AI Berkshire: One Person + AI = A Full Investment Research Team

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🔥 AI Berkshire: One Person + AI = A Full Investment Research Team

Meta Description (SEO‑friendly, 155 characters):
AI Berkshire is an open‑source multi‑Agent investment framework that systematizes Buffett, Munger, Duan Yongping, and Li Lu’s methods into actionable reports.

📖 Introduction

Most AI tools for investing give vague answers like “on one hand… on the other hand…”. AI Berkshire breaks that mold. Built on Claude Code / Codex, it transforms the wisdom of Buffett, Munger, Duan Yongping, and Li Lu into a structured multi‑Agent investment research framework. The result? Clear reports with price ranges, position sizing, and explicit conclusions — validated by real trading performance:

  • 2024: +69.29%
  • 2025: +66.38%
  • Two‑year cumulative profit: over ¥1.46M

🔎 What Makes AI Berkshire Different?

  • Multi‑Agent adversarial research: /investment-team runs four independent agents, each simulating a master’s perspective, cross‑challenging and validating.
  • Forced conclusion mechanism: Every stock gets a verdict — Pass / Fail / Grey Zone — with price ranges and layered allocation advice.
  • Bias‑resistant structure: Built‑in richness ratings (A/B/C), Munger‑style inversion, and contrarian “why smart people short” checks.
  • Financial‑grade rigor: All calculations use Python decimal.Decimal, with manual market cap cross‑checks to avoid LLM math errors.
  • Repeatable research process: Standardized scoring across companies, longitudinal comparisons over time.

👥 Who Should Use It?

  • Individual investors: Filter hundreds of stocks with /investment-research, eliminating 80% of false opportunities.
  • Analysts: Compress deep report cycles from days to hours with /investment-team.
  • Portfolio managers: Use /earnings-review each quarter to validate holdings with the “mirror test” (5 sentences must explain the business logic).
  • Learners: Follow /deep-company-series to generate 120k words of structured insights, walking through master investors’ thought processes.

✨ Core Advantages

  1. Multi‑Agent orchestration → Parallel perspectives, adversarial validation.
  2. Explicit decision outputs → No vague analysis, only actionable verdicts.
  3. Bias checks → Prevents false certainty from data overload.
  4. Precision math → Decimal‑based calculations, currency sanity checks.
  5. Process reproducibility → Standardized scoring, longitudinal tracking.

🚀 Getting Started

  • GitHub Project: AI Berkshire
  • Installation: Clone into Claude Code / Codex environment.
  • Usage: Trigger skills like /investment-team, /investment-research, /earnings-review, /deep-company-series.

📌 Tags

AIInvesting #ValueInvesting #MultiAgent #ClaudeCode #OpenSourceFramework

🎯 Conclusion

AI Berkshire is not another chatbot that “analyzes stocks.” It’s a structured, multi‑Agent investment research framework that delivers actionable decisions, validated by real trading results. For investors, analysts, and learners alike, it’s a way to scale Buffett‑style thinking with AI orchestration — turning one person into a full investment research team.