Agent frameworks for software development

An agent framework helps you build AI systems that can plan work, call tools, write or inspect code, run commands, use files, delegate subtasks, and keep state across multi-step workflows. For software development, they are useful for coding assistants, code review bots, test-generation agents, migration tools, documentation agents, DevOps agents, and multi-agent engineering workflows.

Main options in 2026

Framework	Best for	Notes
OpenAI Agents SDK	Production agent apps, coding/tool workflows, OpenAI-native systems	Lightweight framework for agents that plan, call tools, collaborate, and maintain state. OpenAI describes it as a way to build agents in code and grow into advanced runtime patterns. (OpenAI Developers)
LangGraph / LangChain Agents	Complex orchestration, durable workflows, graph-based control	Strong choice when you need explicit state, branching, retries, checkpoints, and control over agent execution. LangChain now directs new agent work toward LangGraph. (LangChain)
Microsoft AutoGen / Agent Framework	Multi-agent collaboration, enterprise .NET/Python ecosystems	AutoGen focuses on multi-agent applications; Microsoft’s newer Agent Framework combines AutoGen-style abstractions with Semantic Kernel enterprise features like state, telemetry, middleware, and graph workflows. (microsoft.github.io)
CrewAI	Simple role-based multi-agent prototypes	Good for quickly modeling “developer,” “reviewer,” “tester,” “planner” style agents. Often simpler to start with, but may be less ideal when you need fine-grained production orchestration.
Semantic Kernel	Enterprise copilots, Microsoft stack, plugin/tool integration	Useful when your software agent needs strong integration with Microsoft services, typed plugins, planners, and enterprise deployment patterns.
Pydantic AI	Typed Python agents, structured outputs	Good when correctness, validation, typed outputs, and clean Python ergonomics matter more than elaborate multi-agent orchestration.
Google ADK / Vertex AI Agent tooling	Google Cloud-native agent apps	Best when your stack is already on Google Cloud and you want managed cloud integrations.

How to choose

For a coding agent inside a real product, start with OpenAI Agents SDK or LangGraph. Pick OpenAI Agents SDK when you want a relatively direct agent runtime with tool calling, tracing, and OpenAI model integration. Pick LangGraph when you want explicit workflow graphs, durable state, and more control over orchestration.

For a multi-agent experiment or demo, CrewAI or AutoGen is often faster to prototype.

For an enterprise Microsoft environment, look at Microsoft Agent Framework / Semantic Kernel, especially if you need telemetry, middleware, type safety, and Azure integration. Microsoft says its Agent Framework combines AutoGen’s agent abstractions with Semantic Kernel’s enterprise capabilities. (Microsoft Learn)

For strict structured output and validation, Pydantic AI is attractive, especially in Python backends.

Typical architecture for software-development agents

A practical agent system usually has:

1. Planner — breaks a request into steps.
2. Code reader — searches the repo, reads files, understands structure.
3. Editor tool — modifies code safely.
4. Executor — runs tests, linters, type checks, builds.
5. Reviewer — checks diffs, security risks, regressions.
6. Memory/state — remembers task context, decisions, repo conventions.
7. Guardrails — permissions, sandboxing, secrets protection, approval gates.

For serious development workflows, the most important features are not “multi-agent chat”; they are tool reliability, sandboxing, observability, rollback, deterministic workflows, and test feedback loops.

Recommended starting point

For most teams building software-development agents today:

Use LangGraph when you need robust orchestration and stateful workflows.

Use OpenAI Agents SDK when you want a clean production-oriented agent layer with strong OpenAI integration and tool execution patterns.

Use CrewAI only if you mainly want a quick multi-role prototype.

Use Microsoft Agent Framework if your organization is already committed to Azure, Semantic Kernel, or Microsoft developer infrastructure.