v2.7.2: Long Conversations Open Instantly, and the Disconnect Loop Is Gone
Some bugs announce themselves. This one hid inside the exact behavior that made everything feel broken: the longer and more valuable a conversation became, the more likely it was to fall apart. v2.7.2 is a small, focused release that fixes it, and the fix is worth understanding because it says something about how real-time systems degrade.
What was actually happening
Every chat in Geta.Team is backed by a live WebSocket connection. When you open a conversation, the server sends you its history so you can see what has already been said. Simple enough, and it worked fine for most conversations.
The trouble started with the long ones. Every time a client connected to a conversation, the server replayed the entire history at once. Not the last screen's worth. All of it. A refresh, a second browser tab, the owner opening the admin view: each one triggered a full replay of every message in that thread.
On a short chat, you never noticed. On a conversation with hundreds or thousands of messages, that replay was a flood. Pushing all of it down the socket in one burst tied up the connection just long enough that the other clients already watching that conversation timed out. They dropped. They reconnected. And reconnecting triggered another full replay, which knocked everyone loose again.
That is a feedback loop, and it behaved like one. The disconnects fed the reconnects, the reconnects fed the floods, and the whole thing spun with those tell-tale "No terminal buffer found" errors scrolling past. The cruel part was the correlation: the more you had invested in a conversation, the more history it carried, and the harder it became to keep the thing open at all.
The fix: load what you can see, fetch the rest as you go
The change is called lazy transfer, and the idea is almost boringly sensible once you say it out loud. You do not need a thousand messages the instant you open a chat. You need the last handful, the ones actually on screen.
So that is what loads now. On connect, the chat pulls only the most recent 32 messages or so. That is enough to fill the view and let you start working immediately. As you scroll up into older history, it fetches the previous messages 32 at a time, on demand, mirroring the way they were already being rendered on screen anyway.
Nothing is lost. Your full history is still there, every message of it, available the moment you scroll back to look. The only thing that changed is when it travels across the wire. Instead of a wall of data on every connect, it arrives in small batches, only when you ask for it.
The results follow directly from that. No more flood on connect, so no more connection tied up long enough to knock other clients offline. No more disconnect and reconnect loop, because the thing that triggered it is gone. And long conversations now open instantly, because opening one no longer means waiting for its entire past to download first.
This behaves identically across Claude, Codex, and custom LLM teammates. It is a change to how the chat transport works, not to any single model integration, so every conversation benefits the same way.
One more fix: no stale badges bleeding into a fresh chat
The same release clears up a smaller but genuinely annoying glitch. Those little status badges that appear in chat, the ones that say things like "Kanban: card created" or "Delegated to a teammate", were being saved per teammate rather than per conversation. So when you started a brand new chat with that teammate, every old badge came back with it, including ones from a completely different session days earlier.
The effect was a fresh conversation that did not feel fresh. You would open a clean thread and find it littered with the residue of past work that had nothing to do with what you were about to do.
Now those badges are cleared when you start a new conversation, so a new chat opens clean. Badges from the conversation you are actually in still persist across refreshes exactly as before. The rule is simply that history belongs to the conversation that created it, not to the teammate in general.
Why a fix like this matters more than it looks
It is tempting to file this under minor bug fix and move on. It is one item in a point release. But the failure it removes is exactly the kind that erodes trust in an AI teammate, because it punished the users who were using the product most.
An AI employee earns its place through continuity. The value compounds over a long relationship: the context it has accumulated, the back-and-forth it remembers, the thread you have been building for weeks. A conversation that gets slower and flakier the longer you rely on it is quietly telling you not to rely on it. That is the opposite of what a coworker should feel like.
There is also a wider engineering lesson tucked in here, and it is one worth keeping. The original design was not careless. Replaying full history is the obvious, correct-looking thing to do, and it passes every test you write on a short conversation. It only breaks at scale, under real usage, on the accounts that matter most. Robust real-time systems are usually the ones that moved data lazily from the start: send what is needed now, fetch the rest on demand, never assume the payload stays small just because it did on day one.
If you have been living with long threads that kept dropping, reload and open one. It should snap open, stay open, and scroll back through its whole history without a stutter. Same conversation, same memory, none of the flood.
