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William Wang
William Wang

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How I Used Mental Models from Charlie Munger to Debug My Code (and My Portfolio)

#productivity #python #investing #beginners

Last year, I hit a wall. My codebase was a mess, my debugging sessions stretched for hours, and — ironically — my investment portfolio was in a similar state of disarray. Then I picked up "Poor Charlie's Almanack" and discovered Charlie Munger's mental models.

What happened next changed how I approach both software engineering and investing.

The Inversion Principle: Stop Looking for Bugs

Munger's most powerful mental model is inversion — instead of asking "how do I solve this problem?", ask "how would I guarantee failure?"

In debugging, I stopped asking "where is the bug?" and started asking "what conditions would make this code definitely break?" This completely changed my approach:

# Instead of scanning for bugs, I invert the problem
def find_failure_conditions(function, test_cases):
    """
    Inversion: What inputs would GUARANTEE failure?
    """
    failure_modes = []
    edge_cases = [None, [], {}, 0, -1, float('inf'), ""]

    for case in edge_cases:
        try:
            result = function(case)
            if result is None or result == False:
                failure_modes.append({
                    'input': case,
                    'result': result,
                    'reason': 'Unexpected falsy return'
                })
        except Exception as e:
            failure_modes.append({
                'input': case,
                'error': str(e),
                'reason': 'Unhandled exception'
            })

    return failure_modes
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This approach cuts my debugging time in half. Instead of wandering through stack traces, I systematically eliminate what should work and zoom in on what cannot.

The same principle applies to investing. Instead of asking "which stocks will go up?", Munger asks "which businesses will definitely fail?" Avoid the losers, and the winners take care of themselves.

This is exactly the philosophy behind KeepRule — a platform that collects timeless investment principles from legendary investors like Buffett and Munger. It helps you build a framework of what to avoid, which is often more valuable than knowing what to chase.

Circle of Competence: Know Your Codebase (and Your Portfolio)

Munger emphasizes staying within your circle of competence. In software, this means:

  • Don't rewrite a module you don't fully understand
  • Don't optimize code before you understand the bottleneck
  • Don't adopt a new framework just because it's trending on Hacker News

I learned this the hard way when I tried to "optimize" a database query layer I barely understood. Three days later, I had introduced two new bugs and the performance was worse.

The same applies to investing. Munger never invested in things he didn't understand. He famously avoided tech stocks for decades — not because they were bad, but because they were outside his circle.

As developers, we actually have an advantage here. We understand technology deeply. We can evaluate whether a SaaS company's moat is real or just marketing fluff. We can read API documentation and understand whether a product is technically differentiated.

The Checklist Method: From Aviation to Code Reviews

Munger borrowed the checklist concept from aviation. Pilots don't skip pre-flight checks because they've done them a thousand times. Similarly, Munger uses investment checklists to avoid repeating mistakes.

I built a personal checklist for code reviews:

## My Code Review Checklist (Inspired by Munger)
- [ ] Does this change handle edge cases? (Inversion)
- [ ] Am I qualified to review this module? (Circle of Competence)
- [ ] What's the second-order effect of this change? (Systems Thinking)
- [ ] Am I approving this because everyone else did? (Social Proof bias)
- [ ] Would I bet my production server on this code? (Skin in the Game)
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This systematic approach eliminates the cognitive biases that lead to bugs slipping through review. It's the same reason KeepRule organizes investment wisdom into actionable principles — having a structured framework beats relying on intuition every time.

Lollapalooza Effect: When Multiple Bugs Converge

Munger coined the Lollapalooza Effect — when multiple psychological tendencies combine to produce extreme outcomes. In code, this is when several small issues compound into a catastrophic failure.

I once had a production incident where:

  1. A race condition (rare, maybe 1 in 10,000 requests)
  2. Combined with a cache invalidation bug (only on specific data shapes)
  3. During a traffic spike (when timeouts were being hit)

Each issue alone was harmless. Together, they brought down the entire service for 4 hours.

Now I look for Lollapalooza conditions in my architecture reviews. What happens when multiple things go wrong simultaneously? This is systems thinking applied to software reliability.

Avoiding Bias: The Developer's Blind Spot

Munger cataloged 25 cognitive biases. Several are deadly for developers:

1. Commitment and Consistency Bias
"I've been working on this approach for 3 days, so it must be right." How many times have you refused to scrap a bad implementation because you'd already invested time in it? That's the sunk cost fallacy in your IDE.

2. Authority Bias
"The senior engineer said this is fine, so it must be." Great engineers make mistakes. Question everything, respectfully.

3. Availability Bias
"The last production bug was a null pointer, so I'll only check for nulls." The most dangerous bugs are the ones you're not looking for.

4. Social Proof
"Everyone on the team approved this PR." Groupthink kills code quality. Be the one who asks the uncomfortable question.

Building Your Own Decision Framework

Here's what I did after studying Munger's models:

  1. Created a personal knowledge base of investment principles and decision frameworks
  2. Applied inversion to every debugging session and code review
  3. Defined my circle of competence and stuck to it
  4. Built checklists for recurring decisions

Tools like KeepRule make step 1 much easier — it's essentially a curated library of battle-tested investment principles from Buffett, Munger, and other legendary investors. I use it as a reference when making both financial and professional decisions.

The Unexpected Connection

Here's what surprised me most: improving my investment thinking made me a better programmer, and improving my programming thinking made me a better investor. Both domains reward:

  • Patient analysis over quick reactions
  • Systems thinking over isolated fixes
  • Avoiding mistakes over chasing wins
  • Compound learning over starting from scratch

Munger said: "Take a simple idea and take it seriously." The simplest idea from his mental models? Think about what can go wrong before you think about what can go right.

Apply that to your next debugging session, your next code review, and your next investment decision. You might be surprised by how much clearer everything becomes.

What mental models do you use in your engineering work? I'd love to hear about frameworks that help you make better decisions — drop a comment below.

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