💬 Cross-Platform Chat Agent
Chat SDK delivers one AI agent across Slack, Teams, Discord, WhatsApp, Telegram, GitHub, and Linear. Single codebase, single deployment, with platform-specific rendering handled by adapters.
The Problem
Companies want AI assistants available everywhere — website, Slack, Teams, Discord, mobile. Without a unified approach, you build and maintain separate integrations for each platform:
- Separate codebases per platform (7 platforms = 7 repos)
- Different message formats, APIs, authentication flows
- Agent logic duplicated and eventually drifts out of sync
- Testing and deploying 7 separate services
The Chat SDK Solution
🔄 One Agent, All Platforms
Define your agent's capabilities once — tools, system prompt, model config. Chat SDK handles platform-specific message formatting, input parsing, and response rendering.
🔌 Platform Adapters
Each platform (Slack, Teams, Discord, etc.) has an adapter that translates between the platform's API and Chat SDK's unified interface. Add a new platform by adding one adapter.
💾 Unified Conversation State
Conversation history stored in Postgres/Redis. Platform-specific metadata (Slack thread_ts, Teams conversation id) handled transparently.
✨ Rich Responses
Agent returns structured responses (text, buttons, forms, images). Each adapter renders these in the platform's native format — Slack blocks, Teams cards, Discord embeds.
Supported Platforms
Architecture
Webhook Receivers
Each platform sends messages to /api/webhook/{platform}. Route handlers parse platform-specific payloads into a unified Message format.
Chat SDK Core
Unified agent logic: system prompt, tools, model selection (via AI SDK), conversation management. Platform-agnostic.
AI SDK + AI Gateway
Model calls via AI SDK with AI Gateway for routing, failover, and cost tracking. streamText() for real-time responses.
Platform Adapters (Output)
Structured agent responses → platform-native format. Text becomes Slack blocks, Teams adaptive cards, Discord embeds.
State Store
Postgres for conversation history, user preferences. Redis for rate limiting and session cache.
🎯 SE Interview Takeaway
Chat SDK embodies the composable architecture principle: one core agent deployed on Vercel, with adapters for each platform. When a customer says "we need our AI assistant in Slack AND on our website AND in Teams," the answer is one Next.js app with Chat SDK — not three separate projects. This is a powerful sales conversation: one deployment, one billing, one codebase, all platforms.