Seriously, I’m done with buying stocks based on gut feelings 😭
Always chasing highs and selling lows, falling asleep the moment I look at financial reports, relying on pure superstition for analysis...
Until I stumbled upon this open-source project ai-berkshire 👇
It uses Claude Code to replicate the investment logic of Buffett, Munger, Duan Yongping, and Li Lu!
Four AI masters simultaneously auditing your portfolio—can you believe it? 🤯
What Can It Actually Do?
Simply put: treat yourself as a fund manager, and let four AI Agents analyze companies the way Buffett and his peers would
Then cross-validate, challenge each other’s arguments, and finally deliver a composite score 📊
Here’s a breakdown of the core features 👇
1️⃣ Four Masters in Parallel
Buffett Agent: Focuses on moat strength + financial stability
Munger Agent: Specializes in finding pitfalls, reverse thinking + psychological biases
Duan Yongping Agent: Evaluates business models and corporate culture
Li Lu Agent: Calculates circle of competence + long-term compounding
Each Agent scores independently, and a final arbiter Agent reconciles conflicting views
It’s like hiring four analysts for a meeting—without paying salaries 😂
2️⃣ Real-World Test on Apple (AAPL)
I imported 2024 financial data and got the following output:
Buffett: 82 ✅ Strong moat, buyable but wait for a pullback
Munger: 68 ❌ Over-reliant on iPhone, AI narrative too optimistic
Duan Yongping: 90 🔥 Great business, fair price
Li Lu: 75 ⚖️ Suitable for long-term holding, watch for antitrust risks
Arbiter Conclusion: 78, recommended position size no more than 15%, wait for PE below 25x
Honestly, this is far more professional than my own analysis...
3️⃣ Multi-Agent Parallel Mechanism
The core code lives in orchestrator.py, using asynchronous parallelism to run all four Agents
In real tests, Claude Sonnet 4 took 45 seconds, while serial execution would take 2.5 minutes
But ⚠️ Pitfall Warning: Claude API has rate limits and tends to stall during peak hours!
4️⃣ Open Source and Free, but High Barrier to Entry
Requires Python 3.10+, Claude Code or Codex access
Suitable for value investors with programming skills and quantitative researchers
Not a silver bullet ❌ It won’t make you money, but it can systematize your research process and reduce emotional interference
Real User Experience
👍 Pros: Reduces subjective bias, transparent analysis logic, customizable Agents
👎 Cons: Relies on API stability, high token consumption (~30k tokens per analysis), unsuitable for short-term trading
Who Is It For?
Value investors who know Python
Retail investors looking to systematize their research
Tech enthusiasts curious about AI + finance crossover
Not for: Beginners, day traders, or anyone who doesn’t want to deal with code
Summary
ai-berkshire is not a stock-picking miracle tool—it’s a research framework
It translates the thinking models of Buffett and others into executable code
Use it as a supplementary tool for investment research, but don’t expect it to make you rich 🚀
Want to know how to configure Claude Code? There’s a full tutorial on my profile.
Drop a comment and share what AI stock tools you’ve tried!
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