Domain-Driven Design: Drawing Context Boundaries for AI to Say Goodbye to "Big Ball of Mud" Code

Tue, 04 Aug 2026 00:00:00 +0000

Getting AI to write a single feature is usually not difficult. What’s truly difficult is:

After AI writes dozens or even hundreds of features in a row, can the code still remain clear?

Many projects start with a decent structure — a bit of user functionality here, some permission handling there, order features over there, logging features somewhere else.

As requirements grow, different modules start calling each other, referencing each other, modifying each other, and may eventually end up like this:

user.py
  ↓
permission.py
  ↓
agent.py
  ↓
tool.py
  ↓
knowledge_base.py
  ↓
conversation.py
  ↘
  calls user.py again

There are plenty of files and lots of code, but who is responsible for what becomes increasingly unclear.

Software architecture has a very vivid name for this:

Big Ball of Mud

And Domain-Driven Design, or DDD as we often hear, has one very important role: drawing boundaries clearly before the system starts to get messy.

For AI programming, this role is especially critical.

Domain-Driven Design on Interesting AI

Domain-Driven Design: Drawing Context Boundaries for AI to Say Goodbye to "Big Ball of Mud" Code