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The complete historical synthesis of agent-native products, enterprise adoption, sandboxes, governance, SaaS, pricing and security, including all published additions through October 22, 2026.
A methodology distillation of notes (87 entries, 8 modules) from an AIPMM-aligned AI Product Manager professional certificate course. In one sentence: this is not beginner-level literacy content explaining "what a PM is"; instead, it compiles all the naming frameworks, models, and checklists that an experienced PM should keep handy — reorganized into six sections. ① PM Roles and Responsibilities: definition of product management (7 stages from ideation to retirement), PM ≠ Project Manager (deciding What/Why vs figuring out How/When), business acumen (6 core financial metrics: ROI/IRR/NPV/Payback), differences between AI PMs and traditional PMs (data strategy/model drift/explainability/Responsible AI). ② Product Lifecycle Methods: 4 stages of the product lifecycle (Introduction/Growth/Maturity/Decline) vs 7 stages of the product management lifecycle (Conceive/Plan/Develop/Qualify/Launch/Deliver/Retire, key deliverables per stage + how AI products rewrite each step), three value delivery approaches (waterfall/iterative/incremental iterative), Predictive vs Adaptive project management. ③ Strategy and Innovation Frameworks: Oslo four categories of innovation + five-step innovation process, three tiers of innovation (incremental/radical/disruptive), SWOT/PEST, Porter's Five Forces, Kotler's Five Product Levels, market segmentation, five-step product strategy. ④ Stakeholder Collaboration and Communication: RACI, Five Dysfunctions pyramid (Trust → Conflict → Commitment → Accountability → Results), SMART goals + dual business value checklist, six elements of an elevator pitch, influence without authority (six sources of influence), 5-step problem-solving method + decision matrix, four communication styles (Analytical/Structural/Conceptual/Social) × Tuckman's four stages × situational leadership, six methods for building trust. ⑤ Business and Commercialization: business development, product portfolio management (breadth/depth/Portfolio PM vs regular PM), public-facing PR/marketing collateral checklist. ⑥ Career Development: transition paths, resume fit-not-identity principle, the rise of the AI PM. Division of labor with nngroup-product-ux (empirical PM×UX disagreements + RACI + PLG) and wiki-ai-pm-design-eng-collab (collaboration implementation): this article serves as the "methodology skeleton and framework dictionary for AI PMs"; collaboration details are cross-referenced rather than rewritten. Target audience = experienced PMs; terms are explained with industry context, and each section includes Why/when to use/counterexamples.