HelloPM: an 86-minute guide to AI product management in 2026

Ankit Shukla published this structured guide in July 2026 as a condensed course for product managers who need to get up to speed on AI product work — whether that means building AI features, transitioning into dedicated AI PM roles, or staying current in a field that shifts quickly.

The guide opens with a model of the AI economy organized into four layers: infrastructure, models, applications, and agency. Each layer behaves differently, has different competitive dynamics, and creates different types of product problems. Knowing which layer your product sits in changes how you think about differentiation, pricing, and roadmap decisions. A product at the application layer competes differently from one that is building at the agency layer, and many PMs conflate the two.

The three PM role types the guide defines are worth understanding even if specialization is not the goal. The first is the AI product builder, responsible for the core AI feature and its quality. The second is the AI-augmented PM, who uses AI tools across the full product workflow without building AI directly. The third is the AI product strategist, focused on the organizational and competitive implications of AI adoption. Most working PMs operate across all three roles simultaneously, but the framing helps identify which specific skills are missing.

The POWER framework — Possibilities, Opportunity, Workflow, Engineering, Reflection — gives PMs a structured approach for evaluating whether an AI capability is worth investing in for a given problem. The five-level AI toolkit section describes a learning progression that starts with basic conversational AI and ends with building agentic workflows using tools like Claude Code. The article makes clear that none of these levels require writing code, which is accurate for most of them.

The piece works as an orientation document for PMs earlier in their AI journey. It also functions as a useful refresh for more experienced PMs who want a single place to review current role expectations and skill gaps, particularly given how much the surface area of AI PM work has expanded since 2024.