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Agent Rigor
Stop AI doom-loops. Add discipline to coding agents.
Most AI agents fail because they lack discipline. They skip planning, write plausible but broken code, and get trapped in endless fix-forward "doom loops." Agent Rigor is an open-source framework that fixes this. Compatible with any coding assistant, it forces agents through a strict 6-phase loop - requiring empirical verification and tests before committing any code. Stop watching your AI coding assistant code itself into a corner and give it empirical discipline.
Hey Product Hunt! I'm the builder behind Agent Rigor.
Like many of you, I've been incredibly frustrated watching state-of-the-art AI coding agents get trapped in "doom loops." They write plausible-looking code, fail a test, and then spiral into endless hallucinated fixes that just break the codebase further. They have the intelligence, but they lack discipline.
Agent Rigor is the solution to this problem. It is a self-sufficient, open-source operating system designed to force strict empirical discipline on your AI agents.
Here’s how it works:
🛡️ Anti-Rationalization: It actively prevents agents from saying "this looks right" without running tests.
🧠 Progressive Disclosure: Instead of overwhelming the context window, it only loads instructions JIT (Just-In-Time) for the current phase.
🔄 6-Phase Loop: It orchestrates planning, execution, verification, and context-saving, moving the codebase strictly between known-good states.
It's completely platform-agnostic—whether you use Cursor, GitHub Copilot, or CLI tools like Claude Code, it plugs right in using markdown instructions.
I built this to save my own sanity, and I hope it saves yours too. I'd love to hear your feedback, answer your questions, and hear what you think of the architecture!
About Agent Rigor on Product Hunt
“Stop AI doom-loops. Add discipline to coding agents.”
Agent Rigor was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #140 on the daily leaderboard. Most AI agents fail because they lack discipline. They skip planning, write plausible but broken code, and get trapped in endless fix-forward "doom loops." Agent Rigor is an open-source framework that fixes this. Compatible with any coding assistant, it forces agents through a strict 6-phase loop - requiring empirical verification and tests before committing any code. Stop watching your AI coding assistant code itself into a corner and give it empirical discipline.
On the analytics side, Agent Rigor competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Agent Rigor performed against the three products that launched closest to it on the same day.
Who hunted Agent Rigor?
Agent Rigor was hunted by Meher Bhaskar. 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 Agent Rigor including community comment highlights and product details, visit the product overview.
Meher Bhaskar