| OpenAI Agents SDK | OpenAI-native agent apps with tools, handoffs, tracing, and guardrails | Clear platform fit when your model, tool, trace, and review loop are already OpenAI-centered. | Less neutral if your company wants every framework primitive to be provider-independent. | You want a direct path from OpenAI model APIs to agent workflows with reviewable traces. |
| LangGraph | Stateful, long-running, graph-shaped workflows with checkpoints and human-in-the-loop control | Strong for explicit state, retries, persistence, branching, subgraphs, and memory-aware flows. | Requires engineering discipline; teams must model state and edges instead of relying on a simple chat loop. | The workflow has durable state, multiple steps, conditional routing, or recovery requirements. |
| CrewAI | Role-based crews, business automations, and process-oriented agent teams | Accessible mental model for agent roles, tasks, flows, knowledge, memory, and observability. | Can hide too much complexity if teams skip deterministic process design and evals. | Business users understand the work as specialized roles collaborating on a process. |
| Microsoft Agent Framework | Microsoft-centric enterprises that need typed orchestration, telemetry, state, and model support | Combines AutoGen-style multi-agent patterns with Semantic Kernel enterprise features. | Best fit depends on Microsoft cloud, identity, developer, and governance alignment. | Your organization standardizes on Azure, Microsoft 365, .NET or Python, and enterprise telemetry. |