Tools

The infinite context problem Imagine you ask Claude to investigate how authentication works in your project. It starts reading files. Lots of files. Suddenly you have 50,000 tokens of context filled with code you only needed to consult, not remember. Now every response is slower. And more expensive. And when you want to do something else, all that context is still there, taking up mental space. The solution: subagents. You launch a specialized agent that does the dirty work in its own isolated context, returns a summary, and disappears. Your main conversation stays clean. ...

The Problem of Repetition Ever had to explain the same thing to someone twenty times? Now imagine that, but with a robot that also loses its memory every few hours. “No, Claude, the commit needs to pass tests first.” “Claude, I already told you to use the type: description format.” “Stop adding emojis!” This was my daily routine until I discovered Skills. These are instructions you write once and Claude follows forever. Like training a dog, but without the treats. ...

When robots forget Imagine hiring a brilliant programmer. They solve complex problems, write clean code, understand your architecture. But they have one tiny flaw: every few hours, their memory gets wiped. They start from scratch. They don’t remember what they were working on, what you decided together, or why the code is structured the way it is. That’s exactly what happens with Claude Code and other AI agents. When context fills up (and it fills up fast if you’re working on a real project), the system performs “compaction.” It summarizes the conversation and throws away everything else. The problem is that summary loses nuance, decisions, and most importantly, the state of ongoing tasks. ...