Run a Product Discovery Sprint with Claude

I want to map the competitive landscape for [product idea or market space].

My product solves: [one sentence — the job to be done, not the feature]
Users I'm targeting: [describe who and what they're trying to accomplish]

Map the market for me:
1. Direct competitors: solving the same problem the same way
2. Indirect competitors and substitutes: different solution, same job
3. For each: what they do well, what users complain about in reviews or forums, and which user segment they seem to be ignoring
4. The gap: where do user needs cluster that no current solution owns? Be specific — "underserved SMBs" is not a gap, "SMBs who need X but can't afford Y's minimum contract" is

Label anything you're inferring rather than citing. I'd rather know the confidence level than get a clean-looking analysis that's partly fabricated.

I'm building [product/feature description]. Before I design anything, I want to map and rank my assumptions.

Here's my current thinking: [describe the product concept and what you believe to be true about users, the market, and your solution]

Use Teresa Torres's 8 risk categories to help me map my assumptions:
- Desirability: do users actually want this?
- Viability: can our business support this?
- Feasibility: can we build this with our current team?
- Usability: can users use it without training?
- Ethical: should we build this?
- Safety: could this cause harm?
- Legal: are there compliance or IP concerns?
- Data privacy: what data do we need and how are we protecting it?

For each assumption I'm making (explicit or implied):
1. Which risk category it falls in
2. How confident I seem to be (high/medium/low, based on what I've told you)
3. What evidence would move that confidence rating

Organize the output as a priority list: high-risk assumptions with low confidence first. Those are the ones I need to test before I build anything.

Also: flag any assumptions I seem to be making that I haven't stated explicitly.

I want to design an experiment to test my riskiest assumption.

The assumption: [paste the #1 item from your assumption map]
Why it's risky: [what happens to the product if this assumption is wrong?]

Help me design a test using this structure:

**Hypothesis:** "We believe [specific thing] will result in [outcome] for [user group]. We'll know we're right when [specific measurable signal]."

**What we're testing:** The smallest version of the idea that would give us real signal. Not a prototype of the product. A test of the assumption.

**How we'll run it:** Method (interview, smoke test, concierge, fake door, etc.), sample, and timeframe.

**Success criteria:** What result would tell us to proceed? Be specific — percentages, counts, or quotes that would meet the bar.

**Kill criteria:** What result would tell us to stop or change direction? Equally specific.

**What we are NOT testing:** An explicit scope constraint so we don't over-build the test.

Keep the test as small as possible. The goal is a decision, not a launch.

I'm doing discovery for a new feature in an existing product, not a greenfield idea.

Product context: [describe your existing product, user base, and business model]
The feature hypothesis: [what you're considering adding and why]
What we know from existing users: [any signals from support, NPS, user research you already have]

Instead of a full competitive analysis, help me:
1. Identify which users in our existing base would benefit most from this feature
2. Map the assumptions specific to adding this to an existing product (adoption, cannibalization, integration complexity)
3. Identify what we already know from our user base that reduces our uncertainty on key assumptions
4. Suggest the experiment that would resolve the biggest unknown we can't answer from existing data

I have 2 hours to do as much discovery as possible before a decision meeting.

The decision: [what needs to be decided and when]
What I know so far: [current state of thinking]

Given the time constraint, help me run a triage version of the three-part discovery sprint:
1. Competitive analysis: skip depth, focus on — is there anyone doing this that we've missed, and what's the one gap most worth naming?
2. Assumption mapping: skip the full 8-category breakdown, just identify the 2 to 3 assumptions that, if wrong, would make this not worth building
3. Experiment design: design one lightweight test I could run in under a week that would resolve the most dangerous assumption

At the end, tell me: based on what I've shared, what's the one question I most need to answer before this meeting?

I built [product/feature description]. Here's what happened: [describe the response — usage data, user feedback, what's not working].

I need to do a retrospective discovery sprint to understand what I got wrong.

Help me:
1. Map the assumptions I was making when I built this (reconstruct them from what I can tell you about the original decisions)
2. Which ones turned out to be false, based on the evidence I've shared
3. What user need actually exists that my product is close to but not quite hitting
4. Whether I should pivot (change the solution), reframe (change the problem I'm solving), or stop

Be honest about what the data suggests, even if it contradicts what I want to hear.