Situation

Code review cannot keep up

Pull requests arrive faster than anyone can read them. Approvals become a formality. The checklist moves the load from reading every line to verifying every release.

Termsverdict (a one-word release result (pass, pass with findings, fail) with the findings and the checklist version behind it) · two-user test (sign in as one user, create a row, then try to read or change it as another user; pass is nothing comes back) · webhook (a message a provider such as Stripe sends to your server when something happens, like a payment) · fault injection (making a dependency fail on purpose in staging to see what the user and the logs show) · CI (the pipeline that builds and tests every change before it can be merged or deployed) · protected branch (the git branch that cannot be pushed to directly and is the only source of production deploys) · migration (a scripted change to the database schema that ships with a release and should be reversible) · store sandbox (Apple's and Google's test environments where purchases run without real money) · LLM feature (a product feature that calls a large language model, such as an assistant or a summariser)

The situation

When a team writes with AI, the volume of code per week grows faster than the number of reviewers. Review then skims, and the things review used to catch (a missing auth check, a dropped error) ship. A release gate with pass criteria checks outcomes instead of lines: it does not matter how the code was written if the two-user test returns zero rows.

What to do this week

An ordered sequence from the checklist. Each item links to its pass criterion.

Day 1
Automate the three items that need no judgement and put them in CI as blocking checks. Review no longer has to look for them.
- SC-01No secret keys in client bundlescritical
- SC-02No secrets in repository historycritical
- AC-01Every table exposed to the client has row-level security enabledcritical
Day 2
Add direct calls to every action and admin route to the suite. This is the check skimmed review misses most.
- AU-02Server actions and API mutations re-check authentication and authorizationcritical
- AC-04Admin functions are verified on the servercritical
Day 3
Fault-inject the critical flows; then make 'has a failure branch and a timeout' a review prompt rather than a hope.
- EH-01Failures surface to the user and to logshigh
- EH-04External calls have timeouts and bounded retriesmedium
Day 4
Run the webhook negative cases. Payment handlers are the most-copied and least-reviewed code.
- PY-01Webhook signatures are verified against the raw bodycritical
- PY-02Duplicate and out-of-order events are handled oncehigh
Day 5
Record the release with its checklist version and verdict. Review can be light when the release gate is not.
- DR-05Release notes carry the checklist version and verdictlow

Which plan

Growth $5,900/mo

Growth: daily releases, up to 10 a week, an API, and the LLM items. The automated suite grows to 80 flows by month 2 and takes the outcome checks off the reviewers.

Limits, inclusions and what is not included.

Email about Growth

What happens without it

In a sample of 470 open-source pull requests, AI-co-authored ones had error-handling gaps nearly twice as often and logic issues 75% more often than human-only ones. Review that skims will not catch those; a fault-injection item (EH-01) and a two-user test (AC-02) will, whoever wrote the code.

In the same 470-pull-request sample, cross-site scripting issues were up to 2.74 times more frequent in AI-co-authored pull requests; error-handling gaps were nearly 2 times more common and logic and correctness issues 75% more common.

Source: CodeRabbit, 2025-12-17 · verified 2026-09-21

Questions

Code review backlog too many pull requests

Move outcome checks out of review and into the release gate: secrets scan, RLS flag query, direct calls to actions, webhook negative cases, fault injection. Reviewers then read for intent and design. Growth runs the gate on up to 10 releases a week.

Managed QA vs test automation tool

A tool runs the tests you write. The service decides what to test from a published checklist, writes and maintains the suite in your repository, runs the manual items a person has to run, and signs a verdict per release. Tools we use are named on the how it works page.

How to test AI generated code?

Check outcomes against pass criteria rather than reading every line: the checklist has 53 of them. The catalogue tells you which failures to expect more often and why.

Start with the audit

5 business days, $1,200, credited to the first month.

Start with the audit Read the checklist

Other situations