?? AI agents are becoming more capable, integrating real-time web search, GUI interactions, and tool orchestration for complex, multi-step workflows.
George Polzer
Sr. Product Manager AI/ML | EU & US Go-to-Market / MVP Consultant | Emerging Tech - Agentic AI, Agent Ops Focus??
Early frameworks like LangChain, AutoGen, and CrewAI (2022-2024) helped structure LLM-based workflows by integrating tools such as Retrieval Augmented Generation (RAG) and function calling.
As AI models have gained multimodal capabilities (vision, reasoning, and planning) and tool-calling functions, the next-gen agent frameworks emerged, moving "upstream" and expanding in scope.
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? OpenAI has released four key components to power AI agent development:
1?? Responses API
?? A new unified API that integrates multiple AI models and built-in tools to streamline complex workflows.
?? Designed to replace the Assistants API by 2026.
?? Supports multi-turn conversations and advanced task execution with fewer API calls.
2?? Built-in Tools
OpenAI has exposed internal agentic tools to developers, allowing them to build custom AI agents with:
?? Web Search – Provides real-time, cited search results using a fine-tuned GPT-4o-search model.
?? File Search – Integrates RAG-based private document retrieval with custom metadata filtering.
?? Computer Use (CUA) – AI agents can interact with GUI interfaces (e.g., execute tasks via screenshots).
3?? Agents SDK (Model-agnostic)
An open-source framework for orchestrating single-agent and multi-agent workflows with:
?? Configurable agents
?? Built-in guardrails for safety
?? Tracing & observability tools
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? The Rise of Anthropic’s Model Context Protocol (MCP)
?? MCP is an open, model-agnostic protocol introduced in late 2024.
?? Standardizes AI-to-tool integration by allowing LLMs to connect to external knowledge bases, databases, and APIs without building custom connectors.
?? Uses a client-server model where MCP servers expose data, and MCP clients query it dynamically.
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? LangChain, Agent Protocol, and AGNTCY – The Push for AI Agent Interoperability
?? LangChain, a popular LLM framework, has evolved to support agent-based workflows.
?? LangGraph enables deploying agents across multiple frameworks (CrewAI, AutoGen, etc.).
?? LangChain’s Agent Protocol – Introduced last year as an interoperability standard for AI agents.
?? AGNTCY – A new initiative (led by Cisco) aiming to create an open "Internet of Agents" where AI agents can discover, connect, and collaborate seamlessly.
?? Key trends shaping the next-gen AI agent ecosystem:
? Standardization is critical – MCP, LangChain’s Agent Protocol, and AGNTCY are pushing for interoperable AI tools.
? Open-source is the way forward – Successful AI tools (LangChain, Goose, MCP, OpenAI’s Agents SDK) embrace openness.
? AI reasoning + better grounding = more reliable AI agents – With Web Search + File Search + Computer Use, agents will generate more accurate and actionable results.
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?? Agentic Systems are the future of AI
? Join the AI Agent Ops Linkedin Group: https://Linkedin.com/groups/6592276
Managing Partner at zConatus
7 小时前Funny how, when talking about AI, its results are always something to be waited for. After all, if it is already intelligent, what exactly are we waiting for? Intelligence, maybe?,