Ship ai as pm

Ship AI as PM

Action playbook from nine AI Engineer / World's Fair talks. Do not summarize talks — pick a workflow and execute it.

Supporting files (read when needed):

• workflows.md — workflows A–I (steps, deliverables, stop conditions)
• source-index.md — src-NNN → talk learnings in ingest-into-skills

Optional: {SKILL_OUTPUT_DIR}/ship-ai-as-pm/

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Step 0 — Pick workflow

Use the decision tree below. Open the matching section in workflows.md.

What is the user trying to do?
├─ Define AI PM role / ownership                         → A
├─ Competitive strategy (knife fight, moats)             → B
├─ Ship to real users fast                               → C
├─ Roadmap under capability uncertainty                  → D
├─ Expert-in-the-loop vertical product                   → E
├─ Domain expert + eval ownership                        → F
├─ Agent coordination in work tools                      → G
├─ Post-engineer engineering org                         → H
└─ Taste-led UX (anti-slop)                              → I

Stop summarizing once a workflow is identified — run its checklist.

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Install

cp -r skills/ship-ai-as-pm ~/.claude/skills/
cp -r skills/ship-ai-as-pm ~/.cursor/skills/
cp -r skills/ship-ai-as-pm ~/.codex/skills/

From skills-i-use or ingest-into-skills (playlists/product-management-ai-engineer-world-s-fair/).

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Cross-cutting rules

Rule	Source
Ship to someone weekly beats platform build	[src-005 @ 0:19]
Evals as discovery under uncertainty	[src-004 @ 9:03]
Experts own rubrics in verticals	[src-006 @ 7:26]

Disputed steps: see source-index.md. Name workflow A–I; save artifacts to ./skill-outputs/ship-ai-as-pm/ when requested; do not auto-commit.

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Invocation examples

@ship-ai-as-pm AI product strategy for crowded market
roadmap when we dont know model limits