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Summary

Agent frameworks package recurring runtime problems such as state, tools, message passing, and control flow. In 2026, the most useful comparison question is no longer just “chat loop or graph?” It is “which abstraction owns the work: conversation, explicit workflows, engineering infrastructure, or load-on-demand skills and integrations?”

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Why It Matters

Teams usually reach for a framework after the first manual prototype starts to hurt. The pain is familiar:
  • duplicated agent loop code
  • unclear state handling
  • brittle tool wiring
  • weak observability
  • hard-to-debug multi-agent coordination
The framework market is now converging and branching at the same time. Microsoft is folding AutoGen and Semantic Kernel ideas into Agent Framework. Google ADK is pushing a skill-and-integration-first model. Older frameworks still matter, but the comparison surface is wider than the original conversation-versus-graph split.

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Mental Model

Six anchors help orient the current landscape:
  • AutoGen: conversation-first collaboration
  • CAMEL: lightweight role-driven collaboration
  • LangGraph: graph-structured control flow and recoverable state
  • Microsoft Agent Framework: unified agents plus explicit workflows
  • Google ADK: code-first agents with skills and integrations loaded on demand
  • AgentScope: engineering-first multi-agent infrastructure
These are not direct substitutes. They reflect different control centers:
  • conversation-first frameworks optimize collaboration as dialogue
  • graph-first frameworks optimize explicit state transitions and orchestration
  • skill-first frameworks optimize reusable expertise and tool ecosystems
  • engineering-first frameworks optimize runtime discipline and production concerns

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Architecture Diagram

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Tool Landscape

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Global coverage

  • AutoGen remains useful when a system should behave like a coordinated group of specialists exchanging messages.
  • CAMEL remains useful when role pairing and autonomous collaboration matter more than heavy orchestration.
  • LangGraph remains useful when loops, checkpoints, and recoverable state transitions need to be explicit.
  • Microsoft Agent Framework matters because it combines agent abstractions with enterprise features such as state management, middleware, telemetry, and graph-based workflows. It is the clearest current signal that the AutoGen and Semantic Kernel lines are being pulled into a shared successor.
  • Google ADK matters when agents should load expertise through skills and then connect quickly to external tools, partner platforms, and cloud services.

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China-linked coverage

  • AgentScope remains the clearest engineering-first reference in the current China-linked set, with stronger emphasis on large-scale coordination, runtime infrastructure, and production operations.

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Selection criteria

  • Choose conversation-first frameworks when collaborative behavior is the main abstraction.
  • Choose graph-first frameworks when explicit control flow, checkpointing, or mixed agent-function orchestration matters most.
  • Choose skill-first frameworks when reusable domain instructions and external integrations are central to the design.
  • Choose engineering-first frameworks when operational rigor arrives early and the team expects multi-agent systems to behave like software infrastructure, not just prompts.
  • If the task is deterministic enough to be a workflow or plain function, do not force it into an autonomous agent abstraction.

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Tradeoffs

  • Conversation-oriented frameworks feel natural for collaboration, but they can be harder to constrain and debug.
  • Graph-oriented frameworks are easier to reason about operationally, but they require more explicit design work upfront.
  • Skill-first frameworks reduce monolithic prompts and speed up reuse, but they introduce another packaging and evaluation boundary.
  • Engineering-heavy frameworks help when production requirements arrive early, but they can be excessive for small prototypes.
Useful defaults:
  • start from the control model, not brand familiarity
  • prefer workflows or plain functions for deterministic tasks
  • keep framework choice aligned with product surface and team capability
  • treat integrations and skills as first-class architecture, not afterthoughts

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Citations

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Reading Extensions

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Update Log

  • 2026-04-23: Refreshed the page with current Microsoft Agent Framework and Google ADK signals.
  • 2026-04-21: Initial repo-native draft based on imported reference material and lab rewrite rules.