Everyone is talking about prompt engineering.

But lately, I've noticed something interesting.

The biggest improvements in AI-generated code aren't coming from better prompts. They're coming from better context.

Give an AI model a vague task, and you'll often get code that works but doesn't really fit the architecture, business logic, or existing patterns.

Give that same model:

• Architecture context

• Relevant files

• Coding standards

• Business constraints

And the output changes dramatically.

This makes me wonder:

Is context engineering becoming more important than prompt engineering for software teams?

Or do you think prompts still matter more?