Human APIs vs. Agent APIs: The Orchestration Problem скачать в хорошем качестве

Human APIs vs. Agent APIs: The Orchestration Problem

Traditional REST APIs were designed for deterministic humans using UIs. If you plug a probabilistic LLM agent directly into them, your production system will fail. We are in the middle of a massive architectural shift in software engineering: moving from Human-Centric API design to Agent-Centric API design. When AI agents attempt multi-step workflows (like filling out complex forms or executing financial transactions), they lose context and state, leading to hallucinations and API errors. In this video, we explain the fundamental impedance mismatch between stateless APIs (CRUD) and probabilistic LLMs. We explore why we must decouple the API from the agent using state-machine orchestrators like LangGraph, and how to rethink schema design for autonomous systems in high-stakes domains like finance and legal tech. ⏳ Timestamps: 0:00 - The problem with traditional APIs and AI Agents 3:15 - Deterministic systems (UIs) vs. Probabilistic systems (LLMs) 6:40 - Why LLM Agents fail at multi-step workflows 10:00 - The Orchestration Layer: Controlling Agent behavior 14:20 - Using LangGraph and State Machines for APIs 18:45 - Why finance and legal sectors demand Agent Schemas 21:10 - The future of Agentic API Architecture 🔗 Links : Check out LangGraph documentation: https://www.langchain.com/langgraph Read the paper on Agent API Schemas: https://arxiv.org/html/2503.23886v1#:.... Subscribe for deep dives into AI Engineering and Backend Architecture! 🏷️ Tags & Hashtags Hashtags: #AIAgents #LangGraph #APIArchitecture #SoftwareEngineering #LLM Tags: AI agents, API design for AI, LangGraph tutorial, LLM orchestration, multi-step LLM workflows, REST API vs Agent API, AI state management, backend engineering, OpenAI function calling, autonomous agents, enterprise AI architecture.