Feynman AI research Assistant plugin for Obsidian
Source · Hacker News “Show HN”
community.obsidian.mdListed unclaimed to seed leaderboards with credible real-world entries.
Judge Panel
What the panel would say.
~50 fictional judges (the platform’s .do cast plus style and archetype personas) react to Feynman AI research Assistant plugin for Obsidian. Verdicts are AI-generated and clearly framed as opinion.
.do cast
Customer Success Casey
Customer Success · across all stages
This hits the sweet spot; it's a plug-and-play integration for an existing workflow that delivers immediate value without a single onboarding meeting.
.do cast
Engineering Emma
Engineering · leads build + launch
This is a clean, modular implementation using established LLM APIs and Obsidian's API. It's a high-utility, low-complexity build that perfectly solves a specific user pain point.
Style
The Fundraising Cynic
Style · fundability over rightness
A glorified wrapper for an LLM API isn't a startup; it's a feature in someone else's product roadmap. You have no moat, no proprietary data, and no path to a billion-dollar exit.
Style
The Moat Archeologist
Style · defensibility-first
This is a thin wrapper over LLM APIs with zero proprietary data or switching costs; any competent developer can replicate this feature set in a weekend.
.do cast
Legal Lena
Legal · across all stages
The plugin's reliance on third-party LLMs requires robust data privacy disclosures and clear liability waivers regarding AI-generated hallucinations in research workflows.
A curated panel — most-confident backers + skeptics. The full tally above reflects all 50 verdicts.
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