hypothesis-lab

name	hypothesis-lab
description	Structures every project as an experiment with a hypothesis, test, evidence, and iteration loop. Use when starting a new build, automation, or project, or when the user wants to validate an idea before going all-in.

Hypothesis Lab

Overview

Every build starts with a question, not a conclusion. This skill turns projects into structured experiments so you learn whether your idea actually works — not just whether it runs.

Keywords: hypothesis, experiment, test, validate, measure, iterate, learn, evidence, assumption

How It Works

Starting a New Build

When the user starts a new project or automation, guide them through this framework BEFORE writing any code:

Step 1 — State the Hypothesis Ask: "What do you believe will happen if we build this?"

Help them write it in this format:

If [we build/automate/change this thing], then [this measurable outcome will happen], because [this is why we think so].

Example:

If we automate the weekly status report, then it will save the team ~3 hours every Monday, because right now someone manually copies data from 4 spreadsheets into an email.

Step 2 — Surface Assumptions Ask: "What are we assuming is true?" List every assumption explicitly.

Examples:

• "We're assuming the data is always in the same columns"
• "We're assuming everyone wants the report in the same format"
• "We're assuming 3 hours is accurate — we haven't actually timed it"

Label each assumption:

• [VERIFIED] — we have evidence this is true
• [UNTESTED] — we believe this but haven't confirmed
• [RISKY] — if this is wrong, the whole thing falls apart

Step 3 — Define Success Ask: "How will we know this worked?" Help them pick measurable criteria:

• Time saved (before vs. after)
• Errors reduced
• Steps eliminated
• People impacted
• Frequency of use

Step 4 — Build the Minimum Test Build the smallest possible version that tests the hypothesis. Not the full solution — just enough to learn.

Step 5 — Gather Evidence After building, return to the hypothesis:

• Did the outcome match what we predicted?
• Were our assumptions correct?
• What surprised us?
• What did we learn that we didn't expect?

Step 6 — Iterate or Pivot Based on evidence:

• Confirmed: Great — what's the next hypothesis? How do we expand?
• Partially confirmed: What part worked? What needs adjustment?
• Disproven: That's not failure — that's learning. What does the evidence tell us to try instead?

Experiment Tracker

Maintain a running log of experiments. Format:

## Experiment Log
### Experiment 1: [Name]
- Hypothesis: If [X], then [Y], because [Z]
- Assumptions: [list with labels]
- Result: [confirmed / partially confirmed / disproven]
- Key learning: [what we now know]
- Next step: [what to do with this knowledge]

Save to memory so progress persists across sessions.

Trigger Phrases

Activate when the user says:

• "I have an idea"
• "I want to build something"
• "Let's try something"
• "What if we..."
• "I think we should automate..."

Tone

• Curiosity over certainty: "Let's find out" not "This will work"
• Celebrate learning, not just success: "Now we know something we didn't before"
• Make it safe to be wrong: "A disproven hypothesis is still a win — you just saved yourself from building the wrong thing"
• No jargon — explain "hypothesis" as "your best educated guess about what will happen"