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Build a specification-first Digital FTE that orchestrates accumulated intelligence from Lessons 1-7. Learn to compose execution skills into production-ready agents, validate against specifications, and position for monetization.
Passed 20 of 23 test cases with the skill, and 12 of 23 without it.
and 7 more in the full report
8 fixed12 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
Draft a go-to-market positioning statement for a sales pipeline analysis skill named pipeline-inspector targeting SaaS sales directors. Standard templates use generic slogan formats like 'The best tool for sales'. Follow the single-sentence structured positioning format.
| Checked | Without skill | With skill |
|---|---|---|
| Uses the template '[Skill name] is the [category] for [audience] that [specific benefit]' | Missed | Passed |
The instructions your model reads when the skill loads.
You've now learned every pattern this chapter teaches: persona design (Lesson 1), skill composition (Lesson 2), MCP-wrapping (Lessons 3-4), script execution (Lessons 5-6), and workflow orchestration (Lesson 7).
But learning patterns is not the same as building products.
This capstone is different. You're not following steps or solving a predetermined problem. You're doing what every AI-native entrepreneur must do: articulate a problem clearly enough that AI can build a solution to it, then validate that solution works in the real world.
You're building a specification-first Digital FTE—a complete, shippable execution skill that solves a real customer problem. This skill will orchestrate the accumulated intelligence from all previous lessons, handle production edge cases, and be ready to monetize.
In the agent economy, the developers who win are those who can:
This capstone exercises all five. You're not learning to code faster. You're learning to build products that customers pay for.
Before any implementation, define what problem you're solving for whom.
Choose a domain where you have expertise or strong interest. This skill should solve a real problem you've experienced or observed:
Domain Categories:
Real Examples:
test cases passed, vs 12 / 23 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.