AI Agents & Orchestration AI Tools
Open-source frameworks for building AI agents, chaining LLM calls, structured generation, and multi-step reasoning workflows.
A single model call answers a single question. Production work needs retrieval, tool calls, retries after a malformed parse, handoffs between a cheap model and an expensive one, and state that survives across turns, which is where a hand-rolled loop around a chat completion stops being maintainable. The audience is backend and platform engineers. By 2026 the field has split into four camps disagreeing about how much control flow belongs to the model. Explicit libraries like LangChain, Haystack and Semantic Kernel keep the graph in code, so paths stay inspectable and token spend stays boundable. Autonomous role-based systems like AutoGen, CrewAI and MetaGPT let the loop decide who acts next, which prototypes fast and debugs badly. Visual builders such as Dify, Langflow and n8n trade git-diffable logic for a canvas a non-specialist can edit. Constrained generation projects, DSPy, Outlines and Guidance, attack reliability at the decoder rather than the agent layer. A reasonable first build starts with smolagents, whose core loop reads in one sitting, or Pydantic AI for teams that already lean on type hints and want tool schemas validated rather than hoped for. Dify is faster when the deliverable is an internal app rather than a library. The license field is worth reading first, since it is not uniformly open source here. n8n ships under the Sustainable Use license, which permits self-hosting and modification but not offering the product as a service to third parties, and similar fair-code terms only bite once someone tries to resell the result.