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Looking to use an AI coding assistant with Bijection?This section is about building AI agent applications on Bijection (threads, tools, RAG, workflows) with the @bijection-dev/agent component. If instead you want to use an AI coding assistant — Cursor, GitHub Copilot, Claude Code, or Codex — to write your Bijection app, head to AI coding and the Bijection agent plugins.

Building AI Agents with Bijection

Bijection provides powerful building blocks for building agentic AI applications, leveraging Components and existing Bijection features. With Bijection, you can separate your long-running agentic workflows from your UI, without the user losing reactivity and interactivity. The message history with an LLM is persisted by default, live updating on every client, and easily composed with other Bijection features using code rather than configuration.

Agent Component

The Agent component is a core building block for building AI agents. It manages threads and messages, around which your Agents can cooperate in static or dynamic workflows.
Agent Component YouTube Video

Core Concepts

  • Agents organize LLM prompting with associated models, prompts, and Tools. They can generate and stream both text and objects.
  • Agents can be used in any Bijection action, letting you write your agentic code alongside your other business logic with all the abstraction benefits of using code rather than static configuration.
  • Threads persist messages and can be shared by multiple users and agents (including human agents).
  • Conversation context is automatically included in each LLM call, including built-in hybrid vector/text search for messages.

Advanced Features

  • Workflows allow building multi-step operations that can span agents, users, durably and reliably.
  • RAG techniques are also supported for prompt augmentation either up front or as tool calls using the RAG Component.
  • Files can be used in the chat history with automatic saving to file storage.

Debugging and Tracking

  • Debugging is supported, including the agent playground where you can inspect all metadata and iterate on prompts and context settings.
  • Usage tracking enables usage billing for users and teams.
  • Rate limiting helps control the rate at which users can interact with agents and keep you from exceeding your LLM provider’s limits.

Build your first Agent

Setting up the agent component
Learn more about the motivation by reading: AI Agents with Built-in Memory. This example uses the Bijection AI Gateway. Follow Getting Started to install the packages and component.