Science

Two Modes

Mode 1: Quick Diagnosis (Under 15 Minutes)

Use when stuck, when intuition fails, or when you are about to "try random stuff."

Step 1: State your goal (30 seconds) One sentence. What does "fixed" look like?

GOAL: [What will be true when this is solved?]

Step 2: Generate hypotheses (60 seconds) MINIMUM THREE. If you cannot think of three, you have not thought hard enough.

H1: [Most likely cause] - because [evidence/reasoning]
H2: [Second possibility] - because [evidence/reasoning]
H3: [Third possibility] - because [evidence/reasoning]

For each, ask: "What would prove this WRONG?"

Step 3: Rank and test (60 seconds) Order by: (Fastest to verify) x (Most likely). Test the top one.

Step 4: Update and iterate (30 seconds)

• Hypothesis confirmed --> Fix it, done
• Hypothesis refuted --> Move to next hypothesis
• Inconclusive --> Need more data, design better test

One-Liner Version: "I think [X] because [Y]. If I am wrong, [Z] would be true. Let me check [Z]."

Exit Criteria: Problem solved, or 15 minutes elapsed without resolution --> escalate to Structured Investigation.

Mode 2: Structured Investigation (Hours to Days)

Use when Quick Diagnosis is not enough, multiple systems are involved, or stakes are high.

Phase 1: Define the Goal -- Specific outcome, measurable success criteria, constraints, and anti-goals (what you are NOT trying to do). Quality check: Can someone else read this and know exactly when you have succeeded?

Phase 2: Gather Context -- What we know (with sources), what we do not know, what has been tried, baseline measurements. Quality check: Did you look for disconfirming evidence?

Phase 3: Generate Hypotheses -- Minimum 3, better 5-10 for important problems. Each needs: claim, rationale, evidence for/against, falsification criteria ("WRONG if..."), cost to test, confidence level. Single-hypothesis thinking leads to confirmation bias.

Phase 4: Design Experiments -- Minimum Viable Experiments (smallest test that gives meaningful data). For each: method, what you are measuring, success/refutation/inconclusive criteria, duration. Prioritize by (likelihood) x (cost to test).

Phase 5: Execute and Measure -- Run experiments, collect data, do not peek prematurely. Record metrics as Expected vs. Actual vs. Delta.

Phase 6: Analyze Against Goal -- Compare results to pre-defined success criteria. Determine hypothesis status (CONFIRMED / REFUTED / INCONCLUSIVE). Capture key learnings, surprises, and new questions.

Phase 7: Iterate -- Goal achieved: document and done. Promising hypothesis: go deeper. All failed: generate new hypotheses. Need more data: design more experiments. Problem reframed: return to Phase 1.

Output Format

## Investigation Report: [Problem]

**Goal:** [What we were trying to achieve]
**Mode:** [Quick Diagnosis / Structured Investigation]

### Hypotheses Tested
| ID | Hypothesis | Verdict | Confidence |
|----|-----------|---------|------------|
| H1 | [Claim] | CONFIRMED/REFUTED | High/Med/Low |
| H2 | [Claim] | CONFIRMED/REFUTED | High/Med/Low |

### Key Finding
[One sentence: what we discovered]

### Evidence
[Data supporting the finding]

### Resolution
[What we did / what we recommend]

### Learnings
- [Generalizable insight 1]
- [Generalizable insight 2]

Key Principles

1. Goal-First -- Define success before starting
2. Hypothesis Plurality -- NEVER just one idea (minimum 3)
3. Minimum Viable Experiments -- Smallest test that teaches
4. Falsifiability -- Experiments must be able to fail
5. Measure What Matters -- Only goal-relevant data
6. Honest Analysis -- Compare to goal, not expectations
7. Rapid Iteration -- Cycle speed matters more than perfect experiments

Scale of Application

Anti-Patterns

Quick Reference

1. Goal -- What does success look like?
2. Observe -- What do we know?
3. Hypothesize -- At least 3 ideas
4. Experiment -- Minimum viable tests
5. Measure -- Collect goal-relevant data
6. Analyze -- Compare to success criteria
7. Iterate -- Adjust and repeat

The answer emerges from the cycle, not from guessing.