90% of AI Demos Fail. Here's How to Build One that Won't — with Lawrence Jones
If you've ever shipped an AI feature that looked great in testing — only to watch it behave unpredictably in production — you're not alone.
In this episode of IT Visionaries, I talk with Lawrence Jones, Founding Engineer at incident.io, about the critical gap between AI that demos well and AI that works under pressure. Lawrence shares how his team designs tools that help engineers respond faster, learn from failure, and build systems that don't crumble when it counts.
Chapters:
0:00 — AI Chaos & The Mike Tyson Rule
0:58 — Meet Lawrence Jones of incident.io
3:14 — From FinTech Outages to Incident Response
6:22 — The Biggest Mistake in Incident Management
9:08 — Training for Chaos: Game Day Simulations
10:31 — Inside the AI SRE System
13:01 — What SRE Really Means
16:23 — From Prototype to Production AI
20:27 — Keeping Up with AI's Rapid Evolution
22:50 — Understanding Vector Databases & Embeddings
28:34 — The Architecture Problem: Chaining Prompts at Scale
36:11 — Measuring AI Performance & Reliability
44:02 — The Future of SRE Meets AI
52:10 — Lessons from Real Incidents
56:42 — Final Thoughts: Building AI That Works
Guest: Lawrence Jones, Founding Engineer, incident.io — LinkedIn
