AutoGen
AutoGen is a multi-agent framework from Microsoft with a layered architecture spanning low-level actor-model runtime primitives, high-level team orchestration, extension packages, and a visual Studio for workflow authoring. With 54K+ GitHub stars, it supports Python and .NET, offers distributed execution with gRPC worker runtimes, and provides multi-agent patterns including sequential, concurrent, swarm, and graph-flow styles. AutoGen targets teams building complex distributed agent systems that benefit from a mature, extensible ecosystem.
Jido
Jido is an Elixir framework that models each agent as a BEAM process with deterministic state transitions, explicit side effects, and OTP supervision. It separates pure business logic from LLM interactions, giving you reproducible testing and fault isolation at the runtime level. Jido targets teams building production agent systems that need to stay up, recover from failures, and scale predictably.
Side-by-side comparison
| Dimension | Jido | AutoGen |
|---|---|---|
| Language and runtime | Elixir on the BEAM VM with preemptive scheduling, lightweight processes, and built-in distribution | Python and .NET with an actor-model runtime supporting local and distributed execution via gRPC |
| Agent model | Each agent is a supervised OTP process with explicit state schema and deterministic transitions | Layered APIs: actor-based Core agents, team-oriented AgentChat agents, and no-code Studio workflows |
| Tool calling | Actions as composable, typed Elixir modules with schema validation; MCP client support | First-class tools in Core and AgentChat layers; MCP integration and extension-based tool adapters |
| Multi-agent coordination | OTP-native process communication via GenServer calls, PubSub, and dynamic supervision trees | Team abstractions with sequential, concurrent, swarm, and GraphFlow patterns; AgentTool composition |
| Failure handling | OTP supervisors restart failed agents automatically; process isolation prevents cascading failures | Distributed runtime with resilience emphasis; state save/load for recovery; termination conditions for teams |
| Observability | BEAM introspection (process info, message queues), Telemetry events, LiveDashboard integration | Logging/tracing guides with Jaeger integration; Studio provides visual debugging and workflow inspection |
| LLM provider support |
Provider-agnostic through jido_ai, supporting OpenAI, Anthropic, Google, and others via unified interface | Multi-provider through extension model clients; broad model compatibility across Python and .NET |
When to choose AutoGen
AutoGen is a strong choice when you need a mature distributed multi-agent runtime with a large ecosystem. Specific scenarios where AutoGen fits well:
- Distributed agent systems where AutoGen’s actor-model runtime scales from single-process to multi-node execution without changing your agent code.
- Python and .NET teams that want to stay in familiar ecosystems with broad library support and enterprise language options.
- Complex team topologies where sequential, concurrent, swarm, and graph-flow patterns give you flexible coordination models out of the box.
- Low-code operations where AutoGen Studio provides visual workflow authoring, run inspection, and iterative debugging without writing code.
When to choose Jido
Jido is a strong choice when you want the actor model built into the runtime rather than layered on top of Python. Specific scenarios where Jido fits well:
- Elixir/Erlang teams that want agents built on the same concurrency and fault-tolerance model they use for the rest of their system.
- Native actor-model guarantees where the BEAM provides true preemptive scheduling, per-process garbage collection, and message-passing isolation without framework abstractions.
- Deterministic testing needs where separating pure state logic from side effects lets you unit test agent decisions without mocking distributed runtime components.
- Always-on agent systems where OTP supervisors provide automatic restart and health monitoring as a runtime primitive, not an application-level pattern.
Get started
Ready to try Jido? Follow the getting started guide to build your first agent in under ten minutes.