u/emiliookap

My AI chats were all over the place while studying so I just built my own workspace

Chats were piling up everywhere, no structure, kept losing context mid study session.

So I built ChatOS. conversations and notes become draggable apps on a canvas, grouped into folders that automatically build a summary with key insights and next steps. When you want to go deeper on something you can nest a side thread into any message without cluttering the main conversation.

You can set any wallpaper you want behind the glassmorphism, supports images and mp4 loops so you can have a living background. threw on a lofi gif and the whole workspace just feels cozy to work in now.

u/emiliookap — 4 days ago

I’ve been using AI heavily for months, long research sessions, coding projects, conversations that run hundreds of messages deep. At some point every tab just becomes sluggish and I always assumed it was server load or API latency.

It’s not.

The reason is straightforward. ChatGPT renders every single message in your browser at once. A 300 message chat means thousands of live DOM elements simultaneously. No lazy loading, no virtualization, no pagination. Everything is in memory all the time. The longer the conversation the worse it gets, and there’s nothing you can do about it from the user side because it’s a frontend architecture choice, not a server problem.

I started building my own AI workspace and I made this a first principle to solve properly. Here’s what actually works:

Virtualized rendering — only the messages currently in your viewport are live DOM elements. Everything else is unmounted. Memory stays flat regardless of conversation length.

Message window cap with progressive loading — instead of dumping the full history into the browser at once, you get a recent tail with older messages loading gradually as you scroll up. The browser never holds the entire thread in memory.

Streaming batching — incoming chunks are merged in animation frames with a frame budget so rendering new messages never blocks the UI even during fast streams.

The result is that a 1000 message conversation feels the same as a 20 message one from a performance standpoint.

Beyond performance I also wanted to fix the other thing that makes long AI sessions painful, context loss and tool fragmentation. So the workspace I built, works like a desktop for your AI chats. Conversations, folders and notes live as draggable apps on a canvas.

Each project folder builds up a persistent memory automatically, summaries, key insights and decisions that carry forward across sessions so you never lose context when you start a new chat. You can also nest directly into any message as a focused side thread without cluttering the main conversation.

Claude, GPT-4o, Gemini and DeepSeek are all available in one place with auto routing that picks the right model for the task.

reddit.com
u/emiliookap — 12 days ago