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Agent engineering teams keep having the same conversation. Which agent framework should we pick? They list LangGraph, DSPy, the Claude Agent SDK, their own in-house setup, and whatever launched last week, then try to compare them side by side. Teams burn weeks on the comparison. They write decision docs. They run bake-offs. They commit, and six months later they have the conversation again because the field has moved and the previous answer no longer feels right.
This is not a strategic question. It is a symptom. The word "framework" papers over two layers that should never have been one, and the comparison breaks down the moment you look at what each tool actually does.
What is an agent runtime?
An agent runtime is the production layer underneath an agent. It owns the things every web service owns: HTTP and streaming endpoints, session lifecycle, authentication, role-based access control, retries, horizontal scaling, observability, tracing, audit logging, and governance. An agent framework, by contrast, owns how the agent expresses itself: how control flows, how tools are described, how prompts and signatures compose, and how sub-agents communicate.
These are two different jobs. Most early agent frameworks bundled them. That bundling is what teams are paying for now.
What do people mean when they say "agent framework"?
When an engineer says they picked LangGraph, they usually mean two unrelated things at once.
The first is how the agent expresses itself. Graphs of nodes. Declarative signatures. Plain Python. Message-passing between sub-agents. This is the orchestration layer. It holds the actual ideas about how an agent should reason. It is the layer that benefits from competition and iteration. New patterns show up here every few months, and they should.
The second is how the agent runs in production. HTTP and streaming endpoints, session lifecycle, authentication, role-based access control, retries, horizontal scaling, observability, tracing, audit logging, and governance. This is the runtime layer. Every team solves roughly the same problem, and adjacent domains have solved it for more than a decade. Nothing about it benefits from a per-framework reinvention.
Most "framework wars" arguments collapse the moment you separate these two layers. The orchestration choice is interesting and contestable. The runtime choice should be boring.
Why did agent frameworks bundle the runtime?
Early agent frameworks shipped a runtime because they had to. No shared deployment story existed in 2023, so each framework wrote its own server, its own session store, its own streaming protocol, its own tracing format. That decision made sense at the time. It is also the source of most of the pain in 2026.
The cost of bundling shows up in three places.
First, switching costs balloon for no good reason. Changing how a team expresses agent logic, whether they move from one orchestration tool to another or rewrite against a new pattern, should answer a question about ergonomics and fit. Instead it becomes a re-platforming project because the deployment surface ships with the orchestration code.
Second, operational patterns fragment. Every framework models sessions slightly differently. Every framework streams slightly differently. Every framework integrates auth slightly differently. Multiply the differences by the number of agents a team runs and the number of incidents they handle at 2am.
Third, the runtime lags the orchestration. Frameworks ship new reasoning patterns fast and new production patterns slowly, because production is not the interesting part of the project. Teams end up forking the runtime to get JWT support, or rate limiting, or whatever they need next.
Agent framework vs. agent runtime: summarized
If you read nothing else, that is the argument.
What would "winning" have looked like?
The phrase "framework wars" assumes one of the contenders should pull ahead and become the standard. That outcome is neither likely nor desirable. The orchestration layer is where agent engineering is still inventing itself. The field needs many frameworks. It needs sharp opinions. It needs the framework that ships next year to beat the one that shipped last year, and it needs teams to move to the new one cheaply.
What the field does not need is for that movement to require rebuilding the production layer.
The actual fight: framework lock-in vs. runtime decoupling
The real question is not which framework wins. The question is whether the runtime decouples from the framework at all.
A useful test: Imagine your team picked the wrong framework eighteen months ago. What does the migration look like? If the answer involves reimplementing sessions, reimplementing streaming, reimplementing auth, and reimplementing tracing, then the framework is not the problem. The architecture is. The framework is doing two jobs, and one of them is in the way.
If the answer is "rewrite the agent against a different SDK and redeploy," the architecture is right, no matter which framework the team happened to pick.
How does Agno separate the agent runtime from the framework?
Agno makes two things: AgentOS, a framework-agnostic runtime, and the Agno SDK, an optional first-party framework. The runtime is the load-bearing piece.
Your team writes the agent in whatever framework makes sense: LangGraph, DSPy, the Claude Agent SDK, the Agno SDK, your own code. AgentOS handles the production surface underneath: APIs, sessions, streaming, scale, auth, observability, and governance. The orchestration choice stays contestable. The runtime choice stops mattering.
Agno ships a first-party SDK because some teams want one. The SDK is optional, not required, and nothing about AgentOS assumes you use it.
The framework wars were never the real fight. The fight is whether your production layer survives the next three frameworks.