What are the best tools for agentic applications?

The ecosystem for building agentic AI applications features a diverse range of tools, depending heavily on your preferred programming language, the level of control you want over the agent's reasoning loop, and whether you prefer low-code configurations. The primary tools available for building and running AI agents include:Code-First Orchestration FrameworksLangGraph: Built by the creators of LangChain, this framework models applications as state machines (graphs of states and transitions). It is widely considered the industry leader for production environments when you need high control, loops, human-in-the-loop steps, and robust error recovery. CrewAI: Ideal for organizing agents into a structured corporate hierarchy or workflow. It allows you to quickly assign roles, goals, and tasks to multiple agents, making it the top choice for fast role-based multi-agent prototyping. Microsoft Agent Framework (formerly AutoGen): The unified successor to AutoGen and Semantic Kernel. It excels at event-driven multi-agent conversations and data science pipelines, and is heavily optimized for teams working within the Microsoft Azure ecosystem. PydanticAI: Highly popular for Python developers who demand type safety, structured outputs, and validated tool inputs, bringing a FastAPI-like experience to AI agent development. Mastra: A standout framework built specifically for full-stack TypeScript teams. It includes built-in state management, integration with React/Next.js, and support for Model Context Protocol (MCP). smolagents: Hugging Face’s lightweight, code-first framework where agents operate by generating raw Python code blocks rather than large JSON structures, maximizing flexibility. LlamaIndex (Workflows): Best suited for document-centric AI applications and data-heavy, event-driven multi-agent operations requiring heavy retrieval-augmented generation (RAG) capabilities.Lab-Specific SDKsOpenAI Agents SDK: A highly efficient, lightweight toolkit designed specifically for developers who want to delegate tasks between tightly scoped assistants, leverage OpenAI’s native tool-calling features, and enforce safety guardrails without adopting a bulky framework. Google Agent Development Kit (ADK): A code-first framework designed for teams leveraging Gemini and Vertex AI, providing managed agent runtimes and local developer UI testing capabilities. Low-Code & Visual Buildersn8n: A popular open-source, visual workflow automation platform that features native AI nodes, letting you connect various web services to custom agent steps without writing code from scratch. Dify: An open-source LLMOps and visual development platform that integrates built-in RAG architectures, ReAct logic, and prompt engineering utilities into a drag-and-drop interface. Gumloop: A visual workflow platform built for connecting multi-step agents to existing business apps using natural language orchestration, and allowing integration directly through Slack. Agent Infrastructure & ToolingStackOne: An integration infrastructure tool that provides agents with secure access to thousands of pre-built actions across enterprise SaaS tools (like Salesforce or Workday) with managed authentication and compliance compliance. Langfuse / LangSmith: Crucial debugging and observability tools that trace what an agent is thinking, what tools it is calling, and how much each agent step costs.