You already know how to succeed. You just haven't extracted the formula.
You have succeeded before. Not abstractly — concretely. You shipped a project that mattered. You maintained a difficult habit for months. You had a conversation that changed a relationship. You solved a problem that had been stuck for weeks. These weren't random events. They share structural elements — conditions, behaviors, sequences — that you can identify, name, and deliberately recreate.
But most people never do this. They study their failures obsessively and treat their successes as flukes. When something goes wrong, they ask "what happened?" When something goes right, they say "I got lucky" and move on. The result is a detailed map of what doesn't work and almost no map of what does.
In L-0114, you mapped your resistance patterns — the consistent ways you avoid and procrastinate. This lesson is the mirror image. Your successes are just as patterned as your failures. And the patterns are just as extractable, just as nameable, and far more useful.
The asymmetry: why you study failure but ignore success
There's a well-documented cognitive bias at work here. Most people reflexively attribute their failures to internal causes ("I'm not disciplined enough") and their successes to external ones ("the timing was right," "I had a good team"). Psychologists call variants of this pattern the fundamental attribution error and self-serving bias, but in practice, many high-performers run it in reverse — they internalize blame and externalize credit. The net effect is the same: your failure patterns become visible and your success patterns stay hidden.
The US Army discovered this problem decades ago and built a formal solution. After Action Reviews (AARs), developed in the 1970s, are structured debriefs organized around four questions: What did we intend to do? What actually happened? Why did it happen that way? What will we do next time? The critical design choice was that AARs are conducted after both failures and successes. A 2020 meta-analysis of 61 studies involving over 3,000 individuals found that AARs produce a large effect on training outcomes (d = 0.79), reducing mistakes in repeated tasks by up to 20%. But the mechanism works in both directions: units that debriefed their wins developed what the Army calls "cookbook recipes" — codified best practices extracted from their own successful performance, not from doctrine or theory.
The lesson is direct. You need a structured process for debriefing your wins, not just your losses. Without one, you'll keep succeeding accidentally and failing systematically.
Positive deviance: finding what already works
In 1991, Jerry Sternin arrived in Vietnam as the new director of Save the Children, facing an impossible mandate: reduce child malnutrition across Vietnamese villages within six months. More than 65% of children in those communities were malnourished. He had no budget for food programs and no time for infrastructure.
Instead of studying why most children were malnourished — the standard problem-focused approach — Sternin asked a different question: Are there any families whose children are well-nourished despite having the same poverty, the same resources, and the same constraints as everyone else? The answer was yes. And those families were doing specific, observable things differently. They collected small shrimp and crabs from rice paddies (protein sources that other families considered inappropriate for children), they added sweet potato greens to meals, they washed their children's hands before eating, and they fed their children three to four times daily instead of the customary two.
Sternin didn't import a solution. He found one that already existed inside the system. A randomized prospective trial across 12 communes confirmed that children in intervention communities — where these positive deviant behaviors were identified and spread — grew better, ate more often, consumed more energy, and experienced less respiratory infection. The program eventually reached over 2.6 million people across 265 Vietnamese communities, and the methodology — called Positive Deviance — has since been applied to problems ranging from hospital infection rates to girl trafficking in Indonesia.
The principle that matters for personal epistemology is this: the solution to your performance problem probably already exists somewhere in your own history. You don't need a new framework. You need to find the times when you were already doing it right — the positive deviations in your own behavioral data — and understand what made those times different.
This is a fundamentally different orientation than self-improvement through weakness remediation. You're not looking for what's broken. You're looking for what's already working and asking why it isn't working all the time.
Strengths-based evidence: build on what works
This orientation has substantial empirical backing. Peterson and Seligman's VIA Classification of Character Strengths — a three-year project involving 55 social scientists, now translated into over 41 languages with 700+ published research articles — identified 24 character strengths organized under six universal virtues. The critical finding wasn't the taxonomy itself but what happens when people use their identified strengths deliberately. A meta-analysis of the "use a signature strength in a new way" intervention found that it boosted happiness and flourishing while decreasing depression in randomized controlled studies.
Donald Clifton, who received a Presidential Commendation from the American Psychological Association as "the father of strengths-based psychology," built the CliftonStrengths assessment around a core claim: individuals gain far more when they invest effort in building on their greatest talents than when they spend comparable effort remediating their weaknesses. While the independent psychometric validation of the specific assessment has been debated, the underlying principle — that amplifying strengths outperforms fixing weaknesses — is supported across multiple research programs in positive psychology.
The practical takeaway is counterintuitive for most people: your highest-leverage move isn't to fix what's wrong. It's to identify what's already working and do more of it, more deliberately, in more contexts.
Exception-finding: the therapist's version
Solution-Focused Brief Therapy (SFBT), developed by Steve de Shazer and Insoo Kim Berg in the 1980s, operationalized this principle for therapeutic practice. The core technique is exception-finding: instead of analyzing the problem in detail, the therapist asks the client to identify times when the problem was absent or less severe. When were you not anxious? When did the conflict not escalate? When did you actually follow through on the thing you usually avoid?
These exceptions aren't random. They have structure. Maybe you don't procrastinate when the stakes are visible to someone you respect. Maybe you don't lose your temper when you've had a full night's sleep. Maybe you write fluently when you start before checking email. Each exception is a success pattern hiding in plain sight.
The evidence base is substantial: close to 150 randomized clinical control studies across multiple countries and clinical settings show positive benefit from SFBT, with effect sizes comparable to CBT and interpersonal therapy but achieved in fewer sessions. A study comparing solution-focused techniques directly found that the miracle question and exception-finding conditions were more effective than problem-focused conditions in reducing negative affect.
De Shazer's insight applies far beyond therapy: the conditions under which your problem doesn't occur are more actionable than the conditions under which it does. If you want to understand your success patterns, stop asking "why do I fail?" and start asking "when do I succeed, and what's different about those times?"
Deliberate practice: what experts actually do differently
K. Anders Ericsson's research on expert performance adds another dimension. His framework of deliberate practice — structured training designed to improve specific aspects of performance — explains how experts develop and refine their skills over time. But there's an underappreciated element in his work: experts don't just practice more. They develop increasingly sophisticated mental representations of what good performance looks and feels like. They know what success is supposed to be at a granular level, which allows them to detect deviations and self-correct in real time.
A replication study (Macnamara & Maitra, 2019) found that deliberate practice accounts for about 26% of the variance in performance — significant, but not the whole story. The remaining variance comes from factors including the quality of one's mental model of success. In other words, it's not enough to repeat an activity. You need to know what the successful version looks like so precisely that you can recognize and reproduce the pattern.
This is exactly what success pattern extraction gives you: a detailed, experience-grounded mental model of your own high performance. Not an abstract ideal. Not someone else's framework. A structural description of what you do when things go well — the conditions, the sequence, the specific behaviors — precise enough to serve as a template.
Your Third Brain: AI as success pattern miner
This is where AI becomes a genuine thinking partner rather than a productivity shortcut. If you've been externalizing your thinking — keeping project retrospectives, journal entries, decision logs, even scattered notes about how things went — you're sitting on a dataset of your own performance that you've never systematically analyzed.
Feed an AI your last ten project retrospectives and ask: "What conditions are present in every project I rated as successful? What conditions are present in every project I rated as a struggle?" The AI will surface patterns you can't see because you're too close to the data. It will notice that your successful projects all started with a written scope document, or that your best months all followed a week of deliberate rest, or that your highest-rated presentations all had a specific structural element in common.
Gary Klein's pre-mortem technique — imagining a project has already failed and generating reasons why — is well-established in risk management. Prospective hindsight research from Wharton, University of Colorado, and Cornell found that mentally transporting to the future increased the ability to accurately forecast outcomes by 30%. But the technique has a positive counterpart called the pre-parade: imagine the project has succeeded brilliantly. What happened? What decisions were made? What conditions were in place?
AI supercharges both techniques. You can run a pre-parade against your extracted success patterns: "Given that my success patterns include X, Y, and Z, generate a pre-parade for this upcoming project. What does success look like if I engineer those conditions from day one?" The AI doesn't replace your self-knowledge — it makes your self-knowledge operational.
Protocol: extracting your personal success formula
This isn't a journaling exercise. It's a structured extraction process.
Step 1: Select five genuine successes. Not modest ones. Pick five times in the past three years where you performed at a level that surprised even you. Shipped something important. Solved something hard. Sustained something difficult. Won something competitive.
Step 2: For each success, answer five questions in writing.
- What conditions were present? (Environment, energy, time of day, season, resources available)
- What did you do that was different from your default? (Specific behaviors, sequences, preparation)
- Who was involved, and what role did they play? (Accountability partner, collaborator, audience, challenger)
- What was your internal state? (Focus level, emotional tone, confidence, pressure)
- What happened in the 48 hours before the success? (Setup behaviors, rituals, decisions)
Step 3: Cross-reference. Lay all five side by side. Highlight every element that appears in three or more. Those overlapping elements are your success pattern — not a theory about success, but an empirical description of your specific conditions for high performance.
Step 4: Name the pattern. Give it a concrete label. "Deep morning + written scope + one accountability partner" is more useful than "be more disciplined." The specificity is the point.
Step 5: Engineer it forward. Before your next important project, check each element of your named success pattern against your plan. Which conditions are present? Which are missing? Which can you create deliberately? Build the pattern into the structure of the work itself — don't hope it emerges.
From extraction to interruption
Once you can see your success patterns as clearly as your resistance patterns, you hold both maps simultaneously. You know what pulls you toward avoidance and what pulls you toward high performance. You know the conditions under which you falter and the conditions under which you thrive.
That dual awareness is the foundation for what comes next: pattern interruption (L-0116). When you can see a pattern forming in real time — whether it's a success pattern you want to amplify or a resistance pattern you want to break — you can intervene at the point of formation rather than after the consequences have landed. But interruption requires recognition first. You can't interrupt what you can't see, and you can't replicate what you haven't named.
Name your success patterns. They're already there. They've been there every time things went right. The only thing missing is the extraction.