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Claude for Product Management: Requirements to Strategy

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Use Claude to clarify requirements, analyse user feedback at scale and accelerate strategy — and verify every output.
1
1/5
(22) Ratings
1 students
Created by Dr. Amar Massoud
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What you'll learn

  • Set Claude up as a product workspace with standing context, so two PMs asking the same question get the same answer
  • Ground every prompt in your own evidence, and spot a confabulated requirement before it reaches a spec
  • Turn a one-line stakeholder ask into a spec with testable Given/When/Then criteria, edge cases and named open questions
  • Synthesise thousands of feedback items, then run the validation protocol that says which themes actually survived
  • Report a finding with its corpus attached, so frequency never gets quietly promoted into prevalence
  • Build competitive briefs, JTBD framings and prioritisation models on fetched evidence rather than model recall
  • Write one fact set into five audience versions and prove that no number drifted between them
  • Encode your recurring work as skills and connectors — and know which decisions stay human
This course includes:
3 total hours on-demand video
0 articles
8 downloadable resources
34 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • No coding, no API work, no terminal — everything happens in the Claude apps and a browser
  • A Claude account; a paid plan is needed for Projects, Skills and connectors
  • Working as a product manager, or close enough to product work to have your own requirements and feedback to practise on
  • Helpful but not required: a real feedback corpus and a spec you have written, to run the course’s methods against

Description

This course contains the use of artificial intelligence.

Generating a PRD with AI takes ninety seconds. Knowing whether it is true takes a method.

That gap is where this course lives. Five other Claude courses for product managers will show you how to produce a spec and a themed summary of your feedback. Not one of them teaches you how to check either. So the PRD ships with an invented approval rule buried in section four, and the synthesis reports that 42% of customers want better reporting when what it actually measured was 42% of the people who bothered to write in.

This course is built on the second half of the job.

What makes this different

Grounding is taught as a habit, not a disclaimer — four moves you make before the question, every time, in Section 2. Feedback synthesis ships with a validation protocol: re-run stability, spot-checks against raw quotes, and the difference between frequency in your corpus and prevalence in your customer base. You will watch Claude invent a policy rule on screen, in a real session, and learn why it read as completely plausible.

There is no product-management fundamentals section

The loudest complaint in the reviews of every competing course is padding — being told what a PM is by someone you came to for something else. PM method appears here only where it is the thing being checked against AI output. Lecture one opens inside a live product problem.

You finish with artefacts, not notes

A grounding and verification checklist. A PRD skill file that triggers itself when the task arises. A feedback synthesis validation protocol. A prioritisation rubric. A one-fact-set sheet that keeps a number identical across five audiences. A PM skill starter kit. A data boundary card. An Article 50 routing card. Everything is built against one company — Fathom, a Berlin spend-management SaaS with 22,000 customers and a flat activation curve — so each artefact connects to the last.

How it is taught

Eight sections, thirty-four lectures, around three hours of video. Seven section assignments plus a capstone. Eight quizzes and a 50-question final practice exam. Eight downloadable templates. Every Claude session you see on screen is a real captured session, not a recreation — a course about Claude should not show you a Claude that isn't one.

One honest note

Model names, tiers and prices move faster than any course can. This one teaches model selection as reasoning — fast tier for extraction, frontier tier for judgement, extended thinking for hard trade-offs — so what you learn survives the next release. Dated regulatory content is confined to a single lecture for the same reason.

Who this course is for:

  • Product managers who already write specs and want the AI-produced version to be checkable
  • Senior and group PMs responsible for synthesis and prioritisation that others act on
  • Product owners and BAs turning stakeholder asks into requirements engineering can build
  • UX researchers and insights specialists analysing feedback corpora too large to read
  • Founders and heads of product doing product management without a product team
  • Product ops and enablement leads standardising how a team uses Claude
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