Tests that get written
whether anyone has time or not
New code ships faster than tests get written for it, so coverage quietly drops every sprint and nobody notices until a regression does the noticing for them. We build an agent that drafts the tests for every new function and edge case the moment the code lands, and leaves the final review to your engineers.
The process today
Engineering teams commonly report that test coverage drifts downward whenever a sprint runs tight, because writing the test is the step that gets cut first when a feature has to ship. Industry surveys on technical debt regularly put “insufficient test coverage” among the top three reasons a team slows down months later, and the gap compounds: a function ships untested, three more functions build on top of it, and by the time someone notices, writing the missing tests costs far more than it would have on day one.
The actual writing is also the part developers avoid even when they have time. A typical range for “test code relative to feature code” that teams aim for is close to 1:1, but the honest reporting from most mid-size teams is well below that, because a unit test for the happy path is easy and a test for the three edge cases that actually break production takes real thought that gets skipped under deadline pressure. The result is a test suite that looks healthy on a coverage dashboard but misses exactly the cases that cause incidents.
What the agent does
Reads the diff the moment a pull request opens, including the function signatures, the types, and any linked ticket describing the intended behavior, so the tests it drafts match what the code is supposed to do, not just what it currently does.
Drafts unit tests for every new or changed function, written in your existing framework (Jest, Pytest, PHPUnit, Go test) and matching your team’s naming and fixture conventions rather than a generic template.
Writes integration tests for new API endpoints and data flows, covering the request and response shape, auth requirements, and the database or queue interactions a unit test alone would not catch.
Generates edge-case and failure-path tests, like malformed input, empty collections, timeouts and concurrent writes, the cases a tired developer skips first when time is short.
Attaches a coverage report to the pull request showing exactly which new lines and branches are covered, so a reviewer sees the gap in seconds instead of running coverage locally.
Flags flaky tests before merge, running the new suite multiple times in CI and holding any test with inconsistent results for a human to fix rather than letting it into the main branch.
What stays with humans
The agent drafts tests, it does not decide what correct behavior is. Any test that implies a product or business-logic decision, anything that needs a real production-like database, a paid third-party API, or a sensitive fixture (real customer data, real payment credentials) is held for a person to set up or approve first. Engineers review and merge the drafted tests like any other pull request; the agent never commits directly to a protected branch.
Guards
A dry-run period where the agent opens its own branch with draft tests instead of pushing into a developer’s pull request, so your team can check its judgment against real code before it is in anyone’s way. Every generated test logs which function or ticket it was drafted against. Rate limits cap how many tests the agent drafts per hour so a large refactor does not flood CI. A kill switch pulls it off any repo instantly, and tests touching real data stores or paid APIs sit in an approval queue until a human clears them.
Price and timeline
| Package | Price | Best for |
|---|---|---|
| Single automation | from $700 | One repo, drafting unit and integration tests into pull requests automatically |
| Department package | from $2,500 | Test generation plus code review, release notes and log triage for the same codebase |
3 to 8 days for the first repo, most of it spent matching your existing test framework and fixtures so the first drafted tests already look like the ones your team writes.
Related
Works best alongside code review, since a reviewed diff and a drafted test suite close the same loop, and feeds release notes with a record of what got new coverage. Teams running log triage and alerting usually add test generation next to catch issues before they reach production logs. Part of automation of everything digital and built the way we build AI agents for our own products. Two of our own projects shipped under this kind of test discipline: the Telegram game club with 428 automated tests and the fitness app with AI coach and gamification.
Tell us which repo and framework you want covered first and we will send back a fixed price and a plan for the first week: get in touch.
Tired of doing this by hand? We can take the whole routine off your team, not just this step: Routine takeover, from $400 →
FAQ
How much does an AI test generation agent cost?
A single-repo agent wired into your existing test framework starts from $700. A department package covering test generation alongside code review, release notes and log triage starts from $2,500, with the exact price depending on language count and framework.
How long does it take to go live?
3 to 8 days: connecting to your repo and CI, matching your existing test style and fixtures, and a short period where the agent drafts tests into a branch for review rather than committing them directly.
Which tools does it connect to?
GitHub, GitLab and Bitbucket for pull requests, your existing test runners (Jest, Pytest, PHPUnit, Go test and similar), your CI pipeline for running the drafted suite, and Claude for reasoning about edge cases a template-based generator would miss.
What if the agent writes a bad test?
It drafts into a branch or a labeled pull request, never commits straight to main, and every test it writes is readable and named for what it checks so a reviewer can fix or delete it in seconds. We tune against your own codebase's patterns before launch.
Is our codebase safe?
The agent only reads the repositories you connect, runs under your git provider's own permissions, and does not retain your code outside the generation session. Any test that would touch a real database or a paid API is flagged and held for a human to approve first.