Long Horizon
Your coding agent writes the feature and runs the tests
Long Horizon launched on May 12, 2026 with 71 votes, #567 of 20,538 launches that month and more than 95% of that year's launches.
What it does
Your coding agent writes the feature — let it test it too. Long Horizon runs real browser tests and produces shareable execution reports with logs, screenshots, and network detail for confident feature delivery.
Automatically plan and run frontend tests in a real browser, discover issues, and fix them—with complete execution logs for review. Signed-in user completes purchase; confirmation renders with order id. The agent drafts the plan, writes the tests, and runs them in the browser. From your feature and repo context, the agent drafts what to test — core paths, edge cases, and failures. Signed-in user with items in cart completes purchase with a saved card; order confirmation renders. Checkout CTA stays disabled when the cart is empty; no network call to payment intent. Simulate card decline, surface inline error, allow user to change method and succeed. The agent writes tests in your project,…from longhorizon.dev
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Horizons – OSS agent execution engineFeb 2026 · github.com · ▲39I'm Josh, founder of Synth. We've been working on coding agent optimization with method like GEPA and MIPRO (the latter of which, I helped to originally develop), agent evaluation via methods like RLMs, and large scale deployment for training and inference. We've also worked on patterns for memory, processing live context, and managing agent actions, combining it all in a single stack called Horizons. With the release of OpenAI's Frontier and the consumer excitement around OpenClaw, we think the timing is right to release a v0. It integrates with our sdk for evaluation and optimization but…
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Continue – Source-controlled AI checks, enforceable in CIFeb 2026 · docs.continue.dev · ▲44We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
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