The agent ecosystem is expanding rapidly. We surveyed the landscape to identify frameworks worth studying, integrating, or competing with.

CrewAI: Team-based Orchestration

CrewAI has emerged as a leader in multi-agent systems at scale. Unlike frameworks that rely on LLMs to route tools dynamically, CrewAI links tools directly to specific agents. This enables efficient task execution without the overhead of continuous routing decisions.

Notable: Proven to handle millions of agents monthly with human-readable configuration. The emphasis on declarative setups makes it accessible to teams new to agent orchestration.

AgentFlow: Low-Code Multi-Agent Canvas

New from Shakudo, AgentFlow wraps LangChain, CrewAI, and AutoGen inside a low-code canvas. Teams can sketch workflows, attach vector or SQL memory stores, and deploy to a self-hosted cluster with one click.

Potential: If the platform delivers on its promise, it could accelerate adoption of multi-agent systems significantly. The visual approach may lower barriers for non-developer stakeholders.

LangChain: Flexible but Heavy

LangChain remains the default for many teams building LLM-powered applications. Its modularity and robust abstractions make it adaptable to a wide range of use cases.

Trade-off: Resource-heavy with many external dependencies. Tool invocation depends on the LLM's natural language understanding, which can introduce latency and unpredictability compared to framework-routed alternatives.

AutoGen: Microsoft's Multi-Agent Play

Microsoft's AutoGen focuses on multi-agent collaboration. It's designed for scenarios where specialized agents work together to solve complex problems.

Note: Still emerging. Worth tracking for enterprise adoption signals, given Microsoft's market position.

LlamaIndex: Document-Centric Workflows

For agents that need to reason over complex documents, LlamaIndex provides workflows for extracting, synthesizing, and acting on document-based knowledge.

Use case: Complementary to other frameworks. Consider integrating LlamaIndex as a document layer on top of a routing framework like CrewAI.

Next Steps

We're evaluating CrewAI's direct tool binding approach for our own architecture. The efficiency gains could be significant for long-running autonomous workflows.

AgentFlow is on our watch list. If it matures, we may adopt it for visual workflow design while keeping core logic in our own system.