A grounded hour on AI adoption — the genuine gains, the real risks, and what doing this right actually takes.
Image created with AI - obviously :-)
Some teams are held back by uncertainty — not sure whether to accelerate or slow down. Some are already moving and noticing things that are hard to name. Some are fully committed, velocity is climbing, and the question is whether what's being built at that speed will hold.
This talk is for all three.
It is for the people responsible for what gets built — decision makers, product owners, architects, developers, testers. It is not a pitch for AI adoption. It is an honest account of what it actually takes to do this well.
I scrapped two projects last year. Both built with AI. That's what I'm here to talk about.
— Bo Frese
One hour. No hype, no transformation promises. Three things that matter whether you're just starting or already in it.
Not the marketing version. AI simulates intelligence — it doesn't have it. That distinction shapes everything about how it should be used. No memory between sessions, a context window with hard limits, a tool that is exceptionally capable within the right structure and genuinely dangerous without it.
The concern about AI quality is legitimate — but usually aimed at the wrong target. The risk is not what AI produces. It's what happens when AI moves at speed through an organisation that hasn't built a real quality culture.
There is also the opposite risk — and it is just as real. Teams that step back entirely, waiting for the right policy or the right moment, cede ground to competitors who are moving with discipline. Sitting it out is not a safe position.
A live walkthrough of a structured AI development process — from business vision to implementation to review. What human ownership actually means in practice. What it takes to build something you can stand behind.
The talk ends with three questions. The first two point toward work AI can help you do right now — if you point it in the right direction. The third is the one only a human can answer.
Habit and behaviour — but it can also be encoded into a set of AI skills and commands. That takes real work and a genuine understanding of how AI works. If the process doesn't exist yet, use AI to build it. That is the first job.
Could a new developer be productive on their first day? If not, neither can the AI. Every session is day one. Documentation, architecture decisions, product vision, CI/CD, test coverage — use AI to build what is missing. Not features. Foundation. Then build faster.
Not the plan. Not the spec. The code, the architecture, the debt accumulating, the maintainability. Someone who could look at what exists and say: I stand behind this. That is the one thing AI cannot do for you.
I spent the past year building real products with AI — full time, end to end. Two iOS apps. A content management system. Four websites. An open-source AI development tool. I also scrapped two of those projects.
The ones I kept — and what I built after the failures — are what this talk is about. I am not here to tell you whether to adopt AI. I am here to tell you what I learned the hard way, so you don't have to.
I am more enthusiastic about AI today than when I started. It enables things that were not possible before — but only when it runs inside a structured process, with the right context and a human who owns the outcome. That is the version I want to help your team reach.
Bo Frese