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Introducing Vet: catch your coding agent’s mistakes Open source, fast, local. Zero telemetry Can review full PRs and it tells us when Claude/Codex/OpenCode lies about passing tests it never ran 👿 We use it daily and it saves tons of headache

586,252 次观看 • 7 个月前 •via X (Twitter)

20 条评论

Imbue 的头像
Imbue7 个月前

We built Vet because our coding agents would constantly implement a feature, hit a wall, and quietly stub things out with hardcoded data. The code looks fine and tests might pass, but it's not what we asked for. We run Vet in agent loops, drop it in CI, and invoke it from the CLI. Get the code:

Imbue 的头像
Imbue7 个月前

Vet catches logic errors, unhandled edge cases, silent failures, insecure code, scope drift, etc At Imbue, we believe open agents must win over closed platforms for humans to live freely in our AI future. Vet is one of many upcoming projects toward that end. Read more:

Kanjun 🐙 的头像
Kanjun 🐙7 个月前

Woohoo, proud of Andrew and the team for building and shipping this! It's sooooo useful

Boyuan (Nemo) Chen 的头像
Boyuan (Nemo) Chen7 个月前

Caught my agents hardcoding expected outputs just to get green checks, more times than I'd like to admit. Code review doesn't always catch it because the logic looks right. What's review latency on a full PR? If fast enough to run mid-agent-loop that changes the workflow completely.

Imbue 的头像
Imbue7 个月前

Review latency on a PR is generally less than a minute, but running Vet in the loop, as the agent works, will be able to catch hardcoded credential issues before any code can be seen by other people! We run Vet in the loop because of issues like this so it can ensure agent changes match requests.

Nikhil Kulkarni 的头像
Nikhil Kulkarni7 个月前

Had so much fun making this one and highlighting the work Andrew and the team put into this product!

Millan Philipose 的头像
Millan Philipose7 个月前

vet is carrying my entire workflow rn and half of you don't even know it exists yet. That's fine. More alpha for me. Seriously though if you're "in AI" and haven't touched vet you're cosplaying. Sorry not sorry.

Ming Yin 的头像
Ming Yin7 个月前

So excited about this! And really cool graphics!!

Danver Braganza 的头像
Danver Braganza7 个月前

I've been using Vet as a final pass code review, and despite a solid pipeline of linting, tests, ratchets and agent directives it still regular catches issues with agent generated code. It's indispensable.

danwonn 的头像
danwonn7 个月前

Vet it and forget it — don’t wait till it’s too late! 🤷🏻‍♂️

Daniel Mewes 🦋 @dmewes com 的头像
Daniel Mewes 🦋 @dmewes com7 个月前

It's evolution-powered code review in your agent loop!

Ehsan Nour 的头像
Ehsan Nour7 个月前

so hyped!

Ashley Slocum 的头像
Ashley Slocum7 个月前

Great work all around 👏

Lauren Dash 的头像
Lauren Dash7 个月前

This video rules @nikhilville

Samuel Eisenhandler 的头像
Samuel Eisenhandler7 个月前

gaslight detection in an easy to install and use form factor!

Stella Wang 的头像
Stella Wang7 个月前

@nikhilville is COOKING

Kyriakos 的头像
Kyriakos7 个月前

Verify everything feels like the new rule in AI workflows

Yusuf Aktan 的头像
Yusuf Aktan7 个月前

Game changer for coders, ensuring accuracy 🚀

Capax Dei 的头像
Capax Dei7 个月前

This is the missing layer. Most frameworks let the LLM claim "tests pass" without independent verification. Vet moves the check from probabilistic to deterministic — the model says it works, the tool verifies independently. That boundary is what matters.

Aaron Edell 的头像
Aaron Edell3 个月前

I keep a regression log beside the code for this reason. Tests catch known failures. The log preserves the weird ways an agent previously declared victory while missing the actual request.

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