In the last 4–5 months, we stopped typing code.” Cognition CEO Scott Wu says almost all coding at Cognition is really just done through prompts now: “The code that we check into GitHub, how much of it was typed by a human at this point? Almost none.” “Now it looks a lot more like: how do we optimize testing, review, and planning - not how do we make AI good at writing code based on the prompt you give. At this point, it’s frankly already done.”

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30,438 次观看 • 8 个月前

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

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296,750 次观看 • 1 年前