Developers building AI products
Free resource · Field guide
From AI Demo to Production System
What I learned turning an impressive AI coding demo into an agentic product that users can actually trust, inspect, operate, and return to.
I walk through the decisions I had to make after the demo stopped being enough: persistent projects, policy-bound tools, isolated execution, validation and repair, observable agent runs, previews, deployment, multi-tenant platform work, and the commercial workflow around the generated output.
Start the guide ↗15 chapters · free · no signup required
Who it's for
Built for people making the same decisions I made.
This is grounded in the build of FewzenAI, my agentic app studio. I use the real architecture, mistakes, rewrites, tradeoffs, and remaining gaps rather than describing an idealised agent system that only exists on a whiteboard.
Technical founders moving beyond an MVP
Consultants advising clients on AI systems
Agencies considering AI-assisted delivery
Engineering leaders evaluating agentic architecture
Structure
5 parts, 15 chapters.
Every chapter follows the same teaching device: the situation, the naive solution, the hidden constraint, the decision, the implementation, the tradeoff, the evidence, the reusable lesson, and the consultant's questions.
Part 1: Finding the Real Problem
Part 2: Building the Agentic Core
Part 3: Turning It Into a Product
Part 4: Lessons for Builders and Consultants
Part 5: Framework and Build Plan
Where I can help
Agentic Product Architecture Review
I help teams evaluate, design, and de-risk agentic products, particularly where a model can touch tools, customer data, generated code, secrets, or production infrastructure. The review focuses on the boundaries that become expensive to fix later: orchestration, execution, tenancy, observability, recovery, and human control.
Book an architecture review ↗Work with me
Ready to work through it?
Start the guide and progress through it at your own pace. Start with a 30-minute call with me.