Customer eyes for your coding agent.

Good Catch opens the change in a fresh browser, pursues your customer’s goal, and reports only what it can show you.

Good Catch Reviews for Fernly, an online plant shop, listing checkout, delivery, and gift reviews with their outcomes. — See what was reviewed, what was found, and what needs another look. View full size

Works with your agent
Your agent runs it automatically, alongside tests and typechecks.
Beyond passing tests
Find confusing journeys and silent failures that functional checks miss.
Evidence with every finding
See what happened, follow the steps, and decide what to fix.

How Good Catch compares

AI QA agents check the flows you describe. Good Catch looks for what nobody described. Use it alongside them.

What Good Catch and AI QA agents are built to do.
Comparison	Good Catch	AI QA agents
Uses your product in a real browser
Browser evidence with every result
Finds problems nobody wrote a test for
Says whether the user reached their goal
Called by your coding agent before it says done
Reruns your known flows on every PR
Mobile apps

Core capabilityDepends on the toolNot its focus

See how Good Catch reviews your product.

Each chapter is one part of a review visit, from first context to a shortlist you can judge.

Product understanding Learns your product. Finds the journeys that matter.

Explores your features automatically
Maps real customer journeys
No test plans to write

Restore an archived projectLearned

Download last month’s invoiceRegression

Promote a member to adminLearned

Create a project from a templateLearned

Replace an expired payment card!Issue found

Invite a contractor as a guestLearning

Duplicate a reusable checklistLearning

Experience reviews Finds what gets in your customers’ way.

Real goals in a real browser
Broken flows and design inconsistencies
Evidence with every finding

Automated reviews Runs with every change. Right alongside your tests.

Triggered by your agent or CI
Reviews your latest build
Findings returned to your workflow

Codex

Cursor

Claude

Fix verification Checks the fix. Proves the journey works.

Replays the original failing journey
Checks the outcome in your latest build
Before-and-after browser evidence

Questions.

Learn how Good Catch works and what to expect.

How is this different from automated testing?

Tests check outcomes your team already specified. Good Catch explores the rendered product like a customer and looks for the rough edges nobody turned into a test.

What does Good Catch actually find?

Where does it run?

How much setup does it take?

What leaves my machine?

Screenshots and page text from the review go to Good Catch, which asks an AI model to judge them through OpenRouter and OpenAI. Good Catch keeps a fingerprint, usage, and cost for each request, not the screenshots. Your source code is not sent. The full review report stays on your machine unless you choose to share it. Customer-grade data controls are not built yet, so use test accounts and test data during the beta.

How does it fit the workflow?

Are the findings worth fixing?

Is it safe to use on our product?

How does the closed beta work?

What does the closed beta cost?

Catch it before your customers have to.

Good Catch is in closed beta. We are letting teams in a few at a time.

“The hardest part is noise. An agent will happily report ten plausible problems, and if eight of them are wrong, you stop reading by day two. Getting that ratio right matters more than anything else I’m working on.”

Waldemar PaninFounder, Good CatchRead the full post