AI Fluency - Communication, Context & Model Mastery · Use AI
Intent Engineering: From Outputs to Outcomes
Define what AI systems owe your business - not just what they generate. Write outcome contracts for every AI agent you deploy, with boundaries, health metrics, and stop rules.
6 lessons · 210 minutes
Before starting: Completed The Three-Layer AI Communication Stack · At least one AI-assisted workflow already in daily or pilot use
Start courseWhat you walk away with
- Write an agent spec stating the outcome owed, boundaries, health metrics, and stop rules
- Define acceptance criteria and escalation conditions in plain business language
- Version-control AI specs so they change like any other documented business process
- Deploy one specced agent end to end on a real business workflow and measure it against its contract
- A tested prompt or customer-facing workflow you can run this week. Every artifact saves to your workspace, so you keep it after the course ends.
- A knowledge-check quiz and a visual walkthrough inside every one of the 6 lessons, about 4 hours of guided work.
- Most lessons close with a checklist, template, or do-it-this-week task, so progress shows up in your work, not just in the app.
Why Well-Built AI Agents Fail in Production: The Outcome Gap
Understand why AI agents that produce excellent outputs still fail to deliver business results - and what the 'outcome gap' means for how you design AI workflows.
The Agent Spec: Outcome Owed, Boundaries, Health Metrics, Stop Rules
Learn the four components of an agent spec - the executable contract that makes AI workflows accountable to business outcomes - and write your first spec for a real workflow.
Writing Acceptance Criteria in Plain Business Language
Learn how to write clear acceptance criteria for AI workflows - the specific, testable conditions that tell you whether the AI's output is actually acceptable before you use it.
Stop Conditions: When Should AI Escalate to a Human?
Design clear escalation triggers so your AI agents know when to stop and hand off to a human - before a bad situation becomes a business problem.
Version-Controlling Your AI Specs: Treating Them Like Business Processes
Build a system for maintaining, updating, and reviewing AI agent specs over time so they stay accurate, auditable, and aligned with your evolving business - without needing technical tools.
Deploying Your First Specced Agent: A Real Business Workflow End-to-End
Walk through the complete process of speccing, building, testing, and deploying a real AI workflow - from blank page to production-ready agent - using a concrete small business example.