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Open-source protocol for AI agents doing longform industry research: brief gates, state files, source/claim discipline, staged drafting, review loops, hard stops, gotchas, and offline evals with regression fixtures.
Hi Product Hunt - I built Industry Research Framework because long AI research tasks fail in repeatable ways: agents start before scope is clear, mix facts with judgment, leak process notes, or declare victory after a thin draft.
This is a lightweight, open-source protocol for Codex, Claude, Gemini CLI, Cursor, OpenClaw, Hermes, and other agents. It gives the agent a brief gate, state files, source/claim/uncertainty registries, staged drafting, review loops, and hard stops for empty collection, evidence drift, false completion, depth collapse, and process leakage.
It also ships eval cases, a source pack, rubric, gotchas, taste anchors, and regression fixtures so changes can be checked. I would love feedback from people using agents for market maps, investment memos, competitive analysis, or research writing: where should the protocol be stricter, lighter, or easier to adopt?
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About Industry Research Framework on Product Hunt
“Source-backed research protocol for AI agents”
Industry Research Framework was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #15 on the daily leaderboard. Open-source protocol for AI agents doing longform industry research: brief gates, state files, source/claim discipline, staged drafting, review loops, hard stops, gotchas, and offline evals with regression fixtures.
Industry Research Framework was featured in Productivity (655.7k followers), Writing (59.3k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 286.4k products, making this a competitive space to launch in.
Who hunted Industry Research Framework?
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