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PLAID Intake Guide

This guide contains the complete question bank for the PLAID vision intake. For each question, you’ll find: the question text, context for why it matters, whether to offer AI suggestions, and how to generate those suggestions.

How to Use This Guide

For each AI-assisted question:

  1. Ask the question (include the context sentence)
  2. Generate 3 suggestions using the generation prompt provided
  3. Present them as numbered options (1, 2, 3)
  4. Include “Or tell me in your own words” as a final option
  5. Carry the answer forward — every subsequent suggestion must account for it

Important: The opening question (“What do you want to build?”) may have already provided answers to some of these questions. Before asking each question, check what you already know from the conversation so far. Skip or pre-fill any question the founder has already answered. When a question was partially answered, say “You mentioned [x] — I want to dig deeper on that” rather than asking from scratch.

Suggestion quality rules:

  • Suggestions must be substantively different from each other — not rephrased versions of the same idea
  • Be specific and concrete, not generic
  • Build naturally on what the founder has already shared
  • Write in the founder’s voice (first person where appropriate)
  • Get better over time — by question ~20, suggestions should be highly personalized

Section 1: About You

Q1.1: What’s your name?

  • AI suggestions: None — direct input
  • Ask: “First, what should I call you?”

Q1.2: What’s your area of expertise?

  • AI suggestions: None — direct input
  • Ask: “What’s your professional background or area of expertise? This helps me tailor suggestions to your strengths.”

Q1.3: Your background story

  • AI suggestions: Yes
  • Ask: “Give me the quick version — what’s your journey been and what led you to wanting to build something?”
  • Generate 3 suggestions using this approach: Given this person’s name ({name}) and expertise ({expertise}), generate 3 different narrative framings of their background that would resonate in a founder context. Each should be 2–3 sentences. Make them substantively different — e.g. one emphasizing domain expertise, one emphasizing a personal pain point they experienced, one emphasizing an opportunity they spotted in their field.

Section 2: Your Purpose

Q2.1: Who do you want to help?

  • AI suggestions: Yes
  • Ask: “Who is the person whose life gets better because your product exists?”
  • Generate 3 suggestions using this approach: Based on {name}’s expertise in {expertise} and background ({background}), suggest 3 different target audiences. Be specific — not “small businesses” but “solo freelance designers earning $50–150k who manage their own client pipeline.” Each should be a meaningfully different audience that makes sense given their background.

Q2.2: What problem are you solving?

  • AI suggestions: Yes
  • Ask: “What’s the pain point? What are these people struggling with today?”
  • Generate 3 suggestions using this approach: Given {name} wants to help {whoYouHelp} and has background in {expertise}, suggest 3 specific problems this audience faces. Each should be concrete and emotionally resonant — describe the frustration, not just the gap. Make them substantively different problems, not variations of the same one.

Q2.3: What transformation do you want to see?

  • AI suggestions: Yes
  • Ask: “If your product works perfectly, what changes for these people? What does their life look like after?”
  • Generate 3 suggestions using this approach: Given {whoYouHelp} currently struggles with {problemYouSolve}, suggest 3 transformation statements. Each should describe a before→after shift that’s specific and measurable. Frame as outcomes, not features.

Q2.4: Why are you the right person to build this?

  • AI suggestions: Yes
  • Ask: “What about your background or experience makes you uniquely positioned to solve this problem?”
  • Generate 3 suggestions using this approach: Connect {name}’s background ({background}) and expertise ({expertise}) to the problem of {problemYouSolve} for {whoYouHelp}. Generate 3 different “founder-market fit” narratives. Each should highlight a different aspect of why this person is credible for this problem.

Section 3: Your Product

Q3.1: What do you want to call it?

  • AI suggestions: Yes
  • Ask: “What’s the name? Don’t overthink it — you can always change it later.”
  • Generate 3 suggestions using this approach: Based on the purpose (helping {whoYouHelp} with {problemYouSolve}) and the desired transformation ({desiredTransformation}), suggest 3 product name ideas. Mix styles: one descriptive, one abstract/evocative, one punchy/short. Avoid generic AI-sounding names.

Q3.2: One-liner description

  • AI suggestions: Yes
  • Ask: “How would you describe this in one sentence to someone at a party?”
  • Generate 3 suggestions using this approach: Generate 3 one-liner descriptions for {productName} using the format “[Product] helps [who] [do what] by [how].” Each should emphasize a different benefit angle. Keep under 15 words each.

Q3.3: How would someone use it?

  • AI suggestions: Yes
  • Ask: “Walk me through the core experience. A user opens the app — then what?”
  • Generate 3 suggestions using this approach: Describe 3 different core user flow narratives for {productName}. Each should be a 3–4 sentence story of a user’s first meaningful interaction. Start with the trigger (what brings them to the product), the core action, and the payoff. Make them feel tangible and specific.

Q3.4: Key capabilities

  • AI suggestions: Yes
  • Ask: “What are the 3–5 main things this product can do?”
  • Generate 3 suggestions using this approach: Based on {productName} ({oneLiner}) and the core flow ({howItWorks}), suggest 3 different capability sets. Each set should be 3–5 capabilities listed as short phrases. Vary the scope — one minimal (ruthlessly simple), one balanced, one ambitious.

Q3.5: Platform target

  • AI suggestions: None — list choice
  • Ask: “Where will people use this?”
  • Options: Web app, Mobile app, Desktop app, Cross-platform

Q3.6: What makes this different?

  • AI suggestions: Yes
  • Ask: “What makes this stand apart from what already exists?”
  • Generate 3 suggestions using this approach: Based on {productName} solving {problemYouSolve} for {whoYouHelp} with capabilities ({keyCapabilities}), suggest 3 differentiation positioning statements. Use the format: “Unlike [existing solutions], {productName} [does x] because [y].” Infer likely competitors from the problem space. Each should highlight a genuinely different competitive angle.

Q3.7: What’s the magic moment?

  • AI suggestions: Yes
  • Ask: “What’s the ‘aha’ moment? The interaction where a user first feels the value and wants to tell someone about it?”
  • Generate 3 suggestions using this approach: Describe 3 “magic moment” scenarios for {productName}. Frame each as a mini-story: “The user does [action], and then [something delightful happens] because [why this product uniquely enables it].” Must be specific to this product — not generic (“onboarding is smooth”). Each should highlight a different aspect of the product’s value.

Section 4: Your Audience

Q4.1: Primary user persona

  • AI suggestions: Yes
  • Ask: “Describe your ideal first user. Who are they, what’s their day like?”
  • Generate 3 suggestions using this approach: Based on {whoYouHelp} and the problem {problemYouSolve}, generate 3 detailed persona sketches. Each should be 2–3 sentences covering: name, role, daily reality, and the specific frustration that makes them a perfect early adopter. Make them feel like real people.

Q4.2: Secondary users

  • AI suggestions: Yes
  • Ask: “Who else would use this, besides your primary user?”
  • Generate 3 suggestions using this approach: Given the primary user ({primaryUser}) and product ({productName}: {oneLiner}), suggest 3 secondary user groups. Each should have a distinct relationship to the product — e.g. a decision-maker who approves purchase, a collaborator who uses it alongside the primary user, a beneficiary who receives value indirectly. Explain why they’d care.

Q4.3: Current alternatives

  • AI suggestions: Yes
  • Ask: “What do people use today to solve this problem? Include hacky workarounds and ‘just living with it.’”
  • Generate 3 suggestions using this approach: For the problem of {problemYouSolve} faced by {whoYouHelp}, identify 3 sets of current alternatives. Each set should include 2–3 specific tools/approaches. Include at least one direct competitor, one adjacent tool people misuse for this purpose, and one manual workaround (spreadsheets, pen and paper, just not doing it).

Q4.4: Frustrations with alternatives

  • AI suggestions: Yes
  • Ask: “What’s broken about the current options?”
  • Generate 3 suggestions using this approach: Given the alternatives ({currentAlternatives}), generate 3 different frustration narratives. Each should focus on a different pain dimension: one functional (it doesn’t work well), one emotional (it feels bad to use), one practical (it costs too much time/money). Be specific and vivid.

Section 5: Business Intent

Q5.1: Revenue model

  • AI suggestions: None — list choice
  • Ask: “How will this make money?”
  • Options: Subscription (monthly/annual), Freemium (free + paid tiers), One-time purchase, Marketplace (take a cut), Ad-supported, Free (figure it out later)

Q5.2: 90-day success

  • AI suggestions: Yes
  • Ask: “What does success look like 90 days from now? Be specific.”
  • Generate 3 suggestions using this approach: For {productName} ({oneLiner}) with a {revenueModel} revenue model, suggest 3 realistic 90-day milestone sets. Each should include 2–3 specific, measurable goals (e.g. “50 active users”, “first paying customer”, “featured in one industry newsletter”). Range from conservative to ambitious.

Q5.3: 6-month vision

  • AI suggestions: Yes
  • Ask: “Where is this in 6 months if everything goes well?”
  • Generate 3 suggestions using this approach: Building on the 90-day goals ({initialGoal}), suggest 3 six-month vision statements for {productName}. Each should describe a concrete state of the business — users, revenue, features, reputation. Make them feel achievable but exciting.

Q5.4: Constraints

  • AI suggestions: Yes
  • Ask: “What are your constraints? Time, money, skills, other commitments?”
  • Generate 3 suggestions using this approach: For a founder with {expertise} background building {productName} ({oneLiner}), suggest 3 realistic constraint sets. Include common ones for this type of product: budget, time commitment (part-time vs full-time), technical skill gaps, regulatory concerns. Be honest, not discouraging.

Q5.5: Go-to-market approach

  • AI suggestions: Yes
  • Ask: “How do you want to get this in front of people?”
  • Generate 3 suggestions using this approach: For {productName} targeting {whoYouHelp} with a {revenueModel} model, suggest 3 go-to-market approaches ranging from lean/organic to ambitious. Examples: build in public on Twitter/X, Product Hunt launch + targeted community outreach, content-led SEO, community-first, partnerships. Each should include a brief rationale for why it fits THIS specific product and audience.

Section 6: The Feeling

Q6.1: Brand personality

  • AI suggestions: Yes
  • Ask: “If your product were a person, how would you describe their personality?”
  • Generate 3 suggestions using this approach: Based on {productName}’s purpose ({oneLiner}), audience ({primaryUser}), and the transformation ({desiredTransformation}), suggest 3 brand personality archetypes. Each should be 3–4 adjectives with a one-sentence description. Make them genuinely different vibes — e.g. “warm expert”, “sharp minimalist”, “playful rebel.”

Q6.2: Visual mood

  • AI suggestions: Yes
  • Ask: “What should this feel like visually? Think colors, energy, aesthetic.”
  • Generate 3 suggestions using this approach: Based on brand personality ({brandPersonality}) and audience ({primaryUser}), suggest 3 visual mood directions. Each should describe a palette tendency, typography feel, and overall energy. Be evocative — reference real-world aesthetics people can picture (e.g. “Notion-like calm”, “Linear-inspired precision”, “Duolingo playfulness”).

Q6.3: Tone of voice

  • AI suggestions: Yes
  • Ask: “How should this product talk to its users?”
  • Generate 3 suggestions using this approach: Based on brand personality ({brandPersonality}), suggest 3 tone of voice profiles. Each should include the tone name, a one-sentence description, and 2 example phrases showing how the product would communicate (e.g. an error message, a success state, a CTA). Make the examples concrete and noticeably different from each other.

Q6.4: Anti-patterns

  • AI suggestions: Yes
  • Ask: “What should this product NEVER feel like?”
  • Generate 3 suggestions using this approach: Based on brand personality ({brandPersonality}) and visual mood ({visualMood}), suggest 3 anti-pattern sets. Each should be 3–4 things the product should actively avoid — specific enough to be actionable (not “don’t be boring” but “never use corporate stock photography” or “avoid dense paragraph-heavy onboarding flows”).

Section 7: Tech Stack

This section uses a different format. Instead of 3 plain text suggestions, present a structured comparison table for each layer of the stack.

Comparison table format

For each tech stack question, present options like this:

Here are 3 options for your [layer]:

**1. [Name] ✦ Recommended**
[One sentence: what it is]
✓ [Pro 1]  ✓ [Pro 2]
✗ [Con 1]  ✗ [Con 2]

**2. [Name]**
[One sentence: what it is]
✓ [Pro 1]  ✓ [Pro 2]
✗ [Con 1]  ✗ [Con 2]

**3. [Name]**
[One sentence: what it is]
✓ [Pro 1]  ✓ [Pro 2]
✗ [Con 1]  ✗ [Con 2]

Or tell me what you'd prefer — I can provide guidance for any tool.

If the user picks “something else” and names a specific tool, generate a brief assessment (what it is, how it fits this product, any gotchas) and accept their choice.

See TECH-STACK-OPTIONS.md for the default comparison data for common stacks. Adapt recommendations based on the specific product’s needs.

Q7.1: Frontend framework

  • Format: Comparison table
  • Ask: “What should the frontend be built with?”
  • Recommendation logic: For web apps → lean toward Next.js (best ecosystem, great with AI coding tools). For mobile → lean toward Expo/React Native. For desktop → lean toward Electron (most mature, largest ecosystem) or Tauri (smaller bundles, lower memory, Rust-based). For cross-platform spanning web + desktop → recommend Next.js for the web layer plus Electron or Tauri for the desktop shell. For cross-platform spanning mobile + desktop → recommend Flutter (single codebase across all surfaces). Adjust based on product complexity and real-time needs. If the product is highly real-time and Convex is the backend, note that Next.js + Convex has excellent integration.

Q7.2: Backend

  • Format: Comparison table
  • Ask: “What about the backend?”
  • Recommendation logic: Lean toward Convex for most cases. Highlight: real-time reactivity, no backend boilerplate, built-in auth & file storage, TypeScript-native, excellent DX for solo developers. Recommend Supabase if heavy relational data is central. Recommend Node/Express + DB only if the founder has strong backend experience and wants full control.

Q7.3: Database

  • Format: Comparison table
  • Ask: “And the database?”
  • Recommendation logic: If Convex was chosen for backend → strongly recommend Convex's built-in database (document-relational, automatic indexing, ACID transactions). If Supabase was chosen → strongly recommend Supabase's managed PostgreSQL. Otherwise → recommend PostgreSQL for relational data. For mobile apps that only need local storage (offline tools, utilities, calculators), recommend None — the app can use on-device storage (AsyncStorage, SQLite, UserDefaults) and skip the backend database entirely. For desktop apps that are local-only tools (editors, utilities, productivity apps without sync), recommend None — the app can use on-device storage (SQLite via better-sqlite3, electron-store, or Tauri's filesystem APIs) and skip the backend database.

Q7.4: Auth provider

  • Format: Comparison table
  • Ask: “How should users sign in?”
  • Recommendation logic: If Convex backend → recommend Convex Auth (native integration, zero config) or Clerk (richer UI components, social login). If Supabase backend → recommend Supabase Auth. Otherwise → Clerk or Auth.js/NextAuth depending on backend. For mobile or desktop apps that don't need user accounts (utilities, offline tools, single-player experiences, local-only desktop tools), recommend None — the app works without sign-in and can add auth later if needed.

Q7.5: Payments

  • Format: Comparison table
  • Ask: “How will you handle payments?”
  • Skip if: Revenue model is “Free (figure it out later)” — tell the user “We’ll skip payments for now since you’re figuring out the revenue model. You can always add this later.”
  • Recommendation logic:
    • For web apps: Lean toward Polar for SaaS/digital products. Present Stripe (most flexible, largest ecosystem) and Lemon Squeezy (merchant of record, handles global tax) as alternatives.
    • For mobile apps: Lean toward RevenueCat for subscription-based apps (abstracts Apple/Google billing into one SDK). If the founder wants to optimize paywall conversion, recommend pairing with Superwall. If the app doesn't need payments, recommend None and note they can add it later.
    • For desktop apps: Use the web payment options — Polar, Stripe, or Lemon Squeezy. Desktop apps are distributed outside app stores so there's no mandatory in-app purchase requirement. If the app doesn't need payments, recommend None.
    • If the product doesn't need payments at all (utility app, free tool), recommend None — no shame in shipping without monetization and adding it later.

Section 8: Tooling

Q8.1: Coding agent

  • Format: List choice
  • Ask: “Last one — what coding agent will you use to build this?”
  • Options: Claude Code, Cursor, Windsurf, GitHub Copilot, Other
  • If “Other”: ask “What’s the tool called?”

After Intake Is Complete

  1. Assemble all answers into a Vision object following the schema in VISION-SCHEMA.md
  2. Save as vision.json in the project root
  3. Confirm with the user: list a brief summary of the key decisions (product name, audience, stack choices)
  4. Offer to begin document generation