We Spent a Week Evaluating a Context Compression Tool, Then Killed It

Here's Everything We Found An AgentAutopsy post — dissecting AI agent failures so you don't have to 177. That's how many times our decision-making agent's context got compacted in two weeks. Claude Opus, sitting at the center of our 1-human + 6-AI autonomous team, hit its context window limit 177 times. Each time that happens, the system summarizes everything and restarts. Each time, something gets lost — a tool call result, a nuanced decision from three turns ago, the reason we ruled out option B. After 177 of these, you start making decisions with a model that's kind of... lobotomized. It still sounds smart. It's just missing the thread. So we decided to build something about it. We called it Context Squeezer. We killed it six days later. Here's the full dissection. First — Isn't This What Prompt Caching Is For? Before we go further, let's clear up the thing that confused us for longer than it should have. Prompt Caching (Anthropic has it, OpenAI has it) caches the static prefix of y