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Read the introRevelica's opinionated AI native product discovery best practices.
Every playbook and skill the product agent runs as part of this method.
Establish workspace KPIs, then set the project outcome and Key Results against them.
Choose the evidence source, then build a cited segment and customer opportunities.
Articulate the value proposition, confirm competitors, and map competitive coverage.
Reuse, reference, or import prior Ideas, or record that there is no backlog.
Explore an alternative positioning for your product. Research a customer segment, articulate the value proposition, discover the competitors that emerge from that frame, and produce a competitive analysis.
Turn the strongest setup context into one tested recommendation.
Define a customer segment, then build the experience map: the moments they go through, the solutions they use, and the unmet needs. Grounded in real customer voice where possible.
Runs competitive analysis end to end: from a blank workspace to a market map that stays current.
Profile the company and primary solution without duplicating existing records.
Test a hypothesis with Analysis of Competing Hypotheses: gather evidence, score against all assumptions in isolation, produce a verdict matrix and report.
Create or refine an idea spec with stories and releases. Review it as a story map, structured document, or Markdown.
Import, reference, or record the ideas your team already considered.
Give your coding agent the product context behind the code: the idea, spec, and research it needs to build, plus a place to write results back so the team stays in sync.
Revelica's opinionated AI native product discovery best practices, ideally suited for empowered teams.