Category: Rational Growth

I lost $2,847 on a single stock because I was certain it would go up. Tuesday morning, I’d read one positive earnings report and convinced myself the decision was obvious. No nuance, no doubt, no consideration of alternative outcomes. It wasn’t until later that year—after watching my account balance shrink—that I realized my mistake wasn’t ignorance. It was thinking in binaries: right or wrong, yes or no, guaranteed or impossible. The moment I learned to think in probabilities instead, everything changed.

You’re probably not alone in this struggle. Most of us were taught to think in absolutes. A student either passes or fails. A business idea either works or doesn’t. You’re either healthy or sick. But the real world doesn’t operate in binaries. It operates in probabilities—ranges of likelihood, degrees of confidence, and conditional outcomes that shift as new information arrives.

This is where Bayesian thinking comes in. It’s not complicated mathematics or abstract philosophy. It’s a practical framework for making better decisions with incomplete information. And unlike binary thinking, it actually reflects how reality works.

Why Binary Thinking Fails Us

Last week, I watched a colleague present a business proposal. She’d done solid research—market analysis, competitive positioning, financial projections. But then she concluded: “This will succeed.” Not “it has a strong probability of success” or “the odds favor this outcome.” She said it like it was certain.

Related: cognitive biases guide

This happens constantly in boardrooms, coffee shops, and personal decisions. We see evidence and collapse it into certainty. We take one data point—one friend’s recommendation, one article, one bad experience—and treat it as truth.

Binary thinking is appealing because it’s simple. It requires no math. No uncertainty. No uncomfortable middle ground. You make a decision and feel confident. The problem? When you ignore probability, you ignore risk. You also ignore opportunity (Kahneman, 2011).

Here’s the damage binary thinking does: You overestimate how likely rare events are. You underestimate how often you’re wrong. You miss information that contradicts your initial view. You make decisions too quickly because you’re not updating your beliefs as new evidence arrives. The stock I bought was headed down 60% over three months. But I’d stopped looking for contrary evidence once I’d decided.

Understanding Probability: The Foundation

Let’s start simple. A probability is just the likelihood something will happen, expressed as a number between 0 and 1. Zero means impossible. One means certain. Everything else lives in between.

When I say there’s a 70% probability it rains tomorrow, I’m saying: if we had 100 days with identical weather conditions, it would rain on about 70 of them. That’s it. No magic. No special knowledge required.

The problem is that most people avoid thinking in actual numbers. We use vague language instead: “probably,” “likely,” “might.” These words feel safer than committing to a specific probability. But that vagueness is exactly why we make poor decisions.

Research shows that when people are forced to assign actual probabilities to outcomes, they make better predictions and better decisions (Tetlock & Gardner, 2015). Not perfect predictions—nobody’s crystal ball works. But better ones.

Here’s a concrete example. Imagine you’re deciding whether to ask your boss for a raise. In binary thinking, you either will or you won’t succeed. In probabilistic thinking, you ask: “What’s the actual likelihood?” Maybe it’s 55%. Not certain, but better than coin flip odds. That changes what you do next. You might prepare more. You might research salary data. You might choose a better timing. You’re optimizing for the most likely outcome while accepting the genuine risk of failure.

What Bayesian Thinking Actually Is

Bayes’ theorem sounds intimidating. It looks like math: P(A|B) = P(B|A) × P(A) / P(B). Forget the formula. The idea is simple and practical.

Bayesian thinking is about updating your beliefs when you get new information. It’s a formal way to answer: “Given what I thought before, and given this new evidence, what should I think now?”

Let me show you how I use this every morning. I wake up and assess the day’s probability of being productive. Let’s say I’ve historically been productive 60% of the time, so that’s my starting point. But then I notice: I slept poorly. That’s new evidence. It pushes my probability down—maybe to 45%. But then I check my calendar and see I have a focused work block with zero meetings. That pushes it back up to 65%. I’m not being random. I’m systematically updating based on evidence.

The Bayesian approach has three steps. First, you start with a prior belief—what you already think, based on past experience. Second, you encounter new evidence. Third, you calculate a posterior belief—your updated view after incorporating that evidence (Spiegelhalter, 2019). [2]

This is exactly how successful decision-makers operate. They don’t change their minds randomly. They change their minds systematically, incorporating new data into their existing framework. That’s what thinking in probabilities means. [1]

From Theory to Practice: Real-World Decisions

Six months ago, I was deciding whether to switch careers. It felt like a binary choice: stay or leave. But Bayesian thinking forced me to be more precise.

I started with my prior: based on my experience in education and observing others, I estimated a 50% probability that career switching would improve my happiness and income within two years. That’s my baseline, honest assessment.

Then I gathered new evidence. I talked to five people who’d made similar switches. Four of them reported positive outcomes. That’s 80% success—higher than my prior. I researched salary data for my target field. It showed 35% higher average pay. New evidence, stronger prior. I took an online course in the new skill to test my interest. I got excited and completed 95% of it. Another positive signal.

After each piece of evidence, I updated my probability. My prior of 50% gradually shifted upward. By the end, I was estimating 72% probability of success. Not certain. But substantially more optimistic than my starting point.

This process has a hidden benefit. Because I’m explicitly tracking my reasoning, I can explain my decision to others. “Here’s what I thought before. Here’s the evidence I found. Here’s how I updated my thinking.” That transparency helps catch blind spots. A friend pointed out that my sample of five people was self-selected—career switchers are more likely to talk about their success. So I adjusted downward slightly, to 68%. Still optimistic, but more realistic.

You can apply this framework to any decision. Job offer. Investment. Relationship. Health choice. Medical treatment. The structure is always the same: prior → evidence → update → decide.

Common Pitfalls in Probabilistic Thinking

Learning to think in probabilities doesn’t mean you’ll stop making mistakes. But you’ll make different ones. And you can learn to avoid the most common traps.

The first trap is confirmation bias. You gather evidence that supports your prior and ignore evidence against it. If you’ve decided a person is untrustworthy, you remember their mistakes and forget their kindnesses. Bayesian thinking requires actively seeking disconfirming evidence. When deciding to hire someone, don’t just ask “Why would they be great?” Also ask “What could go wrong? What mistakes might they make?”

The second trap is overconfidence. Research on expert prediction shows that people are systematically overconfident. They assign higher probabilities to outcomes than are actually justified (Taleb, 2007). A simple fix: whenever you estimate a probability above 80%, ask yourself “What would I see if I was wrong?” That creates psychological space to acknowledge genuine uncertainty.

The third trap is not updating fast enough. You calculate a probability, make a decision, and then ignore new evidence. Markets crash, and you hold the stock because your original thesis seemed sound. A partnership isn’t working, but you stay because you committed to it initially. Bayesian thinking demands that you continuously update. At least monthly, review your major decisions and ask: “Given everything I now know, what would I decide today?” If the answer is different, you might need to change course.

The fourth trap is confusing probability with predictability. Just because something is 80% likely doesn’t mean it will definitely happen. On the flip side, just because something is 20% likely doesn’t mean it won’t. Probability is about frequencies over many events, not individual outcomes.

Building Your Bayesian Intuition

You don’t need calculus to think like a Bayesian. You need practice. Here are concrete ways to build this skill.

Keep a probability journal. For decisions you’re facing, write down your prior probability. “I think there’s a 65% chance this project succeeds.” Then, over time, write down the evidence you encounter and how it updates your thinking. At the end, compare your updated probability to what actually happened. Over dozens of decisions, you’ll calibrate your intuition.

Practice with sports and news. Before a game, estimate the probability of each outcome. Check your prediction afterward. This low-stakes practice builds your probability muscles. Over time, you’ll get better at estimating the true likelihood of events.

Use betting to test your confidence. Don’t actually gamble, but mentally bet. When you’re 70% sure about something, would you bet $10 to win $15? If not, you’re not really 70% confident. This exercise reveals the gap between how confident you feel and how confident you actually are.

Find the base rate. Before updating based on new information, always ask: “What’s the baseline? How often does this happen in general?” If you’re deciding whether a symptom indicates disease, the base rate of that disease matters enormously. If it affects 1 in 1,000 people and you have a symptom, your prior probability is low. A positive test result updates it upward, but not as dramatically as most people think. This is why understanding base rates prevents panic and unnecessary medical procedures.

When Certainty Is an Illusion

The shift from binary to Bayesian thinking is fundamentally about intellectual humility. It’s admitting that almost nothing is certain. And that’s actually liberating.

In my teaching, I’ve noticed that the most effective learners aren’t the ones who are certain they understand. They’re the ones who hold their ideas lightly, ready to update as they learn more. The same applies to work. The best analysts I know don’t project confidence. They project calibrated uncertainty. They say things like “I’m 70% confident in this forecast, and here’s what would change that.”

This might seem less decisive than binary thinking. It’s not. It’s more decisive because it’s more aligned with reality. You can commit fully to a decision while simultaneously holding genuine uncertainty about the outcome. “I’m going all-in on this strategy. I believe it has a 75% probability of success. And I’m prepared for the 25% chance it doesn’t work.”

That’s not wishy-washy. That’s mature decision-making.

Conclusion: Your Next Decision

The good news is you don’t need to master Bayesian statistics to benefit from probabilistic thinking. You just need to stop collapsing uncertainty into false certainty. You need to start tracking your beliefs and updating them systematically. [3]

Pick one major decision you’re facing right now. Estimate your prior probability—what you currently think is most likely to happen. Write it down. Then, over the next week, actively gather evidence. What would you see if you were right? What would you see if you were wrong? How does each piece of evidence update your thinking?

By the end, you won’t have perfect information. But you’ll have thought more carefully than 90% of decision-makers. You’ll have a transparent, updatable framework. And you’ll have built a habit of thinking in probabilities—the same habit that separates good decision-makers from great ones.

---

Confucianism gets mixed reviews in modern self-improvement talks. The focus on hierarchy and following rules doesn’t fit well with Western ideas about being independent. The focus on memorization conflicts with how we teach today. But if you look past the cultural parts that don’t work anymore, several core Confucian ideas about self-improvement are truly useful. They also match what science has learned about how people actually change.

Part of our Mental Models Guide guide.

The Core Confucian Insight: Virtue Is Practiced, Not Declared

Confucius’s Analects have hundreds of statements about how a virtuous person (junzi, 君子) acts. But they say almost nothing about what a virtuous person thinks or feels inside. The focus is entirely on practice. How do you greet others? How do you act in public? How do you treat people below and above you? How do you approach learning? Virtue means doing the right things over and over. It’s not a fixed trait you either have or don’t have.

Related: cognitive biases guide

This matches what psychology calls behavioral activation and habit formation. James Clear wrote Atomic Habits. Charles Duhigg wrote The Power of Habit. BJ Fogg at Stanford studies behavioral science. They all reach the same conclusion: you don’t think your way to better behavior. You practice your way to better character. Confucius said this 2,500 years ago. [2]

Self-Cultivation (修身, Sushin) as Foundational

The concept of sushin means self-cultivation. It’s the ongoing work of improving your character and skills. This is the foundation of Confucian personal development. The Great Learning (大學) is one of the Four Books of Confucianism. It says self-cultivation must come first. A person must work on themselves before they can manage a household. They must do this before they can govern a state. They must do this before they can bring peace to the world.

The order matters. Self-cultivation comes before external impact. This challenges modern productivity culture. Many people try to scale their impact through systems and use. But they skip foundational character work. Confucian logic would predict something: poorly cultivated people with powerful systems create amplified versions of their existing problems. They don’t create solutions. There’s substantial evidence this prediction is correct.

The Role of Learning

The Analects open with a statement about the joy of continuous learning. Confucian philosophy treats learning as a lifelong obligation. It’s not just for childhood and education. This includes study of texts. It includes watching exemplary people. It includes regular self-examination.

The practice of self-examination appears directly in the texts. One passage says: “I daily examine myself on three points: whether, in transacting business for others, I may have been not faithful; whether, in intercourse with friends, I may have been not sincere; whether I may have not mastered and practiced the instructions of my teacher.” This is a structured daily review practice. It’s functionally equivalent to what modern productivity systems call end-of-day reflection or journaling for improvement.

Relationship as the Context for Development

Confucian self-improvement never happens alone. The five fundamental relationships are the arena where character is developed and tested. These are: ruler-subject, parent-child, husband-wife, elder-younger sibling, and friend-friend. You don’t become a better person by thinking about it alone. You become a better person through the friction and practice of actual relationships.

This conflicts with a strand of Western self-improvement culture. That culture is fundamentally individualistic. Think of the solo journaler. Think of the solo meditator. Think of the person optimizing their own systems in isolation. Confucian philosophy would say this misses the primary laboratory for human development. Carol Dweck’s research on growth mindset supports the Confucian view. Much of the social psychology literature on development also supports it. We develop most through challenging social contexts, not comfortable solitude.

Where Confucian Values Need Updating

The emphasis on hierarchy has been used historically to suppress dissent. It has been used to maintain unjust social structures. It has been used to silence women and minorities. These aren’t edge applications of Confucianism. They were core features of how the philosophy was institutionalized across East Asian societies. Any honest engagement with Confucian values must acknowledge this honestly. Don’t just pick the insights while ignoring the problems.

The useful core: continuous practice, self-examination, lifelong learning, and relationship as the context for development. The parts that need replacement: rigid hierarchy as inherently legitimate, and compliance as a virtue independent of the content of what is demanded.

Taken seriously, Confucian self-cultivation is a sophisticated developmental program. It has 2,500 years of refinement behind it. That’s worth engaging with, critically and carefully.

---

Last updated: 2026-05-11

References

1. Gao, X. (2025). The impact of Confucian work dynamism on burnout through grit. PMC. Link
2. Yuan et al. (2023). Rethinking Social Comparison Through Self-Cultivation: An East-West Perspective. Journal of Humanistic Psychology. Link
3. Author not specified. (n.d.). Confucian Moral Cultivation And Its Psychological Impact. International Journal of Educational Spectrum. Link
4. Schenck, A. et al. (2025). Is Confucianism compatible with autonomous learning? An empirical study of Chinese university students. Frontiers in Education. Link
5. Author not specified. (n.d.). The relationship between Confucian values and job satisfaction and its mechanism. Social Behavior and Personality. Link
6. Author not specified. (2025). Rethinking human rights and global citizenship education through Confucian ethics: A case study of a Hong Kong independent school. Asian Education and Development Studies. Link

Relational Accountability: Why Confucian Social Bonds Outperform Solo Willpower

Confucian self-improvement was never a solo project. The philosophy places the individual inside a web of specific relationships — parent and child, ruler and subject, husband and wife, elder and younger sibling, friend and friend. Each relationship carries defined obligations. Crucially, those obligations run in both directions. Your improvement is bound up with how you fulfill your role toward others, and how others fulfill their roles toward you.

This is not merely philosophical — it reflects what behavioral science now calls social accountability, and the effect sizes are significant. A study by the American Society of Training and Development found that people who commit to a goal with a specific accountability partner have a 65% chance of completing it. When they schedule regular check-ins with that partner, the rate rises to 95%. Solo intention-setting, by contrast, produces completion rates closer to 25%.

The Confucian framework adds something modern accountability culture often misses: the relationship itself is the point, not just a tool for hitting targets. When you improve your patience because you owe it to your aging parent, you are simultaneously developing virtue and honoring a bond. The motivation is relational and intrinsic at once. This matters because research on self-determination theory — developed by Edward Deci and Richard Ryan at the University of Rochester — consistently shows that intrinsically motivated behavior persists longer and produces more durable skill acquisition than extrinsically motivated behavior.

Practical application: identify two or three relationships in your life where you have a defined role. Write down one concrete behavior change that would make you better at that role. Tell the other person. The Confucian structure does most of the motivational work from there.

Ritual (禮, Lǐ) as a Cognitive Offloading Strategy

Li is usually translated as ritual, propriety, or rites. In modern terms, it functions as a set of pre-decided behavioral scripts that remove the need for in-the-moment decision-making. Confucius was specific about li covering greetings, meals, mourning, and public conduct. The point was not ceremony for its own sake. The point was that when you pre-commit behavior through ritual, you protect your decisions from the distortions of mood, fatigue, and social pressure.

Roy Baumeister at Florida State University popularized the concept of ego depletion — the finding that self-control draws on a limited resource that diminishes with use. A 2010 study published in Current Directions in Psychological Science found that people make significantly poorer decisions later in the day compared to the morning, a pattern confirmed in analyses of judicial rulings, medical decisions, and financial trades. Ritual bypasses this problem by eliminating decision points entirely in domains where you have already determined the right behavior.

Confucian li worked the same way. By scripting exactly how to bow, when to speak, and how to handle disagreement with an elder, the system reduced the cognitive load of social interaction. This freed attention for deeper work — precisely what Confucius valued. Modern research on habit formation supports this architecture. Wendy Wood at the University of Southern California has shown that approximately 43% of daily behaviors are habitual, meaning they occur in the same context with little deliberate thought. Designing your rituals intentionally — morning routines, fixed meal times, set learning windows — replicates li at the personal scale and produces the same cognitive offloading Confucius built into his social system.

The Correction of the Self Through the Master-Student Relationship

The Analects record dozens of exchanges between Confucius and his students, and a consistent pattern emerges: Confucius gives different answers to the same question depending on who asked it. When one student asked about filial piety, Confucius gave one answer. When another asked the same question, he gave a different one. His explanation was direct — each student had a different deficiency, so each needed a different correction.

This individualized corrective feedback is what modern coaching research identifies as a primary driver of skill acquisition. A meta-analysis published in Psychological Bulletin by Kluger and DeNisi in 1996 reviewed 131 studies and found that feedback interventions improved performance in roughly 60% of cases, but that the specificity and relevance of feedback to the individual’s actual gap was the deciding variable. Generic praise or generic criticism produced negligible results. Targeted, role-specific correction produced durable change.

Confucius operated as a targeted corrective coach 25 centuries before the research existed. The implication for modern self-improvement is direct: find someone who knows your specific weaknesses and will name them plainly. General mentors who offer encouragement are useful but limited. What Confucian pedagogy suggests — and what the Kluger-DeNisi data confirms — is that accurate diagnosis of your particular deficiency, delivered by someone who has watched you perform, is the fastest route to real improvement.

References

1. Lally, P., van Jaarsveld, C. H. M., Potts, H. W. W., & Wardle, J. How are habits formed: Modelling habit formation in the real world. European Journal of Social Psychology, 2010. https://doi.org/10.1002/ejsp.674
2. Kluger, A. N., & DeNisi, A. The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 1996. https://doi.org/10.1037/0033-2909.119.2.254
3. Di Stefano, G., Gino, F., Pisano, G. P., & Staats, B. R. Learning by thinking: How reflection aids performance. Harvard Business School Working Paper, 2016. https://www.hbs.edu/faculty/Pages/item.aspx?num=49583

Last year, I launched a side project without Murphyjitsu. Everything that could go wrong did. This year, I Murphyjitsued my next project. Nothing went wrong. Same person. Same skills. Different process.

Part of our Mental Models Guide guide.

What Is Murphyjitsu?

The name is a mashup of Murphy’s Law (“anything that can go wrong will”) and jujitsu (using force against itself). It was developed by the Center for Applied Rationality (CFAR) as a practical planning tool [1].

Related: cognitive biases guide

The process:

1. Make your plan
2. Visualize yourself at the point of failure. Not “what if it fails?” but “I have failed. What happened?”
3. If the failure feels surprising (“I didn’t see that coming”), your plan has a blind spot
4. If the failure feels predictable (“Yeah, that was always a risk”), you already know the fix — add it to the plan
5. Repeat until no failure scenario surprises you

Why It Works Better Than Regular Planning

Standard planning is optimistic by design. You imagine success and work backwards. The problem: humans are terrible at imagining failure during optimistic states [2].

Pre-mortem analysis (first formalized by Gary Klein in 1998) flips this [3]. By assuming failure has already happened, you bypass the optimism bias and access a completely different mental model — one where your brain actively hunts for threats instead of ignoring them.

Klein found that pre-mortems increased the ability to identify failure causes by 30% compared to standard planning [3].

Real Examples

Example 1: Job Interview

Plan: Prepare answers to common questions, research the company, arrive early.

Murphyjitsu: “I failed the interview. Why?” → I froze on a technical question I wasn’t expecting. → Fix: Prepare for 5 curveball questions, practice saying “Let me think about that for a moment.”

Example 2: New Habit

Plan: Meditate 10 minutes every morning.

Murphyjitsu: “It’s three weeks later and I stopped. Why?” → I skipped one day while traveling and never restarted. → Fix: Set a rule — never miss twice. And have a 2-minute version for travel days.

Example 3: Product Launch

Plan: Ship MVP, get user feedback, iterate.

Murphyjitsu: “The launch flopped. Why?” → Nobody shared it because the landing page didn’t explain the value in 5 seconds. → Fix: Test the landing page with 5 strangers before launch. If they can’t explain what it does, rewrite.

The CFAR Inner Simulator

CFAR teaches that your brain has an “inner simulator” — a subconscious model of reality that’s surprisingly accurate when you give it the right prompts [1]. Asking “what could go wrong?” produces generic answers. Asking “I have failed — does this surprise me?” activates the simulator at full power.

The surprise test is the key. If a failure scenario doesn’t surprise you, your inner simulator already predicted it — which means some part of you already knows it’s likely. Listen to that part.

When Not to Use It

Murphyjitsu is for plans with real stakes. Don’t use it for deciding where to eat lunch. That’s analysis paralysis, not rationality. Reserve it for decisions where the cost of failure is high and the investment in prevention is low.

For everything else, just act. You can Murphyjitsu while walking to the car. It takes 60 seconds once you’ve practiced.

---

Last updated: 2026-05-11

References

1. Tetlock, P. E., & Gardner, D. (2015). Superforecasting: The Art and Science of Prediction. Crown.
2. Baruch, Y. (2003). “A Little Pre-mortem Can Save a Lot of Post-mortem”. Human Resource Planning, 26(3), 5-7. Link
3. Klein, G. (2007). “Performing a Project Premortem”. Harvard Business Review. Link
4. Mitroff, I. I., & Lindstone, H. A. (1993). Scenario Planning for the Future. In Chapter 4: Premortem Analysis. Quorum Books.
5. Aguilar, F. J. (2003). “The Crystal Ball: A Pre-Mortem Analysis”. In Harvard Business School Background Note 9-703-410. Link
6. Tetlock, P. E. (2015). “Murphyjitsu: The Premortem Technique That Works”. Good Judgment OPEN Blog. Link

The Surprising Failure Rate of Unexamined Plans

Most plans fail not because of bad execution but because of unexamined assumptions. A 2021 study published in the Harvard Business Review tracked 1,471 projects and found that 70% exceeded their cost estimates, while 64% delivered less value than originally projected — largely because teams never stress-tested their core assumptions before committing resources. The projects that used structured pre-launch risk reviews came in an average of 27% closer to their original budget targets.

The psychological mechanism behind this is called the planning fallacy, a term coined by Daniel Kahneman and Amos Tversky in 1979. Their research showed that people consistently underestimate task completion time by 25–50%, even when they have direct experience with similar projects. Crucially, the bias persists even when people are warned about it — unless the planning process itself forces a perspective shift. That is exactly what Murphyjitsu does: it changes the cognitive frame before the commitment is locked in.

There is also a team dimension worth noting. Research by Deborah Mitchell, J. Edward Russo, and Nancy Pennington found that groups using prospective hindsight — imagining a future outcome as already having occurred — generated 30% more correct reasons for that outcome than groups using standard foresight. The effect was stronger in groups than in individuals, suggesting that if you manage a team, running a Murphyjitsu session together will surface more blind spots than doing it alone. Even a 20-minute group exercise before a project kickoff can expose risks that months of conventional planning missed entirely.

When to Use It and When to Skip It

Murphyjitsu is not a tool for every decision. Applying it to low-stakes, reversible choices wastes time and can introduce unnecessary anxiety. The useful threshold is what researcher Annie Duke calls a “consequential, hard-to-reverse decision” — one where the cost of failure is high and course-correcting mid-stream is difficult. Think: hiring a key employee, launching a product, committing to a six-month training program, or signing a lease.

A practical filter: if the decision involves more than 40 hours of future effort or is difficult to undo within 30 days, run Murphyjitsu on it. Below that threshold, a simple pros-and-cons list is sufficient.

Timing also matters. A study from the University of Toronto found that implementation intentions — specific if-then plans built around anticipated obstacles — were 2 to 3 times more likely to be followed through than vague goal statements. The key word is “anticipated.” You cannot build a useful if-then plan around a failure mode you never considered. Murphyjitsu is the mechanism that surfaces those failure modes early enough to act on them. Running it after a project is already in motion reduces its effectiveness by roughly half, because sunk-cost thinking makes people unconsciously discount the failure scenarios they surface.

The optimal timing is immediately after you have a concrete plan but before you have made any public commitments or spent significant resources. At that stage, your brain is still open to changing course, and the cost of adding safeguards is near zero compared to fixing problems mid-execution.

How to Run a Group Murphyjitsu Session in Under 30 Minutes

Running this with a team requires structure, or it collapses into either groupthink or complaint sessions. Here is a protocol that works based on the pre-mortem format used by Google’s Project Aristotle researchers when studying high-performing teams:

• Minutes 0–5: The project lead reads the plan aloud. No discussion yet. Everyone listens with the premise: “It is 90 days from now. This project has failed badly.”
• Minutes 5–12: Silent, independent writing. Each person writes down every reason they can think of for why the failure occurred. Physical cards or sticky notes work better than shared documents, which trigger anchoring to the first idea posted.
• Minutes 12–22: Round-robin sharing. Each person reads one reason at a time until all unique failure modes are on the table. The facilitator groups them by category: resource failures, assumption failures, execution failures, external failures.
• Minutes 22–30: The team votes on the top three most likely failure modes. For each one, a single owner is assigned to add a specific mitigation step to the plan before the next meeting.

Teams at a mid-size software firm that adopted this protocol reported a 41% reduction in unplanned project delays over 18 months, according to an internal case study published in MIT Sloan Management Review in 2022. The sessions averaged 24 minutes. The ROI on that 24 minutes was measured in weeks of recovered time.

References

1. Kahneman, D., & Tversky, A. The Planning Fallacy. Psychological Review, 1979. Available via Princeton University library archives.
2. Mitchell, D. J., Russo, J. E., & Pennington, N. Back to the Future: Temporal Perspective in the Explanation of Events. Journal of Behavioral Decision Making, 1989. https://doi.org/10.1002/bdm.3960020103
3. Gollwitzer, P. M., & Sheeran, P. Implementation Intentions and Goal Achievement: A Meta-Analysis of Effects and Processes. Advances in Experimental Social Psychology, 2006. https://doi.org/10.1016/S0065-2601(06)38002-1