Today, most conversations about AI in software development revolve around one question:

Which tasks can we automate?

An AI agent can help with requirements refinement. It can generate code. It can write unit tests. It can prepare documentation. It can perform code review or help with a deployment checklist.

And yes, it works.

Teams get results faster. Routine work is reduced. Engineers can move from idea to implementation much quicker. But there is one problem in this approach that we often underestimate. We talk a lot about what an AI agent can do. But we almost never talk about what an AI agent leaves behind.

The problem: AI completed the task, but the context disappeared

Let’s imagine a simple scenario.

An AI agent helped a business analyst decompose a user story.…