3 paste-ready prompts. Take your text-only MVP and add one more sense. Fresh signals from Super AI 2026 baked in.
"Save this as `[name].md` in my project folder."
Optional. Run ONCE at the top of your chat. Claude introspects what it knows about your project (Day 7 outputs, Lovable URL, MVP cut) and confirms before auto-filling brackets in P01–P03.
# ROLE
You are my Build Sprint multi-modal scope partner for the next 40 minutes. You'll help me pick the right modality pair, wire it into Lovable, and audit cost.
# GOAL
Before we start: read what you know about my project from prior context — Day 7 PRD, MVP cut (1-3 features), user journey, Lovable URL, QA report, any cost work. Then confirm with me.
# OUTPUT
Restate, in this exact format:
- **Product (one line):** [your understanding]
- **Target user (specific):** [your understanding]
- **The 1-3 MVP features:** [your understanding]
- **Live Lovable URL:** [your understanding]
- **Current modalities used:** [likely "text only"]
- **My scariest modality (if known):** [your understanding]
End with: "Reply 'yes' if accurate, or correct any line. I'll auto-fill these in P01–P03 for the rest of the session."
# DELIVERABLE
After confirmation, tell me: "Save this confirmed context as `multimodal_context.md` in my project folder."
# SELF-CHECK
- ✓ Did I list ALL 6 fields above?
- ✓ Did I use the user's actual words where possible?
- ✓ Am I asking for confirmation, not assuming?
A panel of three senior multi-modal product designers generates 3 modality-pair candidates for YOUR product · scores each on shipability/wow/cost/journey-fit · picks the winner with reasoning · gives you the v1.5 architecture.
# ROLE
You are a panel of three senior multi-modal product designers who've shipped at scale at top consumer AI companies. You think in causal chains: which modality creates the strongest user moment? Which adds the most cost? Which can a Build Sprint cohort ship in 48 hours?
# GOAL
For my product, generate 3 different modality-pair candidates. Score each on 4 axes. Pick the winner with reasoning.
# CONTEXT (Claude reuses prior context — fill only what's needed)
NOTE · Claude already knows your PRD, MVP cut, user journey, Lovable URL from Day 7. Fill what's new.
- The 1-3 MVP features (from Day 7 Prompt 02): [FEATURES OR "USE PROJECT CONTEXT"]
- Target user: [USER OR "USE PROJECT CONTEXT"]
- Live Lovable URL: [URL]
- Modalities currently used (likely just text): [E.G. "TEXT ONLY"]
- Days to ship the multi-modal upgrade: 2 (deadline = tomorrow's hackathon demo)
- Modalities I'm scared of: [FROM THE EARLIER HANDS-UP]
# CONSTRAINTS
- 3 pair candidates · each pair is exactly 2 modalities (not 3, not 1)
- One pair MUST include my scariest modality (we don't avoid it)
- Each scored on 4 axes (1–5): shipability in 2 days · wow factor · added cost · journey fit
- The winner is picked by panel consensus, not highest score
# SUPER AI CONTEXT — bake this into your reasoning
At Super AI 2026, the cohort heard 3 signals worth weighing:
1. Voice is the new mobile — sub-150ms TTFB · real revenue · the modality with biggest moat right now
2. Video gen cost dropped ~40% in 6 months — if you wrote off video for cost, re-evaluate
3. Image editing models (Flux Kontext class) are the next image wave — worth scoring as "image" for B2C products
When scoring "wow factor", account for these shifts.
# OUTPUT FORMAT
**🎯 The 3 Pair Candidates**
**Pair A · [Modality 1] + [Modality 2]**
- The user experience this enables (1 sentence)
- The "wow per second" moment (what they see in 0–10 sec)
- Shipability: __/5 · Wow: __/5 · Cost: __/5 · Journey fit: __/5
**Pair B · [Modality 1] + [Modality 2]**
- Same structure
**Pair C · [Modality 1] + [Modality 2]** (MUST include my scariest modality)
- Same structure
**🏆 The Winner**
The panel picks: Pair [A/B/C]
- Reasoning (3 sentences max)
- One thing each panelist would change about the runner-up
**⚡ The v1.5 architecture (winner only)**
- Step 1 (LLM does): [action]
- Step 2 ([modality 2] does): [action]
- Step 3 (user sees): [the share moment]
**🚨 Tomorrow's risks**
- 3 specific failure modes (latency · cost spike · API failure · UI confusion)
- < 30 sec recovery for each
# DELIVERABLE
Tell Claude: "Save this as `modality_pair.md` in my project folder."
# SELF-CHECK
- ✓ Exactly 2 modalities in each pair (not 3, not 1)?
- ✓ Pair C includes my scariest modality?
- ✓ Winner buildable in 2 days?
- ✓ Did I factor in the Super AI signals when scoring wow?
- ✓ Did I (Claude) save `modality_pair.md`?
Paste-ready Lovable prompt. Takes your chosen modality pair → updates your 3-screen MVP · adds Supabase generations + rate_limit tables · sets up API key handling via edge functions · publishes. Built-in fallback for APIs Lovable can't connect to directly.
# ROLE
You are a senior Lovable + multi-modal engineer who has wired ElevenLabs, Flux, Luma, and HeyGen APIs into 100+ Lovable apps. You build on the first try. You name the cheapest fitting model. You wire rate-limits before launch, not after the surprise bill.
# GOAL
Take my existing Lovable MVP (3 screens · text-only · auth via Supabase) and add my chosen modality pair. Output: paste-ready Lovable prompt I can drop in immediately.
# CONTEXT (Claude reuses prior context)
- Existing Lovable URL: [URL OR "USE P05 OUTPUT"]
- Chosen modality pair (from Prompt 01): [E.G. "TEXT + VOICE" OR "USE modality_pair.md"]
- For each new modality, the tool I want to use: [E.G. "VOICE = ELEVENLABS · IMAGE = FLUX"]
- API keys I have: [E.G. "CLAUDE, FLUX. NEED: ELEVENLABS"]
- Free-tier signup tolerance: [E.G. "OK TO ADD 1 NEW VENDOR ACCOUNT"]
# SUPABASE SCHEMA UPDATE — DO THIS FIRST
Add to my existing Supabase project:
generations table (tracks usage + cost)
- id uuid primary key
- user_id uuid references auth.users
- modality text (e.g., 'image', 'voice', 'video')
- vendor text (e.g., 'flux', 'elevenlabs')
- cost_cents integer
- inputs jsonb
- output_url text
- created_at timestamptz default now()
rate_limit table (enforces per-user caps)
- user_id uuid primary key
- generations_today integer default 0
- last_reset_at timestamptz default now()
Add RLS: users read their own rows · cannot write to rate_limit (writes happen via edge function only).
# BUILD FLOW — exactly these steps
Screen 2 update (the Working screen)
- Add UI for the new modality's input (file upload · text · voice record button)
- On submit: check rate_limit table · if over cap, show friendly "you're at your daily limit"
- Otherwise: call the modality API · insert row in generations table with cost
- Update rate_limit counter
Screen 3 update (the Aha moment)
- Display the new modality output prominently (image · audio player · video player)
- "Download" button + "Copy share link" button (the viral loop)
API key handling
- Store all API keys in Supabase Edge Function secrets (NEVER in frontend)
- Each modality call goes through an edge function (e.g., /generate-image, /generate-voice)
- Edge function checks rate limit · makes the call · inserts cost row · returns output URL
# DESIGN RULES (non-negotiable)
- Mobile-first (390px baseline)
- Light theme · accent matching original landing page
- Loading state on every modality call (these take 2–30 sec)
- Error state with specific message (not "Something went wrong")
# PUBLISH
1. Wait for Lovable build to complete
2. Test in Lovable preview · submit a test action
3. If Lovable adds a 4th screen → reply: "Reduce to 3 screens. Add modality to Screen 2."
4. Click Publish (top-right rocket)
5. Wait 10-15 sec for live URL
6. Test on phone · confirm cost shows in Supabase generations table
7. Save live URL as `live_url_v15.txt`
# DELIVERABLE
Tell Claude: "Save this build summary as `multimodal_wireup.md` in my project folder." Include: live URL, new schema, API keys needed, any fallback edge functions created.
# SELF-CHECK — answer YES before "Done"
- ✓ Are modality calls going through edge functions (not frontend keys)?
- ✓ Is rate-limit enforced before each call?
- ✓ Is cost inserting into generations table?
- ✓ Does the Aha screen show the output + share button?
- ✓ Is it published to a live URL?
- ✓ Did I resist building a 4th screen?
- ✓ Did I (Claude) save `multimodal_wireup.md`?
End with: live URL + Supabase dashboard link.
supabase.functions.invoke('generate-voice', { body })cache_control: { type: "ephemeral" } on stable parts of your prompt. This alone will move your cost line in Prompt 03.
For your newly multi-modal app, Claude projects costs at 100 / 1K / 10K users. Names 3 specific cost-saving moves. Gives you a free-tier strategy that keeps the first 100 users under $50. Includes a hard kill-switch if monthly spend exceeds your budget ceiling.
# ROLE
You are a senior ML infrastructure engineer who has shipped to millions of users at major AI labs. You think in cost per call · cost at scale · cost of failure. You also have a finance-aware PM brain — cofounders fold not when the product fails but when the bill hits.
# GOAL
For my newly multi-modal app, project costs at 100 / 1,000 / 10,000 monthly users. Name 3 specific cost-saving moves. Give me a free-tier strategy that lets me onboard the first 100 without burning $200.
# CONTEXT (Claude reuses prior context)
- My multi-modal stack (from P01 + P02): [E.G. "CLAUDE SONNET + ELEVENLABS + SUPABASE" OR "USE multimodal_wireup.md"]
- Average actions per user per month: [E.G. "10 ACTIONS/MO IN MVP"]
- Each action calls these APIs: [E.G. "1 LLM CALL + 1 IMAGE GEN"]
- My current free tier limits per user: [E.G. "3 ACTIONS/DAY"]
- My monthly budget burn ceiling (above which I pause growth): [E.G. "$500"]
# CONSTRAINTS
- Project costs at EXACTLY 100, 1K, 10K users
- Cost-saving moves must be specific implementations (not "use a smaller model")
- Free-tier strategy must keep first 100 users under $50 total
- Honest about which moves are real vs theoretical
# SUPER AI CONTEXT — factor these into your projections
- Prompt caching (Anthropic): 80%+ savings on long-context calls. If we're not using it, recommend it as Move A.
- Cartesia vs ElevenLabs: Cartesia is 5x cheaper at near-equal quality for non-cloned voices. If we're using ElevenLabs for non-emotional use, recommend swap as Move B.
- Open-source multimodal small models (Llama 4 vision, DeepSeek): catching up at 1/10 cost. Worth mentioning as a v2 consideration.
# OUTPUT FORMAT
**💸 Cost Projection · Monthly**
| Users | LLM | Image | Voice | Video | Total | Per-user |
|-------|-----|-------|-------|-------|-------|----------|
| 100 | $X | $X | $X | $X | $X | $X |
| 1,000 | ... | ... | ... | ... | ... | ... |
| 10,000| ... | ... | ... | ... | ... | ... |
**📊 The breakdown**
- 80% of cost comes from: [specific modality + call type]
- The single most expensive call per user: [specific]
- The model swap that saves the most: [specific recommendation]
**🔥 The 3 cost-saving moves**
1. **Move A** — [specific cache key strategy OR specific cheaper model OR specific tier change]
2. **Move B** — [specific change]
3. **Move C** — [specific change]
**🆓 Free-tier strategy**
- First 100 users: limit to [N actions/week]
- Estimated total spend at 100 users: $X
- Convert to paid tier when: [specific trigger]
- Paid tier offering: $[X]/mo for unlimited
**🚨 The kill-switch**
If monthly spend exceeds my $500 budget, I should:
1. [specific action 1 — e.g., disable video generation tier]
2. [specific action 2 — e.g., move all new signups to waitlist]
3. [specific action 3 — e.g., switch ElevenLabs → Cartesia]
# DELIVERABLE
Tell Claude: "Save this as `cost_audit.md` in my project folder." Reference it every Monday before deciding to scale or hold.
# SELF-CHECK
- ✓ Did I project costs at exactly 100 / 1K / 10K?
- ✓ Are the 3 cost moves SPECIFIC to this stack?
- ✓ Does the free-tier strategy keep first 100 under $50?
- ✓ Is there a hard kill-switch with 3 named actions?
- ✓ Did I factor in the Super AI signals (caching, Cartesia, OS models)?
- ✓ Did I (Claude) save `cost_audit.md`?