TestSprite

Developers and AI coding agents ship code faster than they can verify it, and writing end to end tests is the chore that always loses to the next feature. TestSprite cites a published benchmark of two to four hours per end to end test, meaning sixty tests cost three to six weeks, so most teams never write the suite that would catch a regression. Because of this, a closed ticket, a green unit suite, or an agent's confident 'done' summary gets treated as proof a feature works even though nothing actually drove the running app. TestSprite's own public testing at CoderCup found that a single AI-assisted change broke 12 to 25 percent of previously working features, with nothing in a standard pipeline watching for it. The result is that the first person to discover a break is often a user in production.

TestSprite installs via a CLI, an MCP server in the editor, or a pasted staging URL, then explores the app and reads the code and PRD to learn how it actually behaves, using that as the test spec instead of hand-written scripts. It runs dozens of agents in parallel in the cloud against the real running app or a live API, producing 50 to 100 end to end tests from a URL in about ten minutes and replaying any session as video evidence. When a test fails, it returns one bundle containing the failing step, screenshots, DOM snapshots, test source, a root-cause hypothesis and a suggested fix, and an Auto-Heal feature repairs tests when the UI drifts. Every passing test is kept and rerun on every change so coverage compounds, and the suite can be scheduled nightly or gated on every pull request, with results posted directly to the PR.

Coding agents have made writing code fast, but verification has not kept pace, so the code shipping fastest is exactly the code nothing is checking.