Autocomplete is the least interesting use
Most engineers meet AI through inline code completion, which is genuinely useful but is the shallow end. The deeper value shows up in the parts of the job that are not typing: understanding unfamiliar systems, reasoning about failure, writing the tests and docs everyone skips, and getting unstuck when a bug makes no sense. Treat the model as a tireless, fast, occasionally wrong junior pair — one that has read a lot of code but has no stake in being right.
Five uses that move the needle
Architecture brainstorming. Describe the constraints — read/write ratio, latency budget, team size — and ask for three approaches with trade-offs. The value is not the answer; it is being forced to articulate constraints and seeing options you would not have listed. You make the call.
Rubber-duck debugging. Paste the error, the relevant code, and what you expected. The model is excellent at “have you considered that X is null here” and at decoding cryptic stack traces. It externalises the thinking that solo debugging keeps stuck in your head.
Test generation. Give it a function and ask for edge cases: empty input, boundary values, malformed data, concurrency. Generated tests are a starting checklist, not gospel — run them, and add the domain-specific cases the model cannot know.
Documenting legacy code. Paste an undocumented module and ask for a summary, inline comments, and a list of suspected gotchas. This is the cheapest way to make a scary file approachable before you change it.
Code review assistance. Run the diff past a model with a request to flag correctness, security, and edge-case issues. It complements human review by catching the boring stuff so reviewers spend attention on design.
The discipline that makes it safe
The rule that separates engineers who benefit from those who get burned: never merge code you have not read and understood. AI confidence is not evidence of correctness, and the worst failures are plausible-looking. Demand tests, run them, review every line, and keep secrets and private code out of consumer tools. The model writes the first draft fast — you remain the engineer of record, and your name is on the commit.