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    Stage 2 of 9

    Product Foundations

    Find problems worth solving, write a one-page spec and decide whether AI is the right tool at all.

    Level: Beginner About 2 weeks at 6 hours a week 6 articles

    By the end of this stage you can

    • Run problem discovery and user interviews as an engineer
    • Write a one-page AI feature spec with success metrics
    • Recognize problems where AI is the wrong solution

    Articles

    1. 2.1 Problem discovery for AI features Find AI feature ideas worth building by starting from frequent, painful user jobs instead of model capabilities, using data you already have. Level: Beginner 10 min Completed
    2. 2.2 User interviews for engineers Run short, useful user interviews as an engineer, from recruiting to asking about real behavior, avoiding leading questions and turning notes into decisions. Level: Beginner 6 min Completed
    3. 2.3 Jobs-to-be-done for AI products Use jobs-to-be-done to frame AI features around the progress users want to make, write job statements, and spot where AI changes the job. Level: Beginner 6 min Completed
    4. 2.4 Writing a one-page AI feature spec Write a one-page spec for an AI feature covering the user and job, success metric, quality bar, failure states, cost estimate and the non-AI alternative. Level: Beginner 9 min Completed
    5. 2.5 Defining success metrics before you build Choose success metrics for an AI feature before you build it, from task success and adoption to guardrails and cost per success, with code to compute them. Level: Beginner 9 min Completed
    6. 2.6 When not to use AI Recognize problems where AI is the wrong tool, where rules, search, templates or better UX solve it more cheaply, reliably and safely than a model. Level: Beginner 9 min Completed