Poe brings multi-bot chat to a single window

Quora's AI platform Poe just solved one of the most annoying habits of power AI users: juggling five browser tabs to piece together responses from different chatbots.

On Monday, Quora rolled out a new multi-bot chat feature that lets users interact with multiple AI models inside a single conversation thread.

Tag-teaming models in one thread

The mechanic is familiar to anyone who uses Slack or Discord. You enter a prompt and can pick from Poe's recommended bots, switch bots in the same pane to compare answers, or simply type @ followed by a bot's name to bring another model into the chat.

In the announcement post, Quora CEO Adam D’Angelo pitched this as a way to easily benchmark outputs across leading systems like Claude 3 Opus, GPT-4, and Mistral Large with a single click.

Instead of opening separate chats and pasting the same prompt over and over, you can stack their answers right next to each other to see which model handles your specific request best.

Passing the baton across workflows

Comparing responses is handy, but the real unlock is chaining models together without losing context.

D’Angelo outlined a sequential workflow: you can drop a massive document into Gemini 1.5 Pro to leverage its 1-million-token context window for deep analysis, @-mention a Web Search bot to pull in breaking news on the subject, and then call in a specialized writing bot to draft the final piece using all the accumulated context from the previous bots.

Because context carries through the thread, users no longer need to manually copy-paste intermediate notes or re-explain background info.

Poe currently bundles frontier models like GPT-4, DALL-E 3, Claude 2, Claude 3, StableDiffusion XL, and Gemini Pro under a $20-per-month subscription. D’Angelo noted that users have already built millions of custom bots on the platform. The multi-bot feature is now live across the web, desktop (Windows and macOS), and mobile apps (iOS and Android).

Why it matters

We think this is a very smart move that fundamentally shifts what an AI aggregator can be.

Until now, platforms like Poe were mostly treated as convenience stores: one login, one $20 subscription, and access to all the leading frontier models under a dropdown menu. But once you switch to a collaborative multi-bot thread, Poe stops being just a multi-model dashboard and starts acting like an orchestration layer. For users who rely on different models for different tasks, this eliminates the friction of being a human copy-paste bridge between closed ecosystems.

It also poses a strategic challenge to standalone model providers like OpenAI and Anthropic. If users get used to treating individual models as specialized sub-agents in a shared workspace, brand loyalty shifts from the underlying model to the platform coordinating the team.

The catch? Chaining multiple frontier models in a single thread will inevitably chew through compute and token limits at blistering speed. Moreover, because different LLMs handle massive contexts and system prompts differently, passing complex, multi-model transcripts back and forth might lead to unexpected hallucination or context degradation down the line.