Hey Product Hunt,

I build with AI coding tools every day. They are great at getting to a draft fast: code, migrations, auth flows, architecture ideas, technical fixes.

But the expensive part usually comes later. What did the model actually check? Which files did it use? Which assumptions were hidden? What could not be proven? Is this safe enough to put into a real PR?

The hard question is no longer just: “Can AI write code?”

It is: “How far can I trust the engineering work AI just produced?”

Ündes is my answer to that problem.

It proposes an engineering solution or code candidate and, in the same run, produces a reviewable artifact: evidence used, files checked, critique, rejected hypotheses, unresolved assumptions, open production/PR risks, and a trust verdict such as safe to apply, needs review, or insufficient evidence.

It uses a multi-agent review process under the hood: propose, critique, consensus, devil’s advocate, and synthesis.

But the multi-agent workflow is the engine, not the point.

The point is to make AI-generated engineering work inspectable before you merge it, deploy it, or base an architecture decision on it.

Ündes does not replace engineering judgment and does not promise that generated code is automatically correct.

Sometimes the most useful answer is: “I could not prove this. Here is exactly what still needs to be checked.”

That is intentional. I would rather have an AI tool expose uncertainty than hand me a confident, unverified patch.

AI can generate the code. Ündes shows how far you can trust it.

I would appreciate feedback from engineers, tech leads, founders, and anyone already shipping with AI coding tools.

What would you need to see before trusting AI-generated engineering work in a real PR or architecture decision?