AI Engineering: From Faster Coding to Reliable Delivery
AI Engineering is the design of workflows, platforms, quality systems, evaluations, governance, and delivery practices that make AI-assisted development useful in real organizations.
Senior Technical Director, Nearform
That means new ways of working, clear ownership and governance, platforms that hold up under real use, and a way to measure whether any of it is actually working. My background is engineering delivery, so the advice survives contact with production.
Turning AI-assisted development into reliable, reviewable delivery.
The platforms, DevOps practices, and delivery systems that help teams ship with confidence.
Hands-on projects that make the tools and their trade-offs concrete.
AI Engineering is the design of workflows, platforms, quality systems, evaluations, governance, and delivery practices that make AI-assisted development useful in real organizations.
A private Go project where I learn how agent runtimes, LLM providers, and tool loops actually work.
Please Stop Force-Feeding AI FOMO to Others!
A quick Friday night experiment: I coded a trie in Go and asked an AI to review it. Here's the hilarious feedback I got.
2025 has been quite a year. Let's look back at the highlights and lessons learned.