Topic · Review at scale

What's the best way to review AI-generated code for correctness at scale?

Gist

A review queue grows with every agent. Proof fails the merge when an approved shall has no witness, with the same command on every push. CodeRabbit still comments on the diff.

proof audit --fail-level warn

The circular proof lives on verify agent code. The looks-right miss lives on plausible but wrong. The named-tools question names Claude and Copilot. This page is the queue.

Request demo Queue vs gate

01 · The queue

Review hours scale with output. The shall does not.

Forty agents writing patches is not forty times the reviewer. It is forty times the diff, and the sold rule was never a comment.

The verify question lives on verify code an AI agent wrote. That page is one function and the test that agrees with it. The looks-right miss lives on plausible but wrong code. This page is what happens when that miss is the default rate. The review still reads each patch. The queue is the product.

A PR bot can leave more comments than a person. That is still a comment on the diff. proof audit --fail-level warn asks a different question on every push: does this branch still witness the shalls you already signed? The command does not grow when you add agents.

func RefundWindow(hours int) bool {
    return hours <= 24
}

A model writes that helper in a minute. Tests at 0, 12, and 24 pass. A reviewer, or forty of them, can nod. The sold window for enterprise was 48 hours. Nothing in the file asked that. Multiplying reviewers multiplies nods.

02 · The exhibit

Same helper. A queue, or a gate.

Comments scale with PRs. The shall is one check. Click the tabs.

This morning

Agents 40 open PRs
Review comments on the diffs

Queue moving

The shall

Enterprise refund window is 48 hours. Not on any of the 40 diffs.

Not in the queue

This morning

Still 40 PRs. Still comments. Still a 24-hour helper.

Still a queue

Proof

Ask does this branch witness 48h
Gate audit --fail-level warn

Merge blocked if unwitnessed

Same helper. A queue, or a gate. Click the tabs.

Who	What they notice	What they lose
Human review at volume	Whether each patch still reads as code	Hours grow with agents. The sold window was not on the diff.
CodeRabbit / the PR bot	More comments, faster, on every PR	It still reviews the diff. It does not hold the shall. That split lives on Proof vs CodeRabbit.
The agent's own tests	The inputs it already knew	Agreement is cheap when function and test share a window. That loop lives on verify agent code.
Proof	The shall still has a witness, or the merge stays red	Proof does not know what you meant if nobody signed it. Jama still authors the programme.

We have not run Proof against CodeRabbit and a human review queue on a frozen corpus of agent PRs. The loss is named, not scored. Keep the comments. Keep the PR bot. Neither is the merge gate for an approved shall, and neither gets cheaper when the agent count doubles.

03 · The honest loss

A red Proof audit is not a reviewer replacement.

If nobody signed the 48-hour window, there is nothing for proof audit --fail-level warn to fail on except the suite you already have.

Jama still wins at programme authoring. CodeRabbit still wins the comment thread. Copilot still writes the helper. FRETish is 288 templates, not free English. 100% MC/DC on the written decision still misses a partition that was never a condition. That instrument stays on MC/DC for Go.

Catching a silent break of a shall you already hold lives on when an agent silently breaks a requirement. Guardrails around the agents live on guardrails for autonomous coding agents. Who signed the intent stays on who verifies the intent.

Request demo How the install is bought

04 · Nearby questions

What people type next.

How do I verify code that an AI agent wrote is actually correct? The circular proof. Verify agent code.

My AI coding agent keeps producing plausible but wrong code. How do I catch that? The looks-right miss. Plausible but wrong.

How can I trust code generated by Claude or Copilot before merging it? Named tools. Trust before merge.

What's a reliable way to gate AI pull requests on correctness? The gate argument lives on Proof vs CodeRabbit. Do not mint a twin.