AI agent frameworks are tools designed to streamline the development, deployment, and management of autonomous AI agents, which process information and make decisions to achieve specific goals. These frameworks typically offer pre-built components and abstractions, supporting various features like agent architecture, memory management, task orchestration, and tool integration. Key considerations for selecting an appropriate framework include the programming language, development team, popularity, features, and supported AI models. Notable frameworks such as AutoGen, LangChain, and OpenAI Agents SDK offer diverse capabilities, ranging from multi-agent systems and modular design to low-code interfaces and production-ready workflows. These frameworks cater to different use cases and scenarios, enabling developers to build sophisticated, scalable, and reliable AI systems. Integration with real-time web access and robust data infrastructure is essential for developing smarter, faster, and production-ready AI applications.