Strategy, economics, evaluation, governance

AI Opportunity Framing and Capability Mapping

Strong AI products begin with a capability map, not a model demo. This module teaches product leaders to distinguish tasks that require generation, classification, retrieval, reasoning, automation, or human review, then map those capabilities to customer pain and business leverage.

Deep dive summary

What this module actually teaches.

Passage 1Strong AI products begin with a capability map, not a model demo. This module teaches product leaders to distinguish tasks that require generation, classification, retrieval, reasoning, automation, or human review, then map those capabilities to customer pain and business leverage.

Passage 2Learners evaluate whether AI changes the core job-to-be-done or merely decorates an existing workflow. The module introduces opportunity scoring across frequency, consequence, data availability, ambiguity, willingness to pay, and tolerance for mistakes.

Passage 3The deliverable is a clear product thesis: what intelligence is being added, why it matters now, what humans still control, and how the team will know whether the feature deserves continued investment.

Learning operating system

Module prerequisites, concepts, outcomes, and artifacts

Prerequisites

  • Basic product discovery experience
  • customer interview familiarity

Key concepts

  • capability mapping
  • job-to-be-done
  • task ambiguity
  • AI fit scoring
  • human control points
  • product thesis

Target audience

  • Product managers, founders, and business leads planning AI features before committing engineering resources.

Outcomes

  • Separate legitimate AI opportunities from demo-driven ideas
  • Map AI capabilities to measurable customer value
  • Create a product thesis that engineering and design can critique

Artifacts

  • AI opportunity scorecard
  • capability-to-workflow map
  • product thesis one-pager

Code example

Real patterns, ready to copy into your editor.

A code reference card that frames this module's concepts in real syntax. Copy any example to study it or adapt it directly in your own editor.

Copy-ready snippets
curriculum/pl-ai-opportunity-framing.tsts
1type ModuleBrief = {2  track: string;3  difficulty: string;4  keyConcepts: string[];5  reviewGate: 'human-review-required';6};7 8export const moduleBrief: ModuleBrief = {9  track: 'Product Leaders',10  difficulty: 'Foundational',11  keyConcepts: [12    'capability mapping',13    'job-to-be-done',14    'task ambiguity',15    'AI fit scoring',16    'human control points',17  ],18  reviewGate: 'human-review-required',19};