Turns Out My Career Was Training for AI
Engineering, product, design, and program management taught me to connect decisions from the problem through to the finished product. That experience is useful when building with AI.
Engineer. Program manager. Product manager. Designer.
I’ve worked across all four. Turns out that’s a pretty useful background when you’re building with AI.
The decisions are getting closer together: What should we build? How should it work? How will someone use it? What needs to happen before we can ship?
An agent can help with implementation. Someone still has to connect those decisions.
Engineering teaches you to question the happy path. Where does the data go? What happens when a dependency fails? Can we explain why the system did that?
A working demo is great… especially when nobody has tried anything weird yet.
Product management teaches you to ask whether the feature deserves to exist. Who needs it? What problem does it solve? Where does AI actually improve the experience? Generating another feature is easy. Knowing when to stop is still useful.
Design makes the experience usable. What does someone see while the AI is working? How do they check its output, correct a mistake, or stop an action? Those are first-version decisions.
Program management brings sequence, dependencies, and ownership. What needs to work first? Which decision is blocking everything else?
Five agents working in parallel sounds impressive… until all five are waiting on the same unfinished dependency.
Take an app that drafts and sends messages. Product thinking identifies the task worth solving. Design shapes review and approval. Engineering handles permissions, failures, and duplicate sends. Program thinking gets those pieces delivered in an order that makes sense.
Four perspectives. Same feature.
My advice: learn what the other functions actually contribute. Sit in on a design critique. Understand why a PM cuts scope. Ask how a program manager spots a dependency. Learn how an engineer investigates a failure.
Then use that knowledge when you build with AI.
That’s what makes the product engineer idea interesting to me. You can carry more context from the problem through to the finished product. My career gave me a lot of practice doing that.
