Quick Thoughts on AI and Software Engineering

I gave a talk to our engineering team about AI and where I think this is all heading. Here’s what matters.

It’s Not Just About Code

AI in software engineering isn’t like going from C to Ruby. It’s not a better programming language or a faster compiler.

It’s a shift in abstraction at every level. You don’t just write code faster. You think and work differently.

The job is changing.

AI has evolved massively in the last two years. It’s still not magic, but it’s very useful.

Cut through the noise. Try things. Keep what works. Drop what doesn’t.

Most of the hype is garbage. Most of the tools are actually helpful if you ignore the marketing.

This isn’t about vibes or guessing. It’s about context.

The better your prompt, the better your result. AI rewards clarity and intent. If you can’t explain what you want clearly, you won’t get it.

This is good. It forces you to think before you type.

The shift is real. Understanding business context, systems, and architecture now matters more than knowing syntax.

Writing code is just one part of the job. Tools are catching up fast on the mechanical parts.

What wins now: creativity, reasoning, system thinking. Focus on the what and why, not just the how.

Here’s the uncomfortable part: AI isn’t deterministic. You won’t get the same output twice.

But you can orchestrate. Use stable, deterministic building blocks with AI agents to build solutions neither could accomplish alone.

Deterministic systems for the foundation. AI for the parts that need flexibility and reasoning.

Getting in early and helping others level up with AI gives you (and your team) a lasting edge.

Learn. Understand. Share.

The engineers who figure this out now and teach others will be the ones shaping how we build software for the next decade.

Don’t wait for it to stabilize. It won’t. Get good at working in uncertainty.