AI agents are systems that combine large language models, tooling, and stateful orchestration to perform multi-step, autonomous tasks. This buyer’s guide focuses on two converging categories: Agent Frameworks (developer stacks for building, testing, and deploying agents) and Agent Marketplaces (no-code/managed platforms for publishing and running agents). As of 2025-12-07 the market is maturing: providers such as Google (Gemini agent tooling), OpenAI (Operator/agent tooling) and Anthropic (agentic features) coexist with ecosystem projects that prioritize composability, observability, and safety. Key tools illustrate common patterns: LangChain (engineering platform with LangGraph for stateful agent flows) and LlamaIndex (document agents and RAG orchestration) support developer-first, production-grade agents. AutoGPT, AgentGPT, Agentverse and Continue demonstrate different trade-offs between autonomy, hosting (self-hosted vs cloud), and no-code templates. Warp and Replit bring agents into developer workflows and IDEs (Agentic Development Environments and embedded assistants), while GitHub Copilot and Aider represent tight editor/terminal copilots and local pairing for code-focused agentic tasks. Trends buyers should note: state management and provenance (stateful graphs), retrieval-augmented generation, standardized evaluation and observability, and layered guardrails for safety and abuse detection. Market realities include mixed hosting models, marketplace governance and occasional moderation or access restrictions during evaluation. Practical selection criteria are integration surface, deployment options, observability/evaluation tooling, governance and cost. This guide synthesizes current platform capabilities and ecosystem roles to help engineering and product teams match agent frameworks and marketplaces to their operational and compliance needs.