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AgentBridge Requirements

Problem

Agent framework choice is becoming a long-term architecture decision too early in the build cycle. Teams often prototype with one framework, then discover they need a different runtime for production concerns such as state, typed outputs, tracing, governance, deployment, or UI event compatibility.

AgentBridge reduces framework lock-in by providing a framework-neutral agent specification and adapter interface.

Target Users

  • Startup teams that prototyped with a high-level framework and now need production behavior.
  • Platform teams supporting multiple agent frameworks across internal product teams.
  • AI engineers comparing frameworks before committing to one runtime.
  • App developers who want normalized streaming and tool events regardless of backend.

Goals

  • Define an agent once with AgentSpec.
  • Run the same spec through multiple backend adapters.
  • Normalize results and stream events.
  • Preserve backend escape hatches through raw fields.
  • Make missing optional framework dependencies obvious and actionable.
  • Provide enough examples to explain the migration story quickly.

Non-Goals

  • AgentBridge is not a new agent framework.
  • AgentBridge does not host a gateway server in v0.
  • AgentBridge does not replace AG-UI, MCP, LiteLLM, LangGraph, CrewAI, or Pydantic AI.
  • AgentBridge does not automatically convert existing framework projects in v0.
  • AgentBridge does not own model-provider routing; it uses LiteLLM-style model names.

Success Criteria

  • A developer can define one simple AgentSpec.
  • The same spec can run against the included mock backend and compile through optional framework adapters.
  • RunResult and AgentEvent have stable JSON-serializable shapes.
  • Examples demonstrate backend selection, tool use, streaming, and AG-UI-shaped event conversion.
  • Tests can run without paid model API calls.
  • Adapter docs state adopted and verified framework versions.