Product
A Lightweight AI Workflow for Product Discovery
Discovery improves when synthesis and evidence stay connected. This guide helps product managers get to clearer bets before writing specs.
AI tools are most useful when they are attached to a specific job. For product managers, the goal is not to add another shiny tool to the stack. The goal is to create a repeatable workflow that produces a better decision, draft, prototype, analysis, or handoff.
Discovery improves when synthesis and evidence stay connected.
In practice, that means using Claude and Perplexity as part of a bounded process. Give the tool enough context to be useful, keep the output connected to real work, and make the human review step explicit.
The Workflow
Use this as a simple starting point. The exact details can change, but the sequence keeps the work focused.
Collect customer inputs
Find market context
Cluster opportunities
Write a decision memo
What Good Looks Like
The output should make the next step easier. If the workflow ends with more ambiguity, more tabs, or a longer list of unresolved ideas, it is not doing its job.
A strong result gives you clearer bets before writing specs. It should also leave a trail: what information went in, what assumptions were made, and what still needs human judgment.
Common Mistakes
Mistaking volume of notes for insight
Researching after the decision is made
Bottom line
Keep the human edit in the loop.
Start small, make the workflow observable, and keep responsibility with the person doing the work. AI should reduce friction, but it should not remove taste, judgment, or accountability.
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