We hit real friction running a large fleet of AI coding sessions: nobody knew who was working on what, two agents kept reaching the same conclusion independently, and long efforts outgrew their own memory. This is what we found — including two things we had backwards.
This is the most consistent finding in the research, and it comes from people with no connection to each other. The number barely moves.
We measured the first token count of eight real sessions before any work happened. They cluster tightly around 145,000 tokens — the project instructions, tool definitions and skill files that load every time.
A rule intended to prevent context exhaustion fired at 19%. Subtracting the 14.5% baseline, that session had used 4.5% of its actual working capacity — and we replaced it with a fresh one that had to re-learn everything from a document.
When a session delegates to a helper, the helper works in its own separate memory and returns only its conclusion. The searching, file reading and dead ends never enter the main conversation. This is documented behaviour, and we confirmed it.
When a session fills up it automatically summarises itself and continues. We assumed this was configurable and that our own safeguard was redundant. Both assumptions were wrong.
Cursor published three generations of their approach to running hundreds of agents. Two of them failed — and they failed in the way we were about to attempt.
Our sharpest problem is two agents independently reaching the same conclusion — “the build is broken, let's fix it” — and both starting. That is not a scheduling clash. Both were right. No lock catches it, because neither knew the other existed.
When a session runs out of room we start a successor, so one effort becomes v1, v2, v3… and it stops being obvious which one is in charge. The naming implies a chain, but we were actually running three different relationships under it — a supervisor, a true successor, and an unrelated new scope.
We searched the ecosystem properly. Visibility and isolation are well solved. The problem we actually have is not.