Product Management in the AI Era
An opinionated guide to building products that matter. Principles for thinking, a process for shipping, an architecture for AI products, and a competency model for the builder era.
Version 2.0 · Last updated 30 March 2026
Product Principles
The mental models that shape how high-performing product teams think, operate, and make decisions.
Outcome-Driven Thinking
Why the best product teams measure success by customer and business outcomes, not feature velocity.
Empowered Teams in the AI Era
The empowerment-autonomy matrix still applies, but AI changes what 'empowered' means when the team includes agents.
Customer Obsession
How to stay relentlessly focused on solving your customers' hardest problems, not building feature lists.
Thinking in Bets
How to embrace uncertainty, minimise the cost of being wrong, and turn every initiative into a calculated experiment.
AI-First, Human-Centred
What AI-first actually means in production, why optional AI is a gimmick, and how to build products where AI is the medium, not a feature.
Product Lifecycle & Process
The operational playbook from discovery through delivery, launch, and continuous optimisation.
Discovery, Feedback, and Backlogs
The dual backlog system, continuous discovery, feedback channels, lighthouse users, and AI-native risk assessment.
Business Viability and AI Economics
The cannibalisation paradox, the margin trap, inference cost modelling, and pricing strategies that survive the shift from SaaS to Service-as-a-Software.
Planning and Prioritisation
Outcome-driven roadmapping, AI-specific prioritisation criteria, and planning in compressed build cycles.
Execution and Delivery
The AI-native Definition of Ready, delivery in the builder era, and sprint ceremonies for agentic products.
Go-to-Market, Launch, and Growth
The PR/FAQ as GTM artefact, AI-specific positioning, release coordination, and continuous growth post-launch.
AI Product Architecture & Operations
The AI-specific technical decisions that separate production AI products from prototypes.
Multi-Model Orchestration and the Routing Layer
Why no single model wins every task, how the routing layer becomes your competitive advantage, and the worker-manager pattern for multi-agent systems.
Agentic AI Product Patterns
What makes a workflow agentic, why 95% accuracy kills enterprise deployment, and the production patterns that actually ship.
Evaluation Frameworks as Product Infrastructure
Why evals are day-one infrastructure, how to build them from 20 examples, and why your eval suite is your competitive advantage.
AI UX and Interaction Design
Why most AI features go unused, the inline-vs-destination decision that determines adoption, and how generative UI replaces the chat box.
AI Governance for Regulated Environments
Risk-tiered governance frameworks, data provenance, compliance for regulated industries, and security as a product risk category.
Roles, Competencies & Organisation
The product builder role, competency model, and team design for the AI era.
The Product Builder
The PM-to-builder shift, the new full stack of Prompt-Build-Eval, and updated career paths for the AI era.
The Product Competency Model
Five domains of product craft with expanded AI fluency: architecture, evaluation, UX, economics, governance, and builder skills.
AI-Native Team Design
Why smaller AI-augmented teams outperform larger ones, the judgment-vs-patience framework, and org patterns for the builder era.