AI Strategy
- AI Strategy (429)
- Generative AI (113)
- IT Leadership (38)
- Leadership (81)
- Product Management (394)
- Product Management Leadership (373)
- Uncategorized (32)
-
How I Use ChatGPT to Supercharge PM: Smart Workflows, Killer Prompts, and Real-World Wins
ChatGPT has become a quiet force multiplier in my product leadership—accelerating discovery, clarifying roadmaps, and sharpening stakeholder communication. I use it to draft PRDs, structure A/B…
-
Taming 1,000+ Vendor Emails: How Xelix’s AI Helpdesk Delivers Fast, Confident Answers
Vendor communication is noisy, costly, and ripe for AI—if you build it right. I break down how an AI Helpdesk can transform 1,000+ daily vendor emails…
-
AI Won’t Replace Engineers—Engineers Using AI Will: A Practical Playbook for Your Next Move
AI is automating tasks, not eliminating software engineers. The real opportunity is to shift from rote implementation to systems thinking, product discovery, and responsible AI Strategy.…
-
From Sketch to Clickable Demo: My AI Prototyping Playbook to Build Apps in Hours
I share a practical playbook for turning napkin sketches into clickable AI prototypes in hours. You’ll see how I frame outcomes and MDEs, generate UI quickly,…
-
Win AI Search: Proven Playbook to Get Your Startup Recommended by ChatGPT & Perplexity
AI search is becoming the new homepage for startups, and the brands that win are the ones models can clearly identify, verify, and cite. In this…
-
Prototypes vs Products: How I De-risk Ideas Fast and Ship Reliable Value at Scale
Too many teams confuse prototypes with products—and pay for it later. I use prototypes to learn fast and reduce risk, and I treat products as promises…
-
Turn Claude Code Into a Trusted Teammate: My 3-Layer Memory System You Can Copy
I used to waste hours repeating the same context to AI and getting generic, off-the-mark feedback. By giving Claude Code a persistent, file-based memory, I now…
-
AI at Home, Impact at Work: Experiments That Supercharged My Product Leadership
I reflect on a standout All Things Product conversation that reinforced how low-stakes AI experiments at home can dramatically improve how we build AI-powered products at…
-
How to Build an Evaluation-Driven AI Innovation Strategy
Build an AI innovation system that links portfolio bets to customer outcomes, release gates, and clear evidence for killing, refining, or scaling them.
-
From Chaos to Consistency: How I Built a Scalable AI Content Design Agent with RAG
I built an AI content design agent that scales quality without sacrificing judgment by grounding it in a rigorous design system and a curated RAG knowledge…
-
What I Learned from Trainline’s Agentic AI: Building a Trusted Travel Assistant at Scale
Agentic AI only works at scale when orchestration, tools, and guardrails are designed together. Trainline’s approach demonstrates how to pair scalable reasoning with deep domain context,…
-
Why We’re Building Our Next AI R&D Hub in Berlin—and Hiring 100 to Power Fin’s Growth
We’re opening our next AI R&D hub in Berlin to accelerate Intercom and our AI Agent, Fin, and we plan to hire 100 people across engineering,…
-
Context Is King: My Playbook to Prep Product Teams for High-Impact AI Collaboration
AI becomes a powerful teammate when we give it the right context. In this commentary, I share how I operationalize context—decision logs, success metrics, and machine-readable…
-
Beyond Digital: How AI Transformation Builds Adaptive, Intelligent Organizations That Win
AI transformation isn’t a tool rollout; it’s an operating model shift toward adaptive, intelligent systems that learn from every interaction. The payoff comes from aligning AI…
-
How to Govern and Measure an Enterprise AI Agent Portfolio
A practical operating model to choose enterprise AI agents, set risk-adjusted autonomy, enforce controls, and prove value per successful outcome.
-
Enterprise AI Workforce Readiness: A Practical Operating Model
A workflow-level operating model for role-specific AI training, human accountability, safer adoption, and measurable business outcomes.
-
From AI Pilot to Platform: An Enterprise Delivery System
A practical operating model for moving enterprise AI from promising demos to measurable, governed products with clear ownership, evals, and economics.
-
An Operating System for AI-Era Product and Engineering Leaders
A practical model for turning faster AI-assisted output into reliable customer outcomes through clear bets, evals, decision rights, and learning loops.
-
Building an AI-Era Product Operating Model That Can Learn
A practical operating model for giving AI product teams clear outcomes, faster evidence loops, proportionate governance, and a repeatable path to scale.
Weekly digest
One email a week on AI products, enablement and hiring. No fluff.
Browse topics
- AI Strategy (429)
- Generative AI (113)
- IT Leadership (38)
- Leadership (81)
- Product Management (394)
- Product Management Leadership (373)
- Uncategorized (32)
Work with me
45-minute consultation on AI product strategy, GTM and PM hiring — no charge.