AI Agents Development Notes (Lesson 1): The Hidden Pitfall of the Context Window

It was only during the project that I realized how tricky this issue can be—several files can accidentally grow too quickly, requiring a major overhaul of the entire process. That moment was truly eye-opening.

Later, I started to think: can we reverse the approach—let agents learn to manage their own context size? In other words, enable agents to recognize when they need to optimize and how to restructure files to fit within token limits during runtime.

This idea is actually quite interesting—the optimization logic could be embedded into the agents' adaptive mechanisms. Next, I will test which solutions are truly effective, which ones are prone to pitfalls. Anyone interested can join the discussion.