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From bette-think
Calculates AI feature costs, challenges necessity, models economics at scale, and provides verdicts with optimizations using ai-cost-analyzer agent.
How this skill is triggered — by the user, by Claude, or both
Slash command
/bette-think:ai-cost-checkThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Before you build an AI feature, answer two questions:
Before you build an AI feature, answer two questions:
Most PMs skip #1 and regret #2 later.
When this skill is invoked, start with:
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AI COST CHECK
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AI features have marginal costs that scale with usage.
Model this BEFORE building, not after launch.
What AI feature are you considering?
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/ai-cost-check [feature-name]
Examples:
/ai-cost-check "product recommendations" - Calculate recommendation costs/ai-cost-check "email composer" - Model email generation economics/ai-cost-check --compare - Compare cost across different modelsAI products have marginal costs that scale with usage. Every user interaction costs money. Model this BEFORE building, not after launch when you're hemorrhaging cash.
| AI Cost as % of Revenue | Status | Recommendation |
|---|---|---|
| <15% | Sustainable | Build it |
| 15-30% | Viable | Build with optimization plan |
| >30% | Unsustainable | Don't build (or fundamentally rethink) |
FEATURE DETAILS:
- Model: GPT-4 Turbo
- Calls per recommendation: 1
- Input: 1,500 tokens
- Output: 300 tokens
COST BREAKDOWN:
Per request: $0.024
Per user/month: $2.16
| Scale | Monthly Cost | Your Revenue | AI % of Revenue |
|-------|-------------|--------------|-----------------|
| 100 | $216 | $2,000 | 10.8% |
| 10K | $21,600 | $200,000 | 10.8% |
VERDICT: Sustainable at 10.8% of revenue
OPTIMIZATION PATHS:
1. Caching (saves 40-60%): $8,640/month at 10K users
2. Model selection (saves 70%): Use GPT-3.5 for simple cases
| Model | Input | Output |
|---|---|---|
| GPT-4 Turbo | $0.01/1K | $0.03/1K |
| GPT-4o | $0.005/1K | $0.015/1K |
| GPT-3.5 Turbo | $0.0005/1K | $0.0015/1K |
| Claude 3.5 Sonnet | $0.003/1K | $0.015/1K |
| Claude 3 Haiku | $0.00025/1K | $0.00125/1K |
/ai-health-check - Full pre-launch readiness audit/four-risks - Includes viability (business model) risk/pmf-survey - Validate willingness to payKey insight: "Most AI features are solutions looking for problems. Validate the problem before modeling costs."
npx claudepluginhub breethomas/bette-think --plugin bette-thinkUse this skill when the user asks specifically about "how to monetize AI features", "should AI be a separate tier", "pricing for AI capabilities", "how to charge for AI", "AI add-on vs. bundle", "AI feature pricing strategy", or is adding AI capabilities to an existing product and wants to decide how to monetize them. This is a specialized version of pricing-review focused on AI feature economics.
Guides adding AI-powered features to SaaS products including LLM API integration, RAG, AI assistants, prompt engineering, API selection, and cost management for scalable shipping.
Audits pre-launch AI features across 6 dimensions—model selection, data quality, cost, monitoring, failure UX, optimization—grading readiness and blocking shipment of broken products.