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AI Berkshire

github.com/xbtlin/ai-berkshire
Value InvestingMulti-AgentClaude CodeResearch Framework
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Two years of live trading with AI: +135% returns

WHAT IT SOLVES

Value investing analysis is expertise-heavy — retail investors can't realistically run Buffett, Munger, Li Lu, and Duan Yongping's frameworks in parallel to cross-check a single company

WHY IT'S INTERESTING

Product taste

Four masters' playbooks, not decoration

Buffett, Munger, Duan Yongping, and Li Lu each get their own agent with a distinct analytical checklist. It's not a name-drop prompt — agents run adversarial analysis from different angles and converge into one research report

Real craft

1,378 commits, battle-tested with real money

The +135% live track record over two years is the hardest proof. 1,378 commits, 15.5k stars, and reports still rolling in (Moutai 10-year profit projection just landed) — this isn't a demo, it's a living system

Two years of live trading at +135% — let me walk you through the multi-agent research framework I built with Claude Code

TECH GUESS

Claude Code / Codex driving a multi-agent workflow; prompt-layer defines each master's analytical framework, likely Python for data scraping and report generation

📍 Source: v2ex📅 2026-08-17Original post →Visit site →
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