Startup Design

Startup Design

A structured, multi-phase skill that takes a startup idea from raw concept to validated design. It produces a complete set of markdown documents organized by domain, with built-in progress tracking so work survives session interruptions.

How It Works

The process has 8 numbered phases executed sequentially, plus a Pre-Flight Check (Phase 0.5) and a Customer Discovery gate (Phase 3.7). Each phase produces output files and updates the progress tracker. If a session is interrupted, resume from the last completed checkpoint.

PRE-FLIGHT → INTAKE → BRAINSTORM → RESEARCH → [Research Gate] → CUSTOMER DISCOVERY → [Interview Gate] → STRATEGY → BRAND → PRODUCT → FINANCIAL → VALIDATION

Modes

Full Mode (default): Execute all phases in order, including Pre-Flight and Customer Discovery. Best for thoroughly designing a startup from scratch.

Fast Track Mode: When the user says they want a "quick validation," "rapid assessment," or similar, or when time/budget is clearly limited, run a compressed version: 1. Phase 0.5 (Pre-Flight Check) — always run, takes 5 minutes 2. Phase 1 (Intake) — shortened to 1 round of questions; capture any prior customer conversations 3. Phase 2 (Brainstorm) — 3 variations instead of 5-8 4. Phase 3 (Research) — Wave 1 + Wave 2 only (skip customer voice and distribution deep-dives) 5. Phase 3.5 (Research Gate) — go/no-go checkpoint 6. Phase 3.7 (Customer Discovery) — if founder has 5+ prior conversations, document them; if not, run at least 3 interviews before proceeding 7. Phase 4 (Strategy) — Lean Canvas only 8. Skip Phase 5 (Brand) and Phase 6 (Product) 9. Phase 7 (Financial) — Revenue model only, Stage A (assumption-based), no full projections 10. Phase 8 (Validation) — Scorecard + top 3 experiments only

Fast Track produces fewer files but still gives the founder a clear go/no-go signal with evidence. Note in PROGRESS.md that Fast Track mode was used, so a future session can expand to full mode if the idea passes validation.

Language

Default output language is English. If the user writes in another language or explicitly requests one, use that language for all outputs instead.

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Reference: Read references/output-guidelines.md once at the start. It defines the standard file header/footer (title, date, phase, confidence, flags), cross-phase referencing format, quality examples of good vs. bad output, and how to handle mid-process pivots.

Phase 0: Resume Check

Before anything else, check if a PROGRESS.md file exists in the working directory (or a project subdirectory). If it does, read it and resume from the last incomplete phase. Tell the user: "I found progress from a previous session. You completed [phases]. Picking up from [next phase]."

If no progress file exists, start from Phase 1.

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Phase 0.5: Pre-Flight Check

Before investing time in the full process, run a fast sanity check — 2-3 targeted searches, 5 minutes maximum. The goal is to surface any immediately disqualifying signals so the founder knows them upfront.

Run these three checks:

1. Dominant solution check — Does a well-funded, widely-adopted solution to this exact problem already exist? Search: "{problem domain} software", "{problem} tool site:producthunt.com", "{problem} app reviews". If a clear market leader with 10k+ customers exists, flag it immediately — this is not a reason to stop, but the founder needs to know the competitive reality before starting.

2. Precedent failure check — Has a company tried this exact idea and failed publicly? Search: "{startup idea} startup failed", "{problem} startup shutdown", "why {product category} failed". Prior failures are not disqualifying — they're learnings. But unknown prior failures are landmines.

3. Regulatory/legal instant kill — Is there an obvious legal reason this idea cannot exist? (E.g., specific financial regulations, data privacy laws in the target geography, licensing requirements.) A quick search prevents building toward a wall.

Output: A short message to the founder (3-5 bullet points max) with what was found. Use this format:

## Pre-Flight Check

✅ No dominant incumbent found — space appears open.
⚠️  [CompanyX] tried a similar approach in 2021 and shut down in 2023.
    Key reason: [one sentence]. Worth understanding before proceeding.
✅ No obvious regulatory blockers identified for [target market].

→ Ready to proceed to intake. The above is context, not a verdict.

Keep it brief. This is a heads-up, not a full analysis. The project directory and PROGRESS.md don't exist yet at this point — present the findings in the conversation, then save them to {project-name}/00-intake/preflight.md during the Phase 1 output step, once the project directory is created.

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Phase 1: Intake Interview

The quality of everything downstream depends on how much context you extract now. Don't rush this — a thorough intake saves hours of misdirection later.

Reference: Read references/intake-questions.md for the full question set (idea, founders, market, business, constraints), the hard questions that surface blind spots, and interviewing technique.

Cover all five question areas plus the hard questions — they set the tone for the entire process and signal that this is an honest assessment, not a cheerleading session. Ask 3-5 questions at a time in a conversational flow, probe vague answers, and after 2-3 rounds summarize what you've understood and ask the user to confirm or correct.

Output

Save the consolidated intake to {project-name}/00-intake/brief.md with all captured information organized clearly. The project name should be derived from the startup idea (kebab-case, e.g., pet-health-tracker).

Create PROGRESS.md at the project root with: project name, start date, language, a checklist of all phases including Pre-Flight (0.5) and Customer Discovery (3.7) — mark Pre-Flight and Phase 1 complete — and a Notes section for session state. Also save the Pre-Flight findings from Phase 0.5 to 00-intake/preflight.md now that the directory exists.

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Phase 2: Brainstorm

Before diving into research, explore the idea space. This prevents premature convergence on the first version of the idea.

Process

1. Diverge — Generate 5-8 variations of the core idea. Push boundaries:

• What if the target market was completely different?
• What if the business model was inverted?
• What if you solved a smaller/larger version of the problem?
• What adjacent problems could you solve instead?
• What would the "10x version" look like vs. the "simplest possible version"?

2. Analyze — For each variation, note:

• What's exciting about it
• What's risky or hard
• How it changes the competitive landscape

3. Converge — Present the variations to the user. Help them identify which elements resonate. The goal isn't to pick one variation — it's to enrich the original idea with insights from the exploration.

4. Refine — Based on the user's reactions, crystallize the refined idea. Update the brief if the idea evolved significantly.

Output

Save to {project-name}/00-intake/brainstorm.md. Update PROGRESS.md.

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Phase 2.5: Research Depth Assessment

After intake (and brainstorm if applicable), assess market complexity and present the Research Depth recommendation to the user.

Reference: Read references/research-scaling.md for the complexity scoring matrix, tier definitions, wave configurations, and the user communication template.

Process

1. Score three factors from the intake: market breadth (1-3), known competitors (1-3), geographic scope (1-3) 2. Sum the scores (range 3-9) and map to a tier: Light (3-4), Standard (5-7), Deep (8-9) 3. Present the Research Depth table to the user (see research-scaling.md for the exact template) 4. Wait for user response: light, deep, or ok to accept the recommendation 5. Record the selected tier in PROGRESS.md

The selected tier determines the number of agents per wave and search rounds per agent in Phase 3. See research-scaling.md for exact wave configurations per tier.

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Phase 3: Market Research

This is the most resource-intensive phase. It uses 4 sequential waves of web research, each building on the previous one's findings.

Environment Detection

Check if the Agent tool is available (Claude Code) or not (Claude.ai, other environments):

• Agent tool available: Spawn subagents in parallel within each wave, as described below. This is faster (~3-5 min per wave).
• Agent tool NOT available (Claude.ai, web): Execute the research yourself, sequentially. For each wave, follow the same agent templates from the reference files, but run the searches one at a time in the main conversation. Cover the same topics and apply the same research principles — the output quality should be identical, it just takes longer. Do NOT skip any wave or reduce search depth because of the sequential mode.

Web Search Availability

Phase 3 requires WebSearch. In Claude Code, the tool is always available — if the user hasn't pre-approved it, the system will prompt them for each search. If the user denies permission, or in environments where WebSearch doesn't exist at all, fall back to Knowledge-Based Research Mode: use your training data, clearly mark all findings with [Knowledge-Based — not live data, verify independently], reduce confidence ratings by one level, and recommend the founder verify key claims manually. Note the mode in PROGRESS.md so future sessions know the research wasn't web-sourced.

References — Read the relevant file for each wave:

- references/research-principles.md — Cross-cutting rules (source quality, cross-referencing, quantification, handling search failures). Read this FIRST.

- references/research-wave-1-market.md — Agent templates for Wave 1 (market sizing, trends, regulatory)

- references/research-wave-2-competitors.md — Agent templates for Wave 2 (direct, indirect, GTM analysis)

- references/research-wave-3-customers.md — Agent templates for Wave 3 (customer voice, demand, audience)

- references/research-wave-4-distribution.md — Agent templates for Wave 4 (channels, geographic entry)

- references/research-synthesis.md — How to synthesize raw findings into final deliverables

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Read only the principles file + the wave file you're currently executing. Don't load all wave files at once.

Research Principles

• Each agent performs 5-8 web searches minimum, drilling deeper with each round
• Cross-reference every key finding across 2-3 independent sources
• Rate source quality (Tier 1: analyst reports, Tier 2: tech press, Tier 3: blogs/social)
• Quantify everything — "$4.2B at 12.3% CAGR" not "the market is growing"
• Date all data and flag anything older than 18 months
• Note contradictions between sources rather than picking one

Research Waves

Full agent briefs, search strategies, and output destinations live in the wave reference files — read the relevant file when spawning each wave:

• Wave 1: Market Landscape (3 agents) — A1 Market Sizing & Economics, A2 Industry Trends & Timing, A3 Regulatory & Compliance (skip A3 if no regulatory exposure)
• Wave 2: Competitive Analysis (3 agents) — B1 Direct Competitor Deep-Dives, B2 Indirect Competitors & Substitutes, B3 Competitor Go-to-Market
• Wave 3: Customer & Demand (3 agents) — C1 Customer Voice & Pain Points, C2 Demand Signals & Market Validation, C3 Target Audience Profiling
• Wave 4: Distribution & Partnerships (2 agents) — D1 Distribution Channels, D2 Geographic & Market Entry

Each wave must complete before the next starts. Pass key findings forward as context (Wave 1 findings to Wave 2 agents, competitor list and GTM findings to Wave 3, and so on). Agents run in parallel within a wave, or as sequential research blocks without the Agent tool.

Raw → Synthesized

All agents save raw findings to {project-name}/01-discovery/raw/. After all waves complete, synthesize into 4 polished deliverables.

Synthesis is reasoning, not formatting — it's where the raw research becomes a decision. Before writing anything, think hard about how the pieces fit together: which sources conflict and which to trust, what the evidence actually supports versus what the founder hopes, and what it all means for this specific startup. This is the highest-leverage thinking in the whole process and every downstream phase inherits its quality, so if the model supports extended thinking, this is the place to spend it. A weak synthesis produces a tidy document that restates the inputs; a strong one reaches the non-obvious conclusions a sharp analyst would draw from the same evidence.

The synthesis must:

• Connect dots across research areas (competitive gaps → customer pains → positioning opportunities)
• Highlight contradictions and explain which data to trust
• Rate confidence for each major claim (High / Medium / Low)
• Extract explicit strategic implications, not just facts

Output Files

• {project-name}/01-discovery/market-analysis.md — Market size (TAM/SAM/SOM), growth, maturity, regulatory summary, timing assessment
• {project-name}/01-discovery/competitor-landscape.md — Competitor profiles, structured comparison matrix (table with columns: Name, Product, Pricing, Target, Funding, Traction, Key Strength, Key Weakness), positioning map, platform risk, vulnerability analysis
• {project-name}/01-discovery/target-audience.md — Persona(s), pain hierarchy, jobs-to-be-done, language map, buying behavior, channels
• {project-name}/01-discovery/industry-trends.md — Tech trends, investment signals, behavioral shifts, regulatory trajectory, strategic implications
• {project-name}/01-discovery/confidence-dashboard.md — Summary of data quality across all research. For each major claim, list: the claim, source tier (1/2/3), number of corroborating sources, confidence level (High/Medium/Low), and data age. This tells the founder where they're standing on solid ground vs. thin ice.

Update PROGRESS.md.

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Phase 3.5a: Research Verification

After synthesis completes and all deliverable files are written, run a verification pass to catch inconsistencies.

Reference: Read references/verification-agent.md for the full verification protocol, universal checks, and skill-specific checks.

Process

1. Spawn agent V1: Verification — it reads all deliverable files in 01-discovery/ and checks for: unlabeled claims, internal contradictions, confidence rating consistency, missing data gaps, missing flags, stale data, and duplicate-source false corroboration 2. V1 also runs startup-design-specific checks: cross-phase consistency (strategy reflects market data, product reflects customer pains, financial reflects business model, validation covers identified risks) 3. V1 produces {project-name}/01-discovery/verification-report.md 4. If Critical issues found: Pause and present issues to the user. Ask: fix first, or proceed as-is? 5. If only Warnings/Info: Show one-line summary and continue to Research Gate

In Claude.ai or when Agent tool is unavailable, run the verification checks yourself in the main conversation following the same protocol.

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Phase 3.5: Research Gate (Go/No-Go Checkpoint)

Before investing time in Strategy through Validation, pause and present the founder with an honest assessment based on research findings. This is a decision point, not a formality.

Reason it through before writing the verdict. Weigh the strongest signals against the red flags rather than averaging them into a noncommittal "it depends" — one fatal flaw can outweigh five promising signals, and one exceptional signal can justify proceeding despite rough edges. The founder is about to spend real time and money on your read of the evidence, so think hard about what the data genuinely supports.

Present a brief summary: "Here's what the research found." Cover market size, competition intensity, customer demand signals, and timing. Then give a clear recommendation:

• Green light — Data supports proceeding. Note the strongest signals.
• Yellow light — Mixed signals. Specify what's concerning and what would need to be true for success.
• Red light — Data argues against this approach. Suggest pivots if the research revealed adjacent opportunities.

Ask the founder: "Based on this, do you want to continue to full strategy, pivot the idea, or stop here?" Respect their decision, but make sure it's an informed one. Save the gate assessment in {project-name}/01-discovery/research-gate.md.

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Phase 3.7: Customer Discovery (Interviews)

Research tells you what the market looks like from the outside. Customer interviews tell you what the problem feels like from the inside. This is the single highest-signal validation step in the entire process — and the only one that requires real calendar time (typically 1-2 weeks).

Reference: Read references/customer-interview.md for the full interview protocol, question structure, notes template, and synthesis guide.

When to run this phase

Run this phase after the Research Gate green- or yellow-lights the idea. If the gate returned a red light and the founder chose to stop, skip this phase.

Because interviews interrupt the session flow, present the founder with an explicit choice:

• Run interviews now (recommended) — pause here, conduct the interviews over the coming days, and resume from this checkpoint (PROGRESS.md preserves the state).
• Defer and continue — proceed to Strategy on research data alone. State the consequences plainly: financial projections stay Stage A (assumption-based), the Final Assessment Dashboard will show "Customer Interviews: 0 conducted · deferred", and interviews become the #1 experiment in the Phase 8 validation playbook. A strategy built without customer contact is a hypothesis, not a validated direction — say this honestly, then respect the founder's decision without nagging.

Exception — Fast Track Mode: If the founder reported 5+ prior customer conversations in intake, document those conversations using the interview template and proceed. Flag all claims as [Founder-reported]. If fewer than 5 conversations happened, recommend running fresh interviews — minimum 5 in Full Mode, minimum 3 in Fast Track.

Process

1. Identify who to interview — Using the primary persona from 01-discovery/target-audience.md, define the exact profile. 5 interviews minimum. 2. Conduct interviews — Follow the protocol in references/customer-interview.md. Aim for 25-30 minutes each, problem-focused, no product pitching. 3. Document each interview — Save to {project-name}/00-intake/interviews/interview-{N}.md using the template from the reference file. 4. Synthesize — After all interviews, write {project-name}/00-intake/interview-synthesis.md covering: problem confirmation rate, behavior signals (who paid/built workarounds), key phrases, and assumption audit.

Interview Gate: Proceed vs. Reassess

After synthesis, present a brief finding to the founder and apply this gate:

Proceed to Phase 4 if:

• 4+ of 5 interviewees confirm the core problem clearly and unprompted
• At least 2 show behavior signals (paid for something, built a workaround, actively searched)
• Problem language is consistent across interviews

Pause and reassess if:

• 3 or fewer of 5 confirm the problem (scale proportionally if more interviews were run)
• Everyone says "interesting" but no behavior signals exist
• The problem they describe doesn't match the proposed solution

Present the synthesis and gate result to the founder. If the result calls for reassessment, suggest specific pivots if the interviews pointed to an adjacent problem worth solving. Let the founder decide: pivot the idea, narrow the target, or stop.

Update PROGRESS.md with the interview gate result.

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Phase 4: Strategy

With research in hand, define the strategic foundations. Each document should reference specific findings from Phase 3 — strategy disconnected from research is just guessing.

References: Read references/frameworks.md for canonical definitions of Lean Canvas, April Dunford Positioning, Value Proposition Canvas, and RICE/MoSCoW. Read references/output-specs.md (Phase 4 section) for the required structure of each file.

Produce in 02-strategy/:

• lean-canvas.md — complete 9-block Lean Canvas
• value-proposition.md — value proposition canvas (jobs, pains, gains), one-sentence value prop, proof points
• business-model.md — revenue model, unit economics, scalability, dependencies and partnerships
• positioning.md — April Dunford's five components
• go-to-market.md — launch strategy, first 100 customers plan, ranked growth channels, milestones

Update PROGRESS.md.

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Phase 5: Brand

Checkpoint: Before starting, briefly present the strategy summary to the founder: positioning, target market, business model. Ask: "Does this reflect your vision? Anything to adjust before we build the brand on top of it?"

Translate strategy into brand identity. The brand should feel like a natural extension of the positioning — not an afterthought.

Reference: Read references/output-specs.md (Phase 5 section) for the required structure of each file.

Produce in 03-brand/:

• mission-vision-values.md — mission, vision, 3-5 working values; generate 2-3 options for the user to choose from or remix
• tone-of-voice.md — personality traits, voice principles with "we are / we are not" examples, writing samples, vocabulary guide
• brand-personality.md — brand archetype, emotional attributes, visual direction, how the brand should feel vs. competitors

Update PROGRESS.md.

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Phase 6: Product

Define the product enough to start building or to brief a development team. Use the competitor feature analysis from 01-discovery/competitor-landscape.md and customer pain hierarchy from 01-discovery/target-audience.md to inform feature decisions — don't design in a vacuum.

References: Use RICE or MoSCoW from references/frameworks.md for prioritization. Read references/output-specs.md (Phase 6 section) for the required structure of each file.

Produce in 04-product/:

• mvp-definition.md — core hypothesis, must-have features, nice-to-haves, explicit out-of-scope, success criteria
• feature-prioritization.md — RICE/MoSCoW list, dependencies, T-shirt effort estimates, build order
• user-journey.md — end-to-end journey map, touchpoints and emotions, drop-off risks, the "aha moment"

Update PROGRESS.md.

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Phase 7: Financial

Checkpoint: Before projections, confirm key assumptions with the founder: pricing, target customer volume, team size, timeline. These directly drive the numbers — getting them wrong here means the projections are fiction.

Ground the strategy in numbers. Be honest about assumptions — label everything as estimated and explain the reasoning. Pull unit economics benchmarks (CAC, LTV, churn, ACV) from 01-discovery/market-analysis.md and competitor pricing from 01-discovery/competitor-landscape.md to anchor projections in real data.

Reference: Read references/industry-benchmarks.md for standard metrics by business model type (SaaS, marketplace, e-commerce, etc.). Compare the founder's projections against these benchmarks and flag any that fall outside normal ranges — both too pessimistic and too optimistic.

Two-stage financial model

Financial projections at this point exist in one of two states depending on whether customer interviews (Phase 3.7) produced validated demand signals:

Stage A — Assumption-Based (default, pre-revenue validation): Used when no real traction data exists. Label every number clearly as [Assumption — unvalidated]. The purpose is to map the financial structure and identify which assumptions are most sensitive, not to produce reliable forecasts.

Stage B — Evidence-Based (if interview gate passed with strong behavior signals): Used when interviews confirmed willingness-to-pay, existing spend on workarounds, or pre-sales interest. Anchor projections to actual signals: "3/5 interviewees said they currently pay ~$200/month for a partial solution" is better data than a benchmark. Label these numbers as [Estimate — grounded in interview data].

At the top of every financial file, include a one-line stage declaration:

**Financial Model Stage:** A — Assumption-Based | All projections are hypotheses to be tested, not forecasts.

or

**Financial Model Stage:** B — Evidence-Based | Key assumptions anchored to {N} customer interviews.

Revenue Model

In 05-financial/revenue-model.md:

• Pricing strategy with rationale
• Revenue projections (Month 1-12, Year 1-3) with every assumption stated explicitly
• Sensitivity analysis: what happens if key assumptions change by ±30%
• For Stage A: clearly mark which assumptions need validation experiments before the model becomes reliable

Cost Structure

In 05-financial/cost-structure.md:

• Fixed costs (infrastructure, tools, salaries)
• Variable costs (per-user, per-transaction)
• One-time costs (development, legal, launch)
• Break-even analysis

Projections

In 05-financial/projections.md:

• 3 scenarios: conservative, base, optimistic
• Key assumptions for each scenario
• Cash flow timeline
• Funding needs and runway calculation
• Assumption sensitivity table: list the top 5 assumptions that, if wrong, would most change the projections. For each: current assumption, what happens if it's 50% worse, and how to validate it.

Update PROGRESS.md.

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Phase 8: Validation

This is the most actionable phase — it tells the founder exactly what to do next to test whether the idea works.

Reference: Read references/output-specs.md (Phase 8 section) for the required structure of each file.

Produce in 06-validation/:

• validation-playbook.md — experiments ordered cheapest-first, each with assumption tested, method, metrics, and pass/fail criteria; if interviews were deferred in Phase 3.7, they are experiment #1
• risk-analysis.md — likelihood × impact matrix across market, product, business, team, and financial risks, with mitigations and early warning signals
• assumptions-tracker.md — every critical assumption with confidence, test method, and status, as a table
• experiment-design.md — detailed design plus ready-to-use templates for the top 3 experiments
• kill-criteria.md — 5-7 specific, measurable stop/pivot conditions tied to experiments
• scorecard.md — 1-10 scores across 7 dimensions plus an unambiguous Verdict paragraph

Be honest. If the idea has weaknesses, say so clearly. The goal is to help the founder make a good decision, not to validate their ego.

Update PROGRESS.md — mark all phases complete.

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Final Deliverable

After all phases are complete, first print the Final Assessment Dashboard in the conversation (see references/output-guidelines.md, "Final Assessment Dashboard" section). This gives the founder an instant visual summary of all key findings before they dive into the files.

Then produce two final files:

`README.md` at the project root — executive summary:

• One-paragraph overview of the startup
• Key findings from research
• Strategic positioning summary
• Top 3 risks and how to mitigate them
• Confidence dashboard summary (what we know vs. what we're guessing)
• Links to all generated documents

`action-plan-30-days.md` — concrete weekly plan for the first month:

• Week 1: Customer discovery (who to contact, what to ask, how many conversations)
• Week 2: Validation experiments (which ones to run first, with specific steps)
• Week 3: MVP scoping (based on validation results, what to build/fake/skip)
• Week 4: Go/no-go decision and next phase planning
• Each week should have 3-5 specific, actionable tasks — not "do customer research" but "send 20 cold LinkedIn messages to [persona] using this template"

Anti-pattern check: Before finalizing, scan the entire output for common founder anti-patterns and flag any you detect: "solution looking for a problem," "boiling the ocean" (too many features/markets at once), "premature scaling," "vanity metrics," "building in stealth too long," "ignoring unit economics." Include a brief Anti-Patterns Detected section in the README if any are present.

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Radical Honesty Protocol

Reference: Read references/honesty-protocol.md at the start of every session for the full protocol. The key rules are summarized here.

This skill helps founders make good decisions, not feel good. Honesty is non-negotiable:

1. Tell the truth. If the market is too small or the idea has a fatal flaw, say so directly. Flag when founder assumptions contradict research data. 2. Label claims. Use [Data], [Estimate], [Assumption], [Opinion] tags. Never present estimates as facts. 3. Surface flags in every phase. Include a Red Flags / Yellow Flags section at the end of every phase output. 4. Clear verdict. Scorecard must recommend: 8-10 proceed, 6-7 conditional, 4-5 concerns, 1-3 stop/pivot. 5. Ground in evidence. No data? Say so. Don't fabricate. 6. Make it actionable. Every document tells the founder what to do next. 7. Track everything. Update PROGRESS.md after each phase.

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Reference Files

The references/ directory contains supporting documentation. Read only what you need for the current phase.

Customer Interview Protocol

Before building strategy, brand, or product, validate assumptions with real people. This document is read during Phase 3.7: Customer Discovery — between research synthesis and strategy.

The goal is not to confirm your idea. The goal is to find out if the problem you think exists actually exists, how painful it is, and whether the people who have it are willing to do something about it.

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Why interviews beat surveys (and AI research)

Web research tells you what people have already said publicly. Interviews tell you what they actually do, struggle with, and would pay for. The two are often different. A customer who writes a glowing review on G2 may use a tool for 5 minutes a month; one who complains on Reddit may be a daily power user desperate for something better. Only conversation reveals the difference.

Rule of thumb: 5 honest conversations beat 500 data points when you're trying to understand whether a problem is real and worth solving.

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Who to interview

Target people who match the persona identified in 01-discovery/target-audience.md. Be specific:

• Right: "B2B SaaS sales managers at 20-200 person companies who currently use a CRM"
• Wrong: "Anyone who might need this"

If the target-audience file identified multiple personas, start with the one most likely to be an early adopter — the person with the sharpest pain, not the broadest appeal.

Minimum viable sample: 5 interviews. Patterns start emerging at 5; beyond 12-15, you get diminishing returns at this stage.

How to find them:

• LinkedIn: search by role + industry + company size, message directly
• Reddit/Slack/Discord: communities where your target hangs out (surfaced in Wave 3 research)
• Warm network: founders, former colleagues, friends-of-friends who match the persona
• Twitter/X: people who complain about the problem in public

Incentives: 20-30 minutes of their time. Offer a gift card ($15-25) if the persona is hard to reach. Never pay for opinions on your product — it biases answers.

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The interview structure (25-30 minutes)

Opening (2 minutes)

"I'm researching how [persona type] handle [problem domain]. I'm not selling anything — I'm trying to understand the problem before building a solution. I'll ask you about your current experience. There are no right or wrong answers. Is it okay if I take notes?"

This framing removes social pressure to be nice about an idea you haven't mentioned yet.

Part 1: Context (5 minutes)

Understand their world before you ask about the problem.

• "Walk me through a typical week in your role. What takes up most of your time?"
• "What tools do you use for [relevant domain]?"
• "How long have you been doing this?"

Don't ask leading questions. Don't mention your solution. Listen for the words they use to describe their work — these become the language map for messaging later.

Part 2: The problem (10 minutes)

This is the core of the interview. Go deep.

• "Tell me about the last time you had to deal with [problem domain]. Walk me through what happened."
• "How often does this come up?"
• "What do you do today to handle it?"
• "What's the most frustrating part of that process?"
• "What have you tried? What didn't work?"
• "If you could wave a magic wand and fix one thing about this, what would it be?"

Do NOT ask hypotheticals like "would you use a tool that..." — hypothetical answers are worthless. People are notoriously bad at predicting their own behavior. Stick to past behavior and current workarounds.

Part 3: Behavior signals (8 minutes)

• "Have you ever paid for something to solve this? What, and how much?"
• "Have you ever built a workaround yourself — a spreadsheet, a script, anything custom?"
• "Have you looked for a solution? What did you find? Why didn't it work?"
• "Who else in your organization deals with this problem?"

Paying, building workarounds, or actively searching are the strongest signals. Someone who "would theoretically be interested" is not a customer. Someone who already pays for an imperfect solution is.

Part 4: Wrap-up (3 minutes)

• "Is there anything about this I didn't ask that you think is important?"
• "Is there anyone else you'd recommend I talk to who has this problem?"
• "Would it be okay if I followed up with a quick question later?"

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How to listen

The Mom Test rule (Rob Fitzpatrick): People will not tell you your idea is bad because they don't want to hurt your feelings. They'll say "that's interesting" and "I could see that being useful." These phrases mean nothing. Anchor to behavior, not opinion.

• Watch for energy: does their voice change when they describe the problem? Frustration = real pain.
• Watch for specificity: "sometimes it's annoying" vs. "last Tuesday I spent 3 hours fixing this manually and still got it wrong." The second is a real problem.
• Watch for volunteered solutions: if they tell you what they wish existed without you asking, pay close attention.
• Watch for workarounds: any system, hack, or manual process they've built is evidence the problem is real and unsolved.

---

After each interview: notes template

Save each interview summary to {project-name}/00-intake/interviews/interview-{N}.md:

# Customer Interview {N}

**Date:** {date}
**Interviewee:** {role, company size, industry} — do NOT record name unless consented
**Duration:** {minutes}

## Context
{2-3 sentences about their role and world}

## Problem signals
- {Quote or paraphrase of key pain expressed}
- {Quote or paraphrase}

## Current solution/workaround
{What they do today. Is it paid? Self-built? Manual?}

## Behavior signals
- [ ] Currently pays for a solution (what, how much: {details})
- [ ] Has built a workaround themselves ({details})
- [ ] Has actively searched for alternatives ({details})
- [ ] Has complained publicly about this ({details})

## Key phrases (use their exact words)
- "{exact quote}"
- "{exact quote}"

## Surprises or unexpected findings
{Anything that contradicted your assumptions}

## Follow-up
- [ ] Okay to follow up: {yes/no}
- [ ] Referred me to: {details or none}

---

Synthesis: what to look for across interviews

After 5+ interviews, look for patterns in {project-name}/00-intake/interview-synthesis.md:

Problem validation:

• Do at least 4 of 5 interviewees describe the same core problem unprompted? (the Interview Gate threshold)
• Do they use similar language to describe it?
• Is the pain acute (happens often, costs time/money/stress) or mild (annoying but ignorable)?

Demand signals:

• Has anyone already paid for a partial solution?
• Has anyone built a workaround?
• Did anyone ask "when can I try it?" without being prompted?

Assumption audit: Update the assumptions tracker in 06-validation/assumptions-tracker.md. For each assumption the intake generated, note: Confirmed, Contradicted, or Unclear.

Red flags from interviews:

• 3 or fewer of 5 confirm the problem exists → the problem may be invented, not discovered
• Nobody has paid for anything related → willingness-to-pay is unproven
• All interviewees say "I'd use it" but nobody has ever tried to solve it → low urgency
• The problem they describe is different from the one you designed for → pivot needed

---

When to proceed vs. when to stop

Proceed to Phase 4 (Strategy) if:

• 4+ of 5 interviewees confirm the problem clearly and unprompted
• At least 2 have paid for a related solution or built a workaround
• The problem language is consistent across interviews (sign that it's a real, shared pain)

Pause and reassess if:

• 3 or fewer of 5 confirm the problem
• Everyone says "interesting" but nobody has ever tried to solve it
• The problem they describe doesn't match your proposed solution

Document the outcome in {project-name}/00-intake/interview-synthesis.md and update PROGRESS.md. If the interviews surface a significant pivot, trigger the pivot protocol from output-guidelines.md.

---

Fast Track mode

If the founder has already spoken to 5+ potential customers before starting this process:

1. Ask: "Can you summarize what you heard? Key pains, exact quotes if you remember them, and whether anyone had already paid for something." 2. Document their answers in interview-synthesis.md directly. 3. Flag that interviews are founder-reported, not independently conducted: add [Founder-reported — verify independently] to any claims derived from this. 4. Skip the interview structure above and proceed to Phase 4.

If the founder has spoken to fewer than 5 people, recommend running fresh interviews — minimum 5 in Full Mode, minimum 3 in Fast Track. Document any prior conversations as [Founder-reported] context anyway.

Strategic Frameworks Reference

Use this document when applying frameworks during Phase 4 (Strategy) and Phase 8 (Validation). These are the canonical definitions — follow them to ensure consistency.

---

Lean Canvas (Ash Maurya)

A 1-page business model adapted from the Business Model Canvas for startups. Fill in this order for best results:

1. Problem — Top 3 problems your customers have. List existing alternatives for each. 2. Customer Segments — Target customers. Identify early adopters separately. 3. Unique Value Proposition — Single, clear, compelling message that turns an unaware visitor into an interested prospect. Follow the formula: "We help [customer] [solve problem] by [mechanism]." 4. Solution — Top 3 features that address the top 3 problems. Keep it minimal. 5. Channels — Path to customers. Distinguish between inbound (SEO, content, referrals) and outbound (ads, sales, partnerships). 6. Revenue Streams — Revenue model, pricing, lifetime value, gross margin. 7. Cost Structure — Customer acquisition costs, distribution costs, hosting, people, etc. 8. Key Metrics — The 3-5 numbers that tell you how the business is doing. Use the pirate metrics framework (AARRR): Acquisition, Activation, Retention, Revenue, Referral. 9. Unfair Advantage — Something that cannot be easily copied or bought. Examples: insider knowledge, personal authority, community, network effects, proprietary data, existing platform.

---

April Dunford's Positioning Framework

From "Obviously Awesome." Positioning defines how your product is the best in the world at providing something that a well-defined set of customers cares a lot about.

The 5 components (work through in this order):

1. Competitive Alternatives — What would customers do if your solution didn't exist? Not just direct competitors — include manual processes, spreadsheets, hiring someone, doing nothing. This grounds the positioning in reality.

2. Unique Attributes — What do you have that the alternatives don't? Be specific and factual. Not "better UX" but "drag-and-drop workflow builder that requires zero code." Capabilities, features, expertise, integrations, data, speed, etc.

3. Value — What do those attributes enable for the customer? Map each attribute to a customer benefit. Attributes are features; value is the outcome. "Drag-and-drop builder" → "Non-technical teams can build workflows without waiting for engineering."

4. Target Customer — Who cares the most about this value? The best customers are those for whom your unique value is critical, not just nice-to-have. Define by characteristics that make them care more than others.

5. Market Category — The context you position your product in so the value is obvious. Three options:

• Existing category: You're a better version of something people already buy (e.g., "CRM for real estate agents")
• New sub-category: You take an existing category and add a qualifier (e.g., "AI-powered recruiting platform")
• New category: Rare and expensive to do. Only if nothing else frames your value well.

---

Value Proposition Canvas (Strategyzer)

Two sides that must fit together:

Customer Profile (right side)

• Jobs-to-be-done — What the customer is trying to accomplish. Include functional jobs (tasks), social jobs (how they want to be perceived), and emotional jobs (how they want to feel).
• Pains — What annoys, frustrates, or blocks them before, during, or after getting a job done. Include risks, undesired outcomes, and obstacles.
• Gains — What outcomes and benefits customers want. Include required gains (must-haves), expected gains (standard), desired gains (nice-to-have), and unexpected gains (delighters).

Value Map (left side)

• Products & Services — What you offer (features, services, support).
• Pain Relievers — How your offering alleviates specific customer pains. Map each to a specific pain.
• Gain Creators — How your offering creates specific customer gains. Map each to a specific gain.

Fit exists when your pain relievers and gain creators match the most important pains and gains.

---

RICE Prioritization (Intercom)

Score features to decide build order. Each feature gets four scores:

• Reach — How many customers will this affect per quarter? Use a concrete number (e.g., 500 users/quarter).
• Impact — How much will this move the needle for each person reached? Score: 3 = massive, 2 = high, 1 = medium, 0.5 = low, 0.25 = minimal.
• Confidence — How sure are you about reach and impact estimates? Score: 100% = high confidence (data-backed), 80% = medium, 50% = low (gut feel).
• Effort — How many person-months will this take? Higher effort = lower priority.

Formula: RICE = (Reach × Impact × Confidence) / Effort

Sort features by RICE score descending. The highest scores should be built first.

---

MoSCoW Prioritization

Simpler alternative to RICE. Categorize every feature into one bucket:

• Must have — Without these, the product doesn't solve the core problem. Non-negotiable for MVP.
• Should have — Important but not critical. The product works without them, but it's notably weaker.
• Could have — Nice to have. Include if time/budget allows, but cut first when scope is tight.
• Won't have (this time) — Explicitly out of scope. Important to name these to prevent scope creep.

---

Risk Matrix

Used in Phase 8 (Validation) for risk analysis. Plot each risk on two axes:

Likelihood: How probable is this risk?

• High (>60% chance)
• Medium (20-60%)
• Low (<20%)

Impact: If it happens, how bad is it?

• Critical — Business fails or pivots required
• Major — Significant delay or revenue loss
• Moderate — Manageable but painful
• Minor — Inconvenience, easily absorbed

Priority quadrants: 1. High likelihood + Critical/Major impact → Address immediately, design mitigation 2. Low likelihood + Critical impact → Monitor, have contingency plan 3. High likelihood + Minor impact → Accept and manage 4. Low likelihood + Minor impact → Acknowledge and move on

Radical Honesty Protocol

This skill exists to help founders make good decisions — not to feel good. An AI that cheerleads every idea is actively harmful: it wastes the founder's time, money, and emotional energy. These principles are non-negotiable and apply to every phase.

Tell the truth, even when it's uncomfortable

• If the market is too small, say so directly. Don't soften "$12M and shrinking" into "room for a focused player."
• If the idea has a fatal flaw, name it up front. Don't bury it in a list of minor risks.
• If the founder's assumptions contradict research, flag it explicitly: "You assumed X, but the data shows Y."
• Challenge "everyone needs this" (who specifically?), "there's no competition" (there's always competition, even if it's doing nothing), and unsupported market claims.
• Never use vague positive language to avoid delivering bad news. Replace "interesting opportunity" with the specific finding.

Separate facts from opinions

• Label every major claim with its basis:
• [Data] — sourced finding with citation
• [Estimate] — calculated projection with stated assumptions
• [Assumption] — unverified belief that needs testing
• [Opinion] — your analytical judgment
• When data is missing or weak, say so: "I couldn't find reliable market size data for this niche. The $X figure comes from a single blog post and should be treated with low confidence."
• Never present estimates as facts. "Revenue could reach $500K in Year 1 assuming 2% conversion and $50 ARPU" — not "Revenue will reach $500K."
• A confident-sounding fabrication is worse than an honest "I don't know."

Surface flags proactively

In every phase output (not just validation), include a Flags section at the end:

• Red Flags — Issues that could kill the business. Examples: market too small to sustain a venture-scale company, dominant incumbent with network effects, regulatory ban likely, unit economics that don't work even optimistically.
• Yellow Flags — Concerns that need investigation or mitigation. Examples: high CAC in a low-LTV market, founder has no domain expertise, solution requires behavior change, crowded market with low differentiation.

If there are no flags for a phase, write "No flags identified" — don't skip the section, because its absence might look like an oversight.

Challenge the founder's assumptions

Don't just accept what the user says at face value. Throughout the process:

• Ask "What evidence do you have for that?" when the founder makes market claims
• Push back on "everyone needs this" — who specifically, and how do you know?
• Question "there's no competition" — there's always competition, even if it's doing nothing
• When the founder is emotionally attached to a feature or positioning, note it and test it against data

Provide a clear verdict

The scorecard in Phase 8 must include an unambiguous recommendation:

• Score 8-10: Strong signal to proceed. Explain what makes this compelling.
• Score 6-7: Conditional proceed. List the specific conditions that must be validated before investing serious resources.
• Score 4-5: Significant concerns. The founder should run validation experiments before committing. Be specific about what would need to change.
• Score 1-3: Recommend against proceeding in current form. Explain why honestly and suggest pivot directions if any show promise.

Never leave the founder wondering "so... should I do this or not?"

Anti-patterns to watch for

Flag these common founder mistakes whenever you detect them:

Ground rules

• Ground in evidence. Every strategy/brand/product claim should trace to research findings. No data? Say so explicitly.
• Make it actionable. Every document should tell the founder what to do next. Avoid abstract frameworks disconnected from concrete actions.
• Respect the founder's time. Don't generate filler. Skip irrelevant sections and note why in PROGRESS.md.
• Track everything. Update PROGRESS.md after each phase — it's the session lifeline.

Industry Benchmarks by Business Model

Use these as reference points when evaluating a founder's financial projections. Flag projections that fall significantly outside these ranges — both overly optimistic and unnecessarily pessimistic.

SaaS (B2B)

SaaS (B2C / Prosumer)

Marketplace / Platform

E-Commerce / DTC

Consumer App (Ad-Supported)

How to Use These Benchmarks

1. Identify the business model type from the founder's description 2. Compare their projections against the relevant benchmarks 3. Flag deviations in the financial documents:

• If projections assume 1% monthly churn for an SMB SaaS → flag as optimistic, explain that 3-5% is typical
• If projections assume 50% gross margin for a pure software product → flag as pessimistic, ask what's driving costs

4. Cite the benchmark when flagging: "Industry benchmark for B2B SaaS monthly churn is 2-5%; your model assumes 0.5% which would place you in the top 1% of all SaaS companies" 5. Note that early-stage startups often perform worse than benchmarks — these represent what good companies achieve at scale, not what a pre-revenue startup should expect on day one

Intake Interview Questions

Read during Phase 1: Intake Interview. Full question set, hard questions, and interviewing technique.

Core Questions

Ask these in a conversational flow, not as a rigid checklist. Group related questions naturally and adapt based on answers. Not every question applies to every startup — skip what's irrelevant.

The Idea

• What problem are you solving? Who has this problem?
• What's your proposed solution? How does it work?
• What triggered this idea? (personal pain, market observation, technical insight)
• Do you have any existing work? (prototypes, research, landing pages, waitlists)

The Founder(s)

• What's your background? Relevant domain expertise?
• Are you solo or do you have co-founders? What are their strengths?
• How much time can you dedicate? Full-time or side project?
• What's your budget/runway situation?

The Market

• Who is your ideal customer? Be as specific as possible.
• How do they currently solve this problem? (existing alternatives, workarounds)
• Do you know of direct competitors? Who are they?
• What geography/market are you targeting first?

The Business

• How do you plan to make money? (subscription, one-time, marketplace, freemium)
• Any idea of pricing?
• What does success look like in 6 months? 12 months? 3 years?
• What are your biggest unknowns or worries?

Constraints & Preferences

• Any technical constraints? (must be mobile-first, needs to integrate with X)
• Any strong opinions on brand/positioning? (premium vs accessible, playful vs serious)
• Regulatory considerations?
• Have you already spoken with potential customers? If yes: how many, what did they say, did anyone express willingness to pay?

Hard Questions

After the core questions, ask these deliberately uncomfortable questions. They surface blind spots early:

• "Why are you the right person to build this? What unfair advantage do you have?"
• "If Google/a well-funded competitor launched this tomorrow, what would you do?"
• "What's the strongest argument against this idea?"
• "Have you talked to potential customers? What did they actually say (not what you hoped they'd say)?"
• "What would make you walk away from this idea?"

Don't skip these — they set the tone for the entire process and signal that this is an honest assessment, not a cheerleading session.

How to Interview

• Ask 3-5 questions at a time, not all at once
• Acknowledge and build on answers — show you're listening
• Probe vague answers: "You said 'small businesses' — can you narrow that down? Like, freelancers? 10-person agencies? Local retail?"
• After 2-3 rounds, summarize what you've understood and ask the user to confirm or correct

Output Guidelines

Standard File Header

Every output file should start with a consistent header:

# [Document Title]

**Phase:** [Phase number and name]
**Project:** [project-name]
**Date:** [generation date]
**Confidence:** [Overall confidence: High / Medium / Low]

---

This makes it easy for the founder to navigate the deliverables and immediately understand the reliability of each document.

Standard File Footer

Every output file should end with:

---

## Flags

**Red Flags:**
- [List any red flags, or "None identified"]

**Yellow Flags:**
- [List any yellow flags, or "None identified"]

## Sources
- [Key sources referenced in this document with tier ratings]

Cross-Phase Referencing

When a document references findings from another phase, use explicit callouts:

Good:

"The target persona (see 01-discovery/target-audience.md, Persona 1: Mid-market CFO) has an average tool budget of $2,000/month [Data, Gartner 2025]."

Bad:

"As mentioned earlier, the target customer has budget for this."

Always include:

• The file path being referenced
• The specific finding (not a vague reference)
• The data label ([Data], [Estimate], etc.)

Quality Examples

Good vs. Bad Output

Market Analysis — Bad:

"The market presents interesting opportunities for growth. There are several competitors but the space is not overcrowded. Timing seems favorable."

Market Analysis — Good:

"The global invoice automation market is $4.2B [Data, MarketsAndMarkets 2025] growing at 12.3% CAGR [Data, Grand View Research 2025]. However, the SMB segment — our target — represents only $340M [Estimate, derived from 8.1% SMB share reported by Ardent Partners]. Three well-funded competitors (Tipalti $270M raised, Stampli $68M, Vic.ai $52M) already serve this segment [Data, Crunchbase]. [Yellow Flag] The market may be too small for a new entrant competing head-on; a niche positioning is needed."

Scorecard — Bad:

| Market size | 7 | Good market size |

Scorecard — Good:

| Market size | 5 | TAM is $4.2B but our serviceable segment (SMB invoice automation) is ~$340M [Estimate]. At 5% penetration that's $17M ARR — viable for a bootstrapped business but below typical VC thresholds. [Yellow Flag] |

Final Assessment Dashboard

After all 8 phases are complete and before writing the README.md, print a summary dashboard directly in the conversation (not in a file). This gives the founder an instant visual payoff of the entire process.

Pull each value from the actual phase outputs. Do not invent or approximate. If a value was not determined, write "Not assessed".

═══════════════════════════════════════════════
        STARTUP DESIGN — FINAL ASSESSMENT
═══════════════════════════════════════════════

 Idea:              [selected variation from Phase 2 brainstorm]
 Founder Fit:       [Strong / Moderate / Weak]
 Market:            [$X TAM] · [growth %] · [maturity stage]
 Competitors:       [N found] · [funding landscape summary]
 Customer Interviews:[N conducted] · [problem confirmed by N/N]
 Positioning:       [Clear / Emerging / Unclear]
 Business Model:    [SaaS / Marketplace / Open Core / etc.]
 Financial Stage:   [A — Assumption-Based / B — Evidence-Based]
 MVP Scope:         [N core features] · [build estimate]
 Model Viability:   [Viable / Risky / Broken]
 Top Risk:          [single biggest risk in one line]

 SCORE:             [X / 10]
 VERDICT:           [GO / CONDITIONAL / NO-GO]

 Files generated:   [N]
 Directory:         [path]
═══════════════════════════════════════════════

Field definitions:

• Customer Interviews: Number of interviews conducted in Phase 3.7 and problem confirmation rate (e.g., "5 conducted · confirmed by 4/5"). If Fast Track with founder-reported conversations, note "[Founder-reported]". If the founder deferred interviews, write "0 conducted · deferred".
• Financial Stage: A = Assumption-Based (no real traction data), B = Evidence-Based (projections anchored to interview signals or real traction data).
• Idea: The specific variation selected after brainstorming, not the original raw input.
• Founder Fit: From Phase 1 intake assessment. Strong = clear unfair advantage. Moderate = some relevant background. Weak = no domain edge.
• Market: TAM from Phase 3 research, growth rate, and maturity (emerging/growing/mature/declining).
• Competitors: Count of direct competitors found in Phase 3, plus a one-phrase summary of the funding landscape (e.g., "3 funded, 2 bootstrapped" or "dominated by 1 incumbent").
• Positioning: From Phase 4 strategy. Clear = obvious differentiation angle. Emerging = differentiation possible but unproven. Unclear = no obvious angle found.
• Business Model: The model selected in Phase 4 strategy.
• MVP Scope: Number of core features from Phase 6 product definition, plus rough build estimate.
• Model Viability: A synthesis judgment from Phase 7 financials. Viable = unit economics work with reasonable assumptions. Risky = unit economics depend on optimistic assumptions. Broken = unit economics don't work under any reasonable scenario.
• Top Risk: The single highest-impact risk from Phase 8 risk matrix.
• Score / Verdict: From Phase 8 validation scorecard. GO (8-10), CONDITIONAL (6-7), NO-GO (1-5).

Print this dashboard in the conversation after all files are written. Then proceed to write the README.md and action-plan-30-days.md as specified in the main skill file.

---

Handling Pivots

If the founder wants to change direction after seeing research or strategy outputs (different target market, different business model, different positioning):

1. Don't restart from scratch. Much of the research and analysis may still apply. 2. Update the brief (00-intake/brief.md) with a "Pivot Notes" section documenting what changed and why. 3. Re-run only the affected phases. If the pivot is about target market, re-run Phase 3 (customer research waves) and Phase 4 (strategy). If it's about business model, re-run Phase 4 and Phase 7. 4. Mark re-run phases in PROGRESS.md: - [x] Phase 4: Strategy — re-run after pivot {date} 5. Keep old versions. Rename the previous output to {filename}.pre-pivot.md before generating the new version. This preserves the decision trail.

Phase Output Specifications

File-by-file requirements for the Strategy, Brand, Product, and Validation phases. Read the section for the phase you're executing — these specs define what each deliverable must contain.

Contents: Phase 4 — Strategy · Phase 5 — Brand · Phase 6 — Product · Phase 8 — Validation

---

Phase 4 — Strategy (02-strategy/)

lean-canvas.md

Build a complete Lean Canvas (1-page business model):

• Problem (top 3)
• Customer Segments
• Unique Value Proposition
• Solution
• Channels
• Revenue Streams
• Cost Structure
• Key Metrics
• Unfair Advantage

value-proposition.md

• The value proposition canvas (jobs-to-be-done, pains, gains)
• How the product addresses each pain and creates each gain
• The one-sentence value prop
• Proof points and credibility signals

business-model.md

• Revenue model (how money comes in, pricing tiers)
• Unit economics (CAC, LTV, margins — even rough estimates)
• Scalability considerations
• Dependencies and key partnerships

positioning.md

Using April Dunford's positioning framework:

• Competitive alternatives (what happens if you don't exist)
• Unique attributes (what you have that alternatives don't)
• Value (what those attributes enable for customers)
• Target market (who cares the most)
• Market category (the context that makes the value obvious)

go-to-market.md

• Launch strategy (where, how, to whom first)
• First 100 customers plan
• Growth channels ranked by expected impact and cost
• Partnerships and ecosystem plays
• Timeline with milestones

---

Phase 5 — Brand (03-brand/)

mission-vision-values.md

• Mission — Why the company exists (present-tense, action-oriented)
• Vision — The world you're building toward (aspirational but credible)
• Values — 3-5 core values with brief explanations of what they mean in practice (not generic platitudes — values should help make decisions)

Generate 2-3 options for mission and vision for the user to choose from or remix.

tone-of-voice.md

• Brand personality traits (3-4 adjectives with definitions)
• Voice principles with "we are / we are not" examples
• Writing samples: how the brand sounds in different contexts (homepage headline, error message, social media post, customer email)
• Vocabulary guide: preferred terms vs. avoided terms

brand-personality.md

• Brand archetype analysis (which archetype fits and why)
• Emotional attributes
• Visual direction suggestions (not full design, but adjectives and references)
• How the brand should feel compared to competitors

---

Phase 6 — Product (04-product/)

mvp-definition.md

• Core hypothesis the MVP tests
• Must-have features (the minimum set to test the hypothesis)
• Nice-to-have features (for v1.1, not v1.0)
• Explicitly out of scope (prevent scope creep)
• Success criteria: what results would validate the MVP

feature-prioritization.md

• Feature list with RICE or MoSCoW prioritization
• Dependencies between features
• Effort estimates (T-shirt sizing: S/M/L/XL)
• Recommended build order

user-journey.md

• End-to-end user journey map (from discovery to regular usage)
• Key touchpoints and emotions at each stage
• Drop-off risks and mitigation ideas
• The "aha moment" — when does the user first experience value?

---

Phase 8 — Validation (06-validation/)

validation-playbook.md

• Ordered list of experiments to run, from cheapest/fastest to most expensive
• For each experiment:
• What assumption it tests
• How to run it (step-by-step)
• What to measure
• What result would validate vs. invalidate the assumption
• Estimated time and cost
• Examples: landing page test, fake door test, concierge MVP, customer interviews, ad campaign test, wizard of oz, pre-sales
• If customer interviews were deferred in Phase 3.7, they are experiment #1 — no exceptions

Tailor experiments to the specific idea — a B2B SaaS needs different validation than a consumer marketplace.

risk-analysis.md

• Risk matrix (likelihood × impact) for:
• Market risks (no demand, timing, regulatory)
• Product risks (can't build it, won't work)
• Business risks (can't monetize, can't scale)
• Team risks (missing skills, founder conflicts)
• Financial risks (runway, CAC too high)
• For each high-priority risk: mitigation strategy and early warning signals

assumptions-tracker.md

• Every critical assumption the business plan rests on
• Current confidence level (high/medium/low)
• How to test each assumption
• Status: untested / testing / validated / invalidated

Format as a table for easy scanning and updating.

experiment-design.md

• Detailed design for the top 3 recommended experiments
• Hypothesis, method, metrics, success criteria, timeline
• Templates the founder can use immediately (interview scripts, survey questions, landing page copy outline)

kill-criteria.md

Define 5-7 specific, measurable conditions under which the founder should stop or pivot. Tie each to a validation experiment. Be specific: "If fewer than 3/10 interview subjects say they'd pay $X" not "if there's no demand." This protects the founder from sunk-cost thinking.

scorecard.md

Produce a summary scorecard:

Be honest. If the idea has weaknesses, say so clearly. The goal is to help the founder make a good decision, not to validate their ego. Include a clear Verdict paragraph after the table with an unambiguous recommendation (see the scoring guide in the Radical Honesty Protocol).

Research Principles

These principles apply to ALL research agents across all waves. Every agent must follow them.

Iterative Deep Research

Each agent performs 5-8 web searches minimum, organized in sequential rounds that drill deeper:

• Round 1: Broad overview queries
• Round 2: Drill-down into specific findings from Round 1
• Round 3: Cross-reference and validate
• Round 4: Reality check and edge cases

Do NOT stop after a single query. The first search gives you the surface — the follow-ups give you the insight.

Source Quality Tiers

Rank every finding by source reliability:

A Tier 3 source saying "the market is $5B" is not reliable. A Tier 1 report saying the same thing is.

Cross-Referencing

Never trust a single source for important claims. For every key finding:

• Look for 2-3 independent sources
• If sources agree: note convergence and cite all
• If sources disagree: note both figures, explain the discrepancy, and state which you trust more and why

Quantification

Vague claims are worthless. Always push for numbers:

• Bad: "The market is growing fast"
• Good: "$4.2B market growing at 12.3% CAGR (Grand View Research, 2025)"
• Bad: "Many companies use this"
• Good: "67% of mid-size companies report using at least one AP automation tool (Ardent Partners, 2025)"

Dating

Always note when data was published. Flag anything older than 18 months as potentially outdated. Markets can shift significantly in that time, especially in tech.

Handling Research Failures

Sometimes WebSearch won't find what you need. When this happens:

1. Try alternative queries. Rephrase, use synonyms, try different angles. At least 3 variations before declaring a gap. 2. Use proxy data. If you can't find market size for your exact segment, find the broader market and estimate the segment share. Show your math. 3. Declare the gap explicitly. Write: "DATA GAP: Could not find reliable data on [X]. Closest proxy: [Y]. Confidence: Low." 4. Never fabricate. If you don't have data, say so. An honest "unknown" is infinitely more valuable than a made-up number. 5. Suggest how to fill the gap. Point to specific reports that might have the data (even if paywalled), or recommend primary research the founder could do.

Research Scaling Protocol

Dynamic scaling adjusts research depth based on market complexity and user preference. Evaluated after intake, before research begins.

Complexity Score

Assess three factors from the intake data:

Complexity score = sum of the three factors (range: 3-9)

Research Depth Tiers

Manual override always wins. If the user requests "light" on a score-9 market, use Light. If they request "deep" on a score-3 market, use Deep.

User Communication

After calculating the score, show this to the user:

## Research Depth

Based on your intake, I've assessed the research complexity:

| Factor           | Assessment          | Score |
|------------------|---------------------|-------|
| Market breadth   | {description}       | {1-3} |
| Known competitors| {N} identified      | {1-3} |
| Geographic scope | {description}       | {1-3} |

**Complexity score: {X}/9 — recommended depth: {Light/Standard/Deep}**

You can override this. Here's what each depth means:

| Depth        | Agents | Searches per agent | Best for                                      |
|--------------|--------|--------------------|-----------------------------------------------|
| **Light**    | {N}    | 2-3 rounds         | Quick scan, niche markets, time-sensitive decisions |
| **Standard** | {N}    | 3-4 rounds         | Most cases, balanced depth vs. speed           |
| **Deep**     | {N}    | 5-6 rounds         | Crowded markets, high-stakes decisions, thorough due diligence |

→ Type **light**, **deep**, or **ok** to accept the recommendation.

The agent counts shown should reflect the actual numbers for this skill (see Wave Configuration below).

Wave Configuration: startup-design

Light (3-4 score or user override)

Wave 1: Market Landscape (2 agents)

• A1: Market Sizing & Economics (unchanged)
• A2: Industry Trends, Timing & Regulatory (merge A2+A3 into one agent)

Wave 2: Competitive Analysis (2 agents)

• B1: Direct Competitor Deep-Dives (unchanged)
• B2: Indirect Competitors & GTM (merge B2+B3 into one agent)

Wave 3: Customer & Demand (2 agents)

• C1: Customer Voice & Pain Points (unchanged)
• C2: Demand Signals & Audience Profiling (merge C2+C3 into one agent)

Wave 4: Distribution (1 agent)

• D1: Distribution & Geographic Entry (merge D1+D2 into one agent)
• Skip Wave 4 entirely if market is local/single-country

Total: 6-7 agents (vs. 11 Standard), 2-3 search rounds per agent

Standard (5-7 score, default)

No changes to current wave structure:

• Wave 1: 3 agents (A1, A2, A3)
• Wave 2: 3 agents (B1, B2, B3)
• Wave 3: 3 agents (C1, C2, C3)
• Wave 4: 2 agents (D1, D2)

Total: 11 agents, 3-4 search rounds per agent

Deep (8-9 score or user override)

Wave 1: Market Landscape (4 agents)

• A1: Market Sizing & Economics (unchanged)
• A2: Industry Trends & Timing (unchanged)
• A3: Regulatory & Compliance (unchanged)
• A4: Adjacent Markets & Expansion (NEW: research adjacent verticals, whitespace, expansion paths)

Wave 2: Competitive Analysis (4 agents)

• B1: Direct Competitor Deep-Dives (unchanged)
• B2: Indirect Competitors & Substitutes (unchanged)
• B3: Competitor Go-to-Market (unchanged)
• B4: Emerging & Stealth Competitors (NEW: search for stealth startups, recent launches, pre-launch products in the space)

Wave 3: Customer & Demand (4 agents)

• C1: Customer Voice & Pain Points (unchanged)
• C2: Demand Signals & Market Validation (unchanged)
• C3: Target Audience Profiling (unchanged)
• C4: Pricing Deep-Dive (NEW: detailed pricing intelligence, WTP analysis, price sensitivity research)

Wave 4: Distribution & Partnerships (3 agents)

• D1: Distribution Channel Deep-Dive (unchanged)
• D2: Geographic & Market Entry (unchanged)
• D3: Strategic Partnership Mapping (NEW: potential partners, integration opportunities, channel partnerships)

Total: 15 agents, 5-6 search rounds per agent

PROGRESS.md

Record the selected tier in PROGRESS.md:

- **Research Depth:** {Light/Standard/Deep} (score: {X}/9, {override: user request / auto})

Research Synthesis Protocol

After ALL waves complete (10-11 agents, depending on whether A3/Regulatory was skipped), synthesize the raw findings into polished deliverables. This step creates the real analytical value — it's not copying, it's connecting.

How to Synthesize

This is reasoning work, not transcription. Read everything first, then think hard about what it all means before writing a single deliverable — the connections you draw here are the analytical value the founder is paying for. Move through these steps deliberately rather than rushing to fill the templates:

1. Read all raw files in 01-discovery/raw/ before writing anything. 2. Look for patterns across sources: what themes repeat? What surprised you? 3. Identify contradictions between sources and explain which you trust more and why. 4. Connect the dots between research areas: how do competitive gaps connect to customer pains? How do market trends affect the go-to-market? 5. Highlight strategic implications — don't just report facts; say what they mean for this startup. 6. Rate your confidence for each major finding: High (multiple Tier 1 sources agree), Medium (some evidence but gaps), Low (limited data, mostly inferred). 7. Aggregate data gaps from all raw files and present them clearly — these become inputs for Phase 8 (Validation).

Output Files

01-discovery/market-analysis.md

Synthesize from: raw/market-size.md, raw/trends.md, raw/regulatory.md, raw/geographic.md

Structure:

• Executive summary (5-sentence overview of the market opportunity)
• Market size with TAM/SAM/SOM breakdown and confidence ratings
• Growth trajectory with key drivers and headwinds
• Market maturity assessment (emerging / growing / mature / declining)
• Unit economics benchmarks (carried from market sizing, used by Phase 7)
• Regulatory summary (key requirements, compliance costs, timeline)
• Geographic analysis (beachhead market, expansion path)
• Timing assessment: why now? What tailwinds and headwinds exist?
• Data gaps aggregated from all market-related research

01-discovery/competitor-landscape.md

Synthesize from: raw/direct-competitors.md, raw/indirect-competitors.md, raw/competitor-gtm.md

Structure:

• Competitive overview (how crowded, market concentration, overall threat level)
• Competitor comparison matrix (features × competitors table)
• Positioning map (describe how competitors position themselves, where the whitespace is)
• Competitor GTM summary (what acquisition channels work, what's saturated)
• Platform risk assessment (which platforms could absorb our functionality)
• Switching cost analysis (what keeps people on current solutions)
• Strategic recommendations: where to compete, where to avoid, how to differentiate
• Vulnerability analysis: which competitors are weakest and why — where can we win?
• Data gaps

01-discovery/target-audience.md

Synthesize from: raw/customer-voice.md, raw/target-audience.md, raw/demand-signals.md

Structure:

• Primary persona (vivid, data-backed, with representative quote)
• Secondary persona (if applicable)
• Anti-persona (who NOT to target)
• Customer pain hierarchy (ranked by frequency × intensity, from customer voice)
• Jobs-to-be-done framework (functional, social, emotional)
• Language map (exact words customers use — feed directly into copywriting)
• Buying behavior (decision process, criteria, cycle length, objections)
• Where to reach them (ranked channels with density and cost)
• Demand validation (search trends, WTP evidence, market validation score)
• Data gaps

01-discovery/industry-trends.md

Synthesize from: raw/trends.md, raw/regulatory.md, raw/demand-signals.md

Structure:

• Macro trends affecting the industry (with timeline and impact assessment)
• Technology shifts and their adoption curve
• Investment and M&A signals (what smart money is doing)
• Behavioral shifts in target customers
• Regulatory trajectory (direction of travel, not just current state)
• What this means for our startup — explicit strategic implications
• Timing scorecard: is now the right time? Rate: tailwinds vs. headwinds
• Data gaps

01-discovery/confidence-dashboard.md

Synthesize from: ALL raw files across all waves.

Structure:

• Overview — How much of the analysis rests on solid ground vs. thin ice
• Claim-level confidence table:

• Highest confidence findings — Claims backed by multiple Tier 1 sources
• Lowest confidence findings — Claims based on single sources, inferred data, or old information
• Critical unknowns — Things we don't know that could change the strategy
• Recommendations — What the founder should verify first, and how

This file helps the founder understand where they're standing on solid ground vs. making decisions based on weak data. It's the meta-layer above the other 4 deliverables.

---

Cross-Document Connections

After writing all 4 files, add a "Strategic Connections" section at the end of each that links to insights from the other documents. For example:

• In market-analysis.md: "The growth in [trend X] (see industry-trends.md) creates an opening in [segment Y] that [competitor Z] (see competitor-landscape.md) hasn't addressed."
• In target-audience.md: "The pricing sensitivity found here aligns with the $X-Y range from competitor pricing analysis (see competitor-landscape.md)."

These connections help Phase 4 (Strategy) build on concrete research rather than abstract claims.

Post-Synthesis Verification

After writing all deliverables, run the Verification Agent protocol. See references/verification-agent.md for the full process. The verification step checks all deliverables for unlabeled claims, internal contradictions, confidence rating consistency, and startup-design-specific cross-phase coherence (strategy reflects market data, product reflects customer pains, financial reflects business model, validation covers identified risks).

Cleanup

Keep the raw/ directory for reference. Note in PROGRESS.md that raw research files are available at 01-discovery/raw/.

Wave 1: Market Landscape (3 agents)

Read research-principles.md first for cross-cutting rules on source quality, cross-referencing, and quantification.

---

Agent A1: Market Sizing & Economics

Research task: Deep market sizing for {industry/product category}
Context: We're designing a startup that {one-sentence description}.
Target market: {geography}, {customer segment}

RESEARCH PROTOCOL — perform these searches in sequence, each building on the last:

ROUND 1 — Broad market overview (2-3 searches):
- "{broad category} market size {current year}"
- "{broad category} market report {current year}"
- "{industry} industry overview statistics"
Capture: TAM figures, growth rates, key players. Note which reports are cited most.

ROUND 2 — Segment drill-down (2-3 searches):
- "{specific segment} market size {geography}"
- "{specific segment} spending trends"
- "{customer type} budget for {product category}"
Capture: SAM figures, segment-specific growth, spending patterns per customer.

ROUND 3 — Unit economics research (2-3 searches):
- "{product category} average contract value"
- "{product category} customer acquisition cost benchmarks"
- "{product category} churn rate benchmarks"
- "{product category} pricing survey"
Capture: Industry benchmarks for ACV, CAC, LTV, churn. These ground the financial model later.

ROUND 4 — Reality check (1-2 searches):
- "{product category} market challenges {current year}"
- "why {product category} startups fail"
Capture: Headwinds, saturation signals, common failure modes.

OUTPUT FORMAT:
# Market Sizing: {industry}

## TAM (Total Addressable Market)
- Figure: $X (Source, Date)
- Figure: $Y (Source, Date) — [note if different and why]
- Growth rate: X% CAGR (Source)

## SAM (Serviceable Addressable Market)
- Segment: {specific segment}
- Figure: $X (Source, Date)
- Reasoning: [how SAM was derived from TAM]

## SOM (Serviceable Obtainable Market)
- Realistic Year 1 capture: $X
- Reasoning: [based on comparable company trajectories]

## Unit Economics Benchmarks
- Average contract value: $X/mo or $X/yr
- Customer acquisition cost: $X
- Lifetime value: $X
- Churn rate: X%/mo or X%/yr
- [Note if benchmarks are for this specific segment or broader industry]

## Market Headwinds & Risks
- [List specific challenges with sources]

## Source Quality Assessment
- [Rate each major source as Tier 1/2/3 and note any data gaps]

## Data Gaps
- [List anything you couldn't find with suggested ways to fill the gap]

Save to: {project-name}/01-discovery/raw/market-size.md

---

Agent A2: Industry Trends & Timing

Research task: Industry trends, timing signals, and future trajectory for {industry}
Context: We're designing a startup that {one-sentence description}.

RESEARCH PROTOCOL — perform these searches in sequence:

ROUND 1 — Technology trends (2-3 searches):
- "{industry} technology trends {current year}"
- "AI impact on {industry}"
- "{industry} innovation report {current year}"
Capture: Which technologies are reshaping the space. Adoption curves. Maturity levels.

ROUND 2 — Investment & M&A activity (2-3 searches):
- "{industry} startup funding {current year}"
- "{industry} acquisitions {current year}"
- "{product category} venture capital deals"
Search Crunchbase, PitchBook summaries, TechCrunch funding roundups.
Capture: Deal sizes, acquiring companies (signals of where big players see value), accelerating or decelerating investment.

ROUND 3 — Behavioral shifts (2 searches):
- "{customer type} changing expectations {industry}"
- "remote work impact on {industry}" OR "{customer type} digital adoption"
Capture: How customer behavior is evolving. New expectations. Generational shifts.

ROUND 4 — Expert predictions (1-2 searches):
- "{industry} predictions {current year + 1}"
- "{industry} future outlook analyst"
Capture: Where credible analysts think this is heading. Consensus vs. contrarian views.

OUTPUT FORMAT:
# Industry Trends: {industry}

## Technology Trends
For each trend:
- Trend name and description
- Current adoption stage (early/growing/mature/declining)
- Impact on our startup (opportunity/threat/neutral)
- Timeline: when does this become mainstream?
- Source and date

## Investment Activity
- Total funding in space (last 12 months): $X across N deals
- Notable rounds: [company, amount, stage, date]
- Notable acquisitions: [acquirer → target, amount, date, strategic rationale]
- Investment trend: accelerating / stable / decelerating
- What this signals for our startup

## Behavioral Shifts
- [Specific shift with data]
- [How this affects demand for our product]

## Expert Predictions
- [Prediction, source, credibility assessment]

## Timing Assessment
- Is now a good time to enter this market? Why or why not?
- What would make the timing better or worse?

## Data Gaps
- [List anything you couldn't find]

Save to: {project-name}/01-discovery/raw/trends.md

---

Agent A3: Regulatory & Compliance Landscape

Skip this agent if the startup has no obvious regulatory exposure. When in doubt, run it — better to discover regulatory requirements early than late.

Research task: Regulatory landscape for {industry} in {geography}
Context: We're designing a startup that {one-sentence description}.

RESEARCH PROTOCOL:

ROUND 1 — Current regulations (2-3 searches):
- "{industry} regulations {geography} {current year}"
- "{product type} compliance requirements"
- "{industry} licensing requirements {geography}"

ROUND 2 — Data & privacy (2 searches):
- "{industry} data privacy requirements"
- "GDPR CCPA impact on {industry}" OR "{industry} data handling regulations"

ROUND 3 — Upcoming changes (1-2 searches):
- "{industry} new regulations {current year}"
- "{industry} regulatory changes pending legislation"

ROUND 4 — Enforcement & precedent (1 search):
- "{industry} regulatory enforcement actions" OR "{industry} compliance fines"

OUTPUT FORMAT:
# Regulatory Landscape: {industry} in {geography}

## Current Regulations
For each regulation:
- Name and jurisdiction
- What it requires
- Who it applies to (does it apply to us at launch? At scale?)
- Compliance cost estimate
- Timeline to compliance

## Data & Privacy
- Applicable frameworks (GDPR, CCPA, HIPAA, etc.)
- Data handling requirements specific to this industry
- Impact on product architecture

## Upcoming Changes
- Pending legislation or proposed rules
- Expected timeline
- Potential impact

## Compliance Cost Estimate
- Minimum viable compliance: $X (what you need at launch)
- Full compliance: $X (what you need at scale)
- Certifications needed: [SOC 2, ISO 27001, HIPAA, etc.]

## Risk Assessment
- Regulatory risk level: Low / Medium / High
- Key regulatory risks for this specific startup

## Data Gaps
- [List anything you couldn't find]

Save to: {project-name}/01-discovery/raw/regulatory.md

Wave 2: Competitive Analysis (3 agents)

Read research-principles.md first. Wave 2 agents receive findings from Wave 1 as context — pass them a summary of market size, key players identified, and relevant trends.

---

Agent B1: Direct Competitor Deep-Dives

Research task: Deep analysis of direct competitors for {product description}
Context: We're designing a startup that {one-sentence description}.
Market context from Wave 1: {brief summary of market size, key players found}

RESEARCH PROTOCOL — for each competitor (aim for 5-8 direct competitors):

ROUND 1 — Identify competitors (3-4 searches):
- "{problem} software/app/tool {current year}"
- "best {product category} tools {current year}"
- "{known competitor 1} vs {known competitor 2} alternatives"
- "G2 {product category} grid"
- "{product category} Product Hunt"

ROUND 2 — Deep-dive each competitor (2-3 searches per competitor):
- Visit their website directly: capture pricing, features, positioning
- "{competitor name} review" on G2, Capterra, TrustRadius
- "{competitor name} funding crunchbase" OR "{competitor name} investors"
- "{competitor name} employees linkedin" (for team size signals)
- "{competitor name} complaints" OR "{competitor name} problems reddit"

ROUND 3 — Competitive dynamics (2 searches):
- "{product category} market share"
- "{competitor 1} vs {competitor 2}" comparison articles

For EACH competitor, build a complete profile:

COMPETITOR PROFILE TEMPLATE:
## {Competitor Name}
- **Website:** {url}
- **Founded:** {year}
- **Headquarters:** {location}
- **Team size:** {estimate from LinkedIn/Crunchbase}
- **Funding:** {total raised, last round, investors}
- **Stage:** bootstrapped / seed / Series A / Series B+ / public

### Product
- **Core offering:** {what they sell}
- **Key features:** {top 5 features}
- **Tech stack signals:** {any public info on their technology}
- **Integrations:** {what they connect with}

### Pricing
- **Model:** {subscription / per-user / usage-based / freemium}
- **Tiers:** {list each tier with price and what's included}
- **Free plan:** yes/no, what's included
- **Enterprise:** custom pricing? sales-led?

### Market Position
- **Target customer:** {who they serve}
- **Positioning:** {how they describe themselves — capture their actual tagline}
- **Key differentiator:** {what they claim makes them unique}

### Traction Signals
- **G2/Capterra reviews:** {count and average rating}
- **Product Hunt:** {upvotes if launched there}
- **Social media:** {follower counts on LinkedIn, Twitter}
- **Job postings:** {number and type — engineering heavy = building; sales heavy = scaling}
- **Notable customers:** {logos or case studies on their site}

### Strengths (based on reviews and positioning)
- {strength 1}
- {strength 2}

### Weaknesses (based on negative reviews, missing features, complaints)
- {weakness 1}
- {weakness 2}

### Threat Level to Our Startup: Low / Medium / High
- {why}

---

After all profiles, add:

## Competitive Landscape Summary
- **Market concentration:** fragmented / consolidating / dominated by 1-2 players
- **Gaps in the market:** {what no competitor does well}
- **Positioning opportunities:** {where we can differentiate}
- **Competitive moat assessment:** {how defensible is this market}

## Data Gaps
- [Competitors you suspect exist but couldn't find info on]
- [Data points missing for specific competitors]

Save to: {project-name}/01-discovery/raw/direct-competitors.md

---

Agent B2: Indirect Competitors & Substitutes

Research task: Indirect competitors, substitutes, and alternative approaches for {problem}
Context: We're designing a startup that {one-sentence description}.
Direct competitors found: {list from Agent B1 if available, otherwise "to be determined"}

RESEARCH PROTOCOL:

ROUND 1 — Alternative approaches (2-3 searches):
- "how do {customer type} currently handle {problem}"
- "{problem} without software"
- "{problem} excel template" OR "{problem} manual process"
- "{problem} outsource"

ROUND 2 — Adjacent products (2-3 searches):
- "{adjacent category} that also does {related function}"
- "{large platform} {related feature}" (e.g., "Salesforce reporting" if you're building analytics)
- "open source {product category}"

ROUND 3 — Platform risk (1-2 searches):
- "{major platform} adding {our feature}"
- "{major platform} AI features {current year}"

OUTPUT FORMAT:
# Indirect Competitors & Substitutes

## Status Quo Solutions (what people do today without a dedicated tool)
For each:
- What it is
- How common it is
- Why people stick with it (cost, familiarity, "good enough")
- Where it breaks down (the pain that creates our opportunity)

## Adjacent Products
For each:
- Product name and what it primarily does
- How it partially solves our problem
- What it's missing (our wedge)
- Risk: could they add our feature?

## Platform Risk Assessment
- Which major platforms could absorb our functionality?
- How likely is this? (based on roadmap signals, acquisitions, public statements)
- Timeline estimate
- Mitigation strategies

## Open Source & Free Alternatives
- What exists
- Quality and adoption level
- Why someone would pay for our solution instead

## Switching Cost Analysis
- What keeps people on current solutions?
- What would make them switch?
- Estimated effort to migrate to our product

## Data Gaps
- [List anything you couldn't find]

Save to: {project-name}/01-discovery/raw/indirect-competitors.md

---

Agent B3: Competitor Go-to-Market Analysis

Research task: How competitors in {product category} acquire and retain customers
Context: We're designing a startup that {one-sentence description}.
Key competitors: {list top 3-5 from Agent B1}

RESEARCH PROTOCOL:

ROUND 1 — Marketing channels (2-3 searches per competitor):
- Check competitor websites for blog, resources, webinars, case studies
- "{competitor name} marketing strategy"
- Search for competitor ads (Google Ads transparency, Facebook Ad Library)
- Check their social media activity and content frequency

ROUND 2 — Sales motion (2 searches):
- "{competitor name} sales team" linkedin
- "{product category} sales cycle length"
- Look for: self-serve signup vs. demo request vs. "contact sales"

ROUND 3 — Content & SEO (2 searches):
- "{product category} blog" — who ranks for key terms?
- Check competitors on Similarweb or similar tools for traffic estimates

OUTPUT FORMAT:
# Competitor Go-to-Market Analysis

For each competitor:
## {Competitor Name} — GTM Breakdown
- **Primary acquisition channel:** {SEO / paid ads / outbound sales / partnerships / community / PLG}
- **Sales motion:** {self-serve / sales-assisted / enterprise sales}
- **Content strategy:** {blog frequency, topics, quality assessment}
- **Social presence:** {which platforms, posting frequency, engagement level}
- **Paid advertising:** {visible ads? what channels? what messaging?}
- **Partnership plays:** {integrations, co-marketing, channel partners}
- **Pricing as GTM:** {freemium? free trial? money-back guarantee?}

## Channel Opportunity Map
| Channel | Competitor Saturation | Our Opportunity | Estimated CAC |
|---------|----------------------|-----------------|---------------|
| SEO/Content | High/Medium/Low | ... | ... |
| Paid Search | ... | ... | ... |
| Social/Community | ... | ... | ... |
| Outbound Sales | ... | ... | ... |
| Partnerships | ... | ... | ... |
| Product-Led Growth | ... | ... | ... |

## Key Takeaway
- What's working for competitors?
- What channels are underexploited?
- Where can we win with limited budget?

## Data Gaps
- [List anything you couldn't find]

Save to: {project-name}/01-discovery/raw/competitor-gtm.md

Wave 3: Customer & Demand (3 agents)

Read research-principles.md first. Wave 3 agents receive competitor findings from Wave 2 as context.

---

Agent C1: Customer Voice & Pain Points

Research task: Deep customer research — real voices discussing {problem}
Context: We're designing a startup that {one-sentence description}.
Target customer: {customer description}
Key competitors found: {list from Wave 2}

The goal is to hear how real people talk about this problem in their own words. This directly informs positioning, copywriting, and product decisions.

RESEARCH PROTOCOL:

ROUND 1 — Reddit deep-dive (3-4 searches):
- "site:reddit.com {problem keywords}"
- "site:reddit.com {industry} frustration"
- "site:reddit.com {existing solution} complaints"
- Browse top posts in relevant subreddits: r/{industry}, r/{role}, r/{related topic}
For each relevant thread: capture the original post, top comments, and upvote counts (upvotes = agreement).

ROUND 2 — Professional forums (2-3 searches):
- "site:news.ycombinator.com {problem keywords}"
- "{problem} forum discussion"
- "{industry} community {problem}"
- Check industry-specific forums (e.g., Stack Overflow for devtools, Bogleheads for finance)

ROUND 3 — Review mining (2-3 searches):
- "{existing solution} reviews" on G2, Capterra, TrustRadius
- Focus on 1-3 star reviews — these reveal unmet needs
- "{existing solution} worst thing about"

ROUND 4 — Social media sentiment (1-2 searches):
- "site:twitter.com {problem keywords}" OR "site:linkedin.com {problem keywords}"
- "{problem} rant" OR "{problem} hate"

OUTPUT FORMAT:
# Customer Voice Research: {problem}

## Verbatim Quotes (Top 20)
Capture exact quotes that express the pain. For each:
- Quote (verbatim)
- Source (Reddit, G2, etc. — with thread/review link if possible)
- Context (who is this person? what role/industry?)
- Upvotes/agreement signals
- Pain category (see below)

## Pain Categories (grouped from quotes)
For each category:
- Name of pain (e.g., "Time wasted on manual process")
- Frequency: how often does this come up across all sources?
- Intensity: mild annoyance vs. hair-on-fire problem?
- Current workarounds people mention
- Quotes that best represent this pain

## Jobs-to-Be-Done (extracted from customer voice)
- Functional jobs: what are they trying to accomplish?
- Social jobs: how do they want to be perceived?
- Emotional jobs: how do they want to feel?

## Language Map
Words and phrases customers actually use to describe:
- The problem: [list exact words]
- The desired outcome: [list exact words]
- Their frustrations: [list exact words]
This language should be used verbatim in positioning and copy — it resonates because it mirrors their own words.

## Unmet Needs (things people ask for that don't exist yet)
- [Need 1 — evidence from quotes]
- [Need 2 — evidence from quotes]

## Data Gaps
- [Communities you couldn't access or find]
- [Customer segments with no voice data]

Save to: {project-name}/01-discovery/raw/customer-voice.md

---

Agent C2: Demand Signals & Market Validation

Research task: Quantitative demand signals for {product category}
Context: We're designing a startup that {one-sentence description}.

RESEARCH PROTOCOL:

ROUND 1 — Search demand (2-3 searches):
- Google Trends for: "{product category}", "{problem} solution", "{competitor name}"
- "{product category} search volume"
- "keyword research {product category}"
Capture: trend direction (rising/flat/declining), seasonal patterns, geographic hotspots.

ROUND 2 — Product launch signals (2 searches):
- Search Product Hunt for similar products — upvotes, comments, maker responses
- Search Indie Hackers for people building in this space — revenue numbers if shared
- Check beta list / landing page tools for pre-launch products in the space

ROUND 3 — Pricing intelligence (3-4 searches):
- Visit pricing pages of top 5 competitors (directly)
- "{product category} pricing comparison {current year}"
- "{product category} how much do companies spend"
- "{customer type} software budget survey"
Capture: exact pricing tiers from each competitor in a comparison table.

ROUND 4 — Willingness to pay signals (1-2 searches):
- "{product category} survey willingness to pay"
- "{problem} worth paying for"
- Check subreddits and forums for discussions about pricing of similar tools

OUTPUT FORMAT:
# Demand Signals: {product category}

## Search Demand
- Google Trends summary: [rising / stable / declining over what period]
- Peak months (if seasonal): [months]
- Geographic hotspots: [regions/countries with highest interest]
- Related rising queries: [list — these reveal adjacent opportunities]

## Product Launch Signals
| Product | Platform | Date | Upvotes/Reception | Key Takeaway |
|---------|----------|------|-------------------|-------------|
| ... | ... | ... | ... | ... |

## Pricing Landscape
| Competitor | Free Plan | Starter | Pro | Enterprise | Model |
|-----------|-----------|---------|-----|-----------|-------|
| ... | ... | ... | ... | ... | ... |

- Median price point: $X/mo
- Price range: $X - $Y/mo
- Most common model: [subscription / per-user / usage-based]
- Pricing trends: [racing to bottom? premium tier growing? usage-based gaining?]

## Willingness to Pay Assessment
- Evidence for strong WTP: [list]
- Evidence for weak WTP: [list]
- Recommended pricing range for our startup: $X - $Y/mo
- Rationale: [why this range, based on competitor benchmarks and value delivered]

## Market Validation Score
- Search demand: Strong / Moderate / Weak
- Competitive activity: High / Medium / Low (high = proven market; low = unproven)
- Customer spending: Growing / Stable / Declining
- Overall demand signal: [assessment]

## Data Gaps
- [Keywords with no trend data]
- [Competitors with hidden pricing]

Save to: {project-name}/01-discovery/raw/demand-signals.md

---

Agent C3: Target Audience Profiling

Research task: Deep target audience research for {customer description}
Context: We're designing a startup that {one-sentence description}.

RESEARCH PROTOCOL:

ROUND 1 — Demographic & firmographic data (2-3 searches):
- "{customer type} demographics statistics"
- "how many {customer type} in {geography}"
- "{customer type} company size distribution"
Capture: population size, segmentation data, geographic distribution.

ROUND 2 — Behavioral patterns (2-3 searches):
- "{customer type} software adoption habits"
- "{customer type} buying process for {product category}"
- "how do {customer type} discover new tools"
Capture: where they research, who influences them, decision-making process.

ROUND 3 — Day-in-the-life (2 searches):
- "{role} daily challenges"
- "{role} workflow {industry}"
Capture: what their day looks like, where our product fits in their workflow.

ROUND 4 — Decision-making (1-2 searches):
- "{product category} buying criteria"
- "who decides on {product category} at {company type}"
Capture: who are the buyers, influencers, blockers? What's the typical sales cycle?

OUTPUT FORMAT:
# Target Audience Profile: {customer description}

## Primary Persona
- **Name:** {fictional representative name}
- **Role:** {job title}
- **Company:** {company type, size, industry}
- **Demographics:** {age range, location, education}
- **Goals:** {what they're trying to achieve}
- **Frustrations:** {specific pains related to our problem}
- **Current tools:** {what they use today}
- **Quote:** {a representative quote from customer voice research}

## Buying Behavior
- **How they discover tools:** {channels, sources}
- **Who's involved in the decision:** {buyer, influencer, approver, blocker}
- **Decision criteria:** {top 5 factors ranked}
- **Typical budget:** {what they spend on similar tools}
- **Sales cycle length:** {days/weeks/months}
- **Common objections:** {why they might say no}

## Secondary Persona (if applicable)
[Same structure as primary]

## Anti-Persona (who is NOT our customer)
- {description of who we should NOT target and why}

## Where to Reach Them
| Channel | Density | Cost | Notes |
|---------|---------|------|-------|
| {specific subreddits} | ... | Free | ... |
| {specific LinkedIn groups} | ... | ... | ... |
| {specific conferences} | ... | ... | ... |
| {specific newsletters} | ... | ... | ... |
| {specific podcasts} | ... | ... | ... |
| {specific communities} | ... | ... | ... |

## Data Gaps
- [Audience segments with no data]
- [Behavioral data you couldn't find]

Save to: {project-name}/01-discovery/raw/target-audience.md

Wave 4: Distribution & Partnerships (2 agents)

Read research-principles.md first. Wave 4 agents receive all prior wave findings as context.

---

Agent D1: Distribution Channel Deep-Dive

Research task: Viable distribution channels for {product category} targeting {customer type}
Context: We're designing a startup that {one-sentence description}.
Competitor GTM findings: {summary from Agent B3}
Target audience: {summary from Agent C3}

RESEARCH PROTOCOL:

ROUND 1 — Content & SEO opportunity (3 searches):
- "{product category} keywords" — look for keyword lists, SEO analyses
- Check Ahrefs/Semrush free tools for domain ratings of competitor content
- "{problem} how to" — are there informational queries we could rank for?
Capture: keyword opportunities, content gaps, estimated difficulty.

ROUND 2 — Community & organic (2-3 searches):
- Find the top 5 communities where target customers are active
- Check community rules on self-promotion (some ban it, some welcome it)
- "{product category} referral program" — do competitors use referrals?

ROUND 3 — Paid acquisition benchmarks (2 searches):
- "{industry} Google Ads CPC"
- "{product category} Facebook ads cost per lead"
- "{industry} LinkedIn ads benchmark"
Capture: estimated CPCs, CPLs for relevant channels.

ROUND 4 — Partnership opportunities (2 searches):
- "{product category} integrations marketplace"
- "{adjacent tool} partner program"

OUTPUT FORMAT:
# Distribution Channel Analysis

## Channel Ranking (by expected ROI for a bootstrapped startup)

### Tier 1: High-Impact, Low-Cost
For each channel:
- Channel name
- Why it works for this startup
- Estimated reach
- Estimated CAC
- Time to first results
- How to get started (specific, actionable steps)

### Tier 2: Medium-Impact, Medium-Cost
[Same structure]

### Tier 3: Long-Term Bets
[Same structure]

### Channels to Avoid
- [Channel] — why it won't work for this startup

## SEO / Content Opportunity
- Top 10 keyword opportunities with estimated volume and difficulty
- Content gap analysis: what competitors haven't covered well
- Recommended content strategy (topics, format, frequency)

## Partnership Opportunities
For each potential partnership:
- Partner name/type
- What they get from us
- What we get from them
- How to approach them
- Priority: High / Medium / Low

## First 90 Days Channel Plan
- Week 1-4: [specific actions]
- Week 5-8: [specific actions]
- Week 9-12: [specific actions]

## Data Gaps
- [Channels you couldn't estimate costs for]

Save to: {project-name}/01-discovery/raw/channels.md

---

Agent D2: Geographic & Market Entry Analysis

Research task: Geographic and market entry analysis for {product} in {target geography}
Context: We're designing a startup that {one-sentence description}.
Target: {geography / market segment}

RESEARCH PROTOCOL:

ROUND 1 — Geographic market conditions (2-3 searches):
- "{industry} market {target city/country}"
- "{customer type} concentration {geography}"
- "{product category} adoption rate {geography}"

ROUND 2 — Local competitive dynamics (2 searches):
- "{product category} {target geography} startups"
- Local directories / review sites for competitors in target geography

ROUND 3 — Entry barriers (1-2 searches):
- "{industry} barriers to entry {geography}"
- Language, cultural, regulatory, payment differences (for international markets)

OUTPUT FORMAT:
# Geographic & Market Entry Analysis

## Target Market: {geography}
- Market size in this geography: $X
- Customer density: {how concentrated are target customers}
- Competitive intensity: Low / Medium / High
- Regulatory considerations specific to this geography

## Beachhead Market Recommendation
- Recommended first market: {specific city/region/segment}
- Why this market first: {density of target customers, lower competition, founder network, etc.}
- What winning here proves: {validation milestones}
- Expansion path: {market 1} → {market 2} → {market 3}

## Market Entry Risks
- [Risk specific to this geography]
- [Risk specific to this geography]

## Data Gaps
- [Geographic data you couldn't find]

Save to: {project-name}/01-discovery/raw/geographic.md

Verification Agent Protocol

After synthesis completes, spawn a Verification Agent (V1) that audits all deliverables for consistency, accuracy, and completeness. This step catches issues that individual agents and synthesis can miss.

When to Run

• After synthesis is complete and all deliverable files are written
• Before the next phase begins (e.g., before Phase 3.5 Research Gate in startup-design)
• Uses one agent: V1: Verification

Agent Task

The V1 agent reads ALL deliverable files (not raw files) and checks them against the rules below. It produces a verification-report.md in the project directory.

Universal Checks

These apply to every skill in the startup plugin:

1. Claims Without Source

Every quantitative claim must have a data label: [Data], [Estimate], [Assumption], or [Opinion]. Flag any number, percentage, or factual assertion without a label.

2. Internal Contradictions

Cross-check numbers and statements across deliverable files. Flag when:

• The same metric appears with different values in two files
• A claim in one file contradicts a claim in another
• Confidence ratings disagree (e.g., "High confidence" in one file, different data in another suggests Medium)

3. Confidence Rating Consistency

Verify that confidence ratings match the evidence:

• A claim with only one Tier 3 source cannot be rated High
• A claim with multiple Tier 1 sources should not be rated Low
• Every major section must have a confidence rating

4. Data Gaps Declared

Every deliverable must have a Data Gaps section. Flag:

• Files missing the Data Gaps section entirely
• Sections where data is clearly thin but no gap is declared
• Gaps mentioned in raw files that didn't make it into the synthesized deliverables

5. Flags Present

Every deliverable must end with Red Flags and Yellow Flags sections. Flag:

• Files missing these sections
• Files with "No flags identified" where the content clearly contains risks

6. Stale Data

Flag any data point older than 18 months that isn't marked as potentially outdated.

7. Duplicate Sources

Flag when the same source is used as "independent corroboration" in multiple places. Two claims both citing the same blog post don't have independent verification.

Skill-Specific Checks: startup-design

In addition to the universal checks above, verify:

Cross-Phase Consistency

• Strategy reflects market data: Do the Lean Canvas, positioning, and GTM in Phase 4 reference specific findings from Phase 3? Flag strategy claims that have no research backing.
• Product reflects customer pains: Does the MVP definition (Phase 6) address the top pains identified in target-audience.md? Flag features that don't map to any validated customer need.
• Financial reflects business model: Do the revenue projections (Phase 7) use the pricing and unit economics from market-analysis.md and business-model.md? Flag projection assumptions that contradict research data.
• Validation covers key risks: Does the risk analysis (Phase 8) address the Red Flags and data gaps surfaced in earlier phases? Flag risks that were identified in research but missing from validation.

Numerical Consistency

• TAM/SAM/SOM numbers must be consistent across market-analysis.md, lean-canvas.md, and revenue-model.md
• Pricing references must match between competitor-landscape.md and business-model.md
• Customer segment descriptions must be consistent between target-audience.md, lean-canvas.md, and mvp-definition.md

Output: verification-report.md

# Verification Report: {project-name}
*Generated: {date}*

## Summary
- **Critical issues:** {count}
- **Warnings:** {count}
- **Info:** {count}

## Critical Issues
Issues that could mislead decision-making. The process pauses here for user review.

### {Issue title}
- **File(s):** {affected files}
- **Section:** {section name}
- **Problem:** {description}
- **Suggested fix:** {how to resolve}

## Warnings
Issues that reduce quality but don't block decisions.

### {Issue title}
- **File(s):** {affected files}
- **Problem:** {description}
- **Suggested fix:** {how to resolve}

## Info
Minor improvements and observations.

- {observation}
- {observation}

## Verification Checklist
- [ ] All quantitative claims labeled
- [ ] No internal contradictions found
- [ ] Confidence ratings consistent with evidence
- [ ] Data gaps declared in all deliverables
- [ ] Red/Yellow flags present in all deliverables
- [ ] No stale data unmarked
- [ ] No duplicate-source false corroboration
- [ ] Strategy reflects market data (cross-phase)
- [ ] Product reflects customer pains (cross-phase)
- [ ] Financial reflects business model (cross-phase)
- [ ] Validation covers identified risks (cross-phase)

Flow Control

• If Critical issues > 0: Pause. Show the user: "Verification found {N} critical issues that could affect decision-making." List them. Ask: "Should I fix these before continuing, or proceed as-is?"
• If only Warnings/Info: Show a one-line summary: "Verification complete: {N} warnings, {N} info items. See verification-report.md for details." Continue to next phase.