You've probably tried a few AI coding tools by now, like Cursor or Claude Code. A lot of the advice on using them, though, comes from the companies that make them or from people online who promise they'll make you 10 times faster.
For this piece, I asked three engineers how they use AI at work: Pooja Naik, Senior Software Engineer; Viraj Patel, a software engineer who joined Microsoft about a year ago; and Tom Archer, Independent AI/ML Research Engineer at Signal & Syntax, who has been programming professionally for more than 40 years.
They're all at very different points in their careers, but they follow a similar rule: AI helps with the work, and they make the important decisions themselves. It also means more of the job is now checking code. As Archer put it, engineers are "increasingly reviewing and taking responsibility for code they didn't personally write."
Here are six habits for using AI as a software engineer, based on what they told me.
David Adubiina
/1. Don't take confident answers at face value
Naik was working through an unfamiliar part of her codebase when she asked an AI tool where a particular function was used. It told her, confidently, that it wasn't used anywhere and was dead code she could remove.
Naik knew from experience that the function was still being called, so she pushed back. But the AI stuck to its answer. She pushed again, and this time it checked more carefully and admitted it had missed where the function was used.
"If I hadn't already known that code path, I would have deleted something that was actually load-bearing," she said.
Something similar happened to Patel. AI once gave him a fix that looked right but ignored an important edge case. He caught it by testing the fix and comparing it against the actual business requirements. He treats AI as "a helpful assistant, not an authority."
Subscribe for paid membership to continue reading this article
Subscribe SubscribeAlready have an account? Log in
