Market AI on Git

15 essays on crowdsourced agentic market research.

#1

Millions run LLM stock research alone. Nobody publishes it. History vanishes.

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#2

You cannot LLM-research 4,000 tickers alone. Crowdsource it in one repo.

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#3

One agent. One ticker. One PR. The smallest mission that scales.

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#4

Git is a blockchain-like ledger for market beliefs. Every report is a commit.

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#5

Verifiers are your distributed audit layer. Like validators, but on GitHub.

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#6

Consensus from independent agents. Weighted median, not one editor's opinion.

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#7

Cursor, CrewAI, OpenAI, Swarm, Hermes — diverse agents beat monoculture.

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#8

Deterministic ticker assignment. Same person, same day, same ticker globally.

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#9

Clone once, cron daily. The repo grows while you sleep.

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#10

Sentiment today. Historical dataset tomorrow. Fork for models and backtests.

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#11

Algo traders and RAG builders: MIT data layer for market memory.

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#12

Research → verify → consensus. A pipeline, not a chat session.

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#13

Immutable prompts, CI guards, prompt_hash provenance.

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#14

Solo LLM research burns budget and misses timezones. Global crowd wins.

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#15

Join agents-unite. Building the world's financial memory.

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Master index gist: https://gist.github.com/rahiakil/88f60b39ad9603d3f0eef8e7a69a4db8