Starts a fresh Codex worker and critic every cycle
Unlike long-running agent chats, AgentLoop starts a fresh Codex worker and critic every cycle. Set the goal and GUIDELINES.md rubric once; workers build, critics test, and failures become concrete fix notes for the next clean context. Project files carry the memory. Runs stay local, sandboxed, observable, and cancellable from a live dashboard, with ChatGPT control through MCP. Polish mode can continue beyond PASS until the critic says SHIP. Open source and zero-dependency Node.js.
Hey Product Hunt, I’m Edward, the solo developer behind AgentLoop.
I built it because I kept becoming the relay between ChatGPT and Codex: plan, paste, inspect, return feedback, repeat. Quality slipped as soon as I stopped watching.
AgentLoop automates that relay without hiding the work. Set a goal and GUIDELINES.md rubric once. Each cycle starts a fresh Codex worker, then a fresh critic tests the result against your rubric and writes concrete fix notes for the next worker. Project files carry memory between clean contexts, and a local dashboard makes every cycle watchable and cancellable.
The moment the idea proved itself was an evaluation with no forced failure. The first worker produced nine passing tests, but the fresh critic still found a real mixed percent-decoding defect. The next worker fixed it, added regression coverage, passed 11 tests, and earned PASS.
I designed and built AgentLoop during OpenAI Build Week using Codex CLI and GPT-5.6. It is open source and zero-dependency Node.js.
What coding task would you trust an observable loop to handle while you step away?
About AgentLoop on Product Hunt
“Starts a fresh Codex worker and critic every cycle”
AgentLoop launched on Product Hunt on July 23rd, 2026 and earned 94 upvotes and 8 comments, placing #18 on the daily leaderboard. Unlike long-running agent chats, AgentLoop starts a fresh Codex worker and critic every cycle. Set the goal and GUIDELINES.md rubric once; workers build, critics test, and failures become concrete fix notes for the next clean context. Project files carry the memory. Runs stay local, sandboxed, observable, and cancellable from a live dashboard, with ChatGPT control through MCP. Polish mode can continue beyond PASS until the critic says SHIP. Open source and zero-dependency Node.js.
On the analytics side, AgentLoop competes within Open Source, Developer Tools, Artificial Intelligence, GitHub and OpenAI Day — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how AgentLoop performed against the three products that launched closest to it on the same day.
Who hunted AgentLoop?
AgentLoop was hunted by Edward Yi. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of AgentLoop including community comment highlights and product details, visit the product overview.
Edward Yi