FLF is running a competition to find the best workflows and methodologies for using AI to produce reliable, trustworthy knowledge bases, grounded in real-world cases. We’re open-minded on the types of submissions we receive and on how they address the problem. We’ve set aside approximately 200 thousand dollars for prizes. Winning submissions may receive a prize from 5 thousand dollars-50 thousand dollars and if submissions warrant, multiple 50 thousand dollars prizes are possible. Winners may be offered opportunities for further funded work.
You can express interest right away to receive commentary, information, and updates — whether you’d like to participate or are just interested in the outcomes of the competition.
The heights of human epistemic investigation are impressive and valuable, but rare and difficult to reach — see our abridged collection of strong examples.[1] The limiting factor is rarely exquisite insight (though this helps!), and more often diligence, a curious and open mindset, and the time and effort needed to do the thorough work investigating background on a topic: activities AI is well placed to assist with.
Existing AI-assisted knowledge base work demonstrates real pieces of this — agent memory (e.g., Claude Code's memory and skills), LLM-curated personal wikis [...]
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Outline:
(02:45) What we're looking for
(04:04) Ingestion
(04:47) Structure
(05:34) Assessment
(06:32) What a good entry looks like
(10:28) Please use this linked form to submit your entry; entries are due by Jul 19, 2026.
(10:40) Prize structure
(12:11) Interested in participating or following along?
(12:28) Why we're doing this
(13:11) We're excited to see what you build.
(13:27) The case studies
(13:30) COVID
(15:12) Starting material
(15:36) Black holes
(16:35) Eggs
The original text contained 8 footnotes which were omitted from this narration.
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First published:
June 4th, 2026
Source:
https://www.lesswrong.com/posts/frizRHnA6AZpJSDqw/lab-leaks-black-holes-and-eggs-epistemic-case-study
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Narrated by TYPE III AUDIO.
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