Most agent framework debates skip the first question:

Do you need a framework at all?

For one agent calling one or two tools, I would usually skip LangGraph, CrewAI, AutoGen, and most orchestration layers.

Raw model calls plus structured outputs are easier to inspect, cheaper to run, and less painful to debug.

Frameworks start earning their complexity when you need branching control flow, persistent state, retries, human approval gates, memory, multi-agent coordination, or long-running execution.

My rough 2026 map:

My personal rule:

If the workflow is simple, avoid the framework.

If the workflow needs state, approvals, retries, audit trails, or complex routing, use LangGraph.

If the goal is to prototype a multi-agent role pipeline quickly, use CrewAI.

If retrieval is the real problem, start with LlamaIndex or Haystack before adding an agent layer.

If long-term memory is the product, look at Letta.

If browser control is the job, Browser Use is the more relevant category.

The biggest mistake I see is choosing an agent framework before defining the job.

A good agent spec should say what the agent can do, which tools it can call, what state it needs, when a human must approve, and what failure looks like.

Without that, the framework debate is mostly noise.