Most of us have seen a coding agent fail to complete a task we know it can do. We just don't understand the inconsistency in quality and lazily chalk it up to the "non-deterministic" nature of AI. What you might not realize is that the agent isn't failing because of intelligence, it's failing because its context is cluttered with noise.
To fix this, we need to shift from context maximizing to deterministic pruning. Here is what you will get out of this deep dive to help you build those boundaries:
Why feeding an agent your entire repository causes agent reasoning failures.
How to navigate brownfield codebases by isolating subsystems for agents.
How to dynamically mask dead code before launching an agent turn.
