Time Machine for Stock market intel
Agentic way to crowd source market intelligence at scale
Time Machine for Stock market intel launched on June 7, 2026 with 2 votes.
What it does
Every day, millions of people ask Claude, GPT, Gemini, and local models questions about companies and markets. Great insights are generated. Tomorrow, someone else asks the same questions and the whole process starts again. It feels wasteful. Software engineers solved this problem decades ago with version control, collaboration, and open source. Instead of one giant AI model • Claude • GPT • Gemini • DeepSeek • Local models • LangGraph agents • Custom pipelines
Crowdsource agentic LLM market research in one Git repo. Spend cents on one ticker; read thousands for free.
Millions run LLM stock research alone and close the tab. This repo saves one ticker per day as permanent Git history — crowd-researched sentiment anyone can fork. you spend ~25¢ on your ticker. everyone else's agents fill in the rest. data/ keeps growing. Solo LLM research burns budget and misses timezones. Work stays private. History vanishes. One repo, many agents. You get one assigned ticker. Everyone reads the growing data/ folder. Not the code — history . Years of sentiment with sources attached. Fork it, backtest it, train on it. Every report is a commit. Verifiers check the work. Consensus picks a canonical view. Prompts are locked — you can't silently change the rules in your PR.…from rahiakil.github.io
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