What is AI coding?

Technical definition

AI coding covers the application of generative models, usually large language models trained on code, to software development tasks: generating new code from a description, editing existing code, translating between languages, explaining unfamiliar code, writing tests, and diagnosing errors.

The category spans a range of autonomy. At one end, inline completion suggests the next few lines while a developer types. At the other, an agent takes a goal, plans an approach, writes across many files, runs the result, and iterates on failures without step-by-step direction.

In plain terms

AI coding is getting a computer to write the code instead of writing it yourself.

How much you hand over is a choice. Some people use AI to finish lines they already started. Others describe a whole product and review what comes back.

Why it matters

AI coding changed who can build software. That is the whole story.

The old constraint was skill: you learned to code, or you paid someone who had. Now the constraint is knowing what you want and being able to judge whether you got it. Domain expertise became the scarce input, and syntax stopped being one.

For a business owner, this changes the build-versus-buy question. Software that was too small to be worth a developer's time, and too specific for an off-the-shelf product, is now worth making. The CRM that matches how you sell. The booking flow that handles your actual service types.

What has not changed: someone still has to decide what correct looks like, and check that the running product does it.