openai7 min read
OpenAI Assistants API — Build AI Agents
Complete guide to building AI agents with OpenAI Assistants API for production applications.
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Agents
14 articles
agents4 min read
LLM Agents — Build Autonomous AI Agents
Build autonomous AI agents that use tools and take actions independently.
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langgraph2 min read
LangGraph — Stateful AI Agents Tutorial
Build stateful agents with LangGraph for complex workflows.
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ai7 min read
Google''s A2A Protocol — How AI Agents Talk to Each Other in Production
Explore Google''s Agent-to-Agent (A2A) protocol for production multi-agent systems. Learn agent cards, task lifecycles, and how to orchestrate multiple AI agents at scale.
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ai10 min read
Designing AI Agent Tools — Schema, Errors, and Idempotency for LLM Tool Use
Master the art of designing tools that LLMs can reliably use. Learn schema patterns, error handling, idempotency, and production tool registries.
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api-design6 min read
Designing APIs for AI Agent Consumers — Not Humans
Design APIs for AI agents: structured errors, idempotency keys, verbose context, bulk operations, OpenAPI specs, token-based rate limiting, and version stability.
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ai9 min read
CrewAI in Production — Building Multi-Agent Teams That Actually Deliver
Deploy CrewAI multi-agent systems to production. Learn crew composition, memory systems, custom tools, and scaling patterns for reliable AI teams.
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ai8 min read
LangGraph in Production — Stateful AI Agents With Checkpointing and Human-in-the-Loop
Master LangGraph for production AI agents. Learn stateful workflows, checkpointing, human-in-the-loop patterns, and deployment strategies.
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langgraph12 min read
LangGraph in Production — Stateful Agent Workflows With Checkpointing
Build production-grade stateful agents with LangGraph: graph definitions, Postgres checkpointing, human interrupts, streaming, error handling, and deployment.
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agents12 min read
Building LLM Agents With Tool Use — Reliable Agentic Workflows for Production
Design bulletproof LLM agents with structured tool definitions, parallel execution, result validation, human-in-the-loop gates, and comprehensive observability.
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ai6 min read
Model Context Protocol (MCP) — The HTTP of AI Agent Communication
Learn how Anthropic''s Model Context Protocol enables AI agents to securely share tools and context. We explore the open standard, build an MCP server, and compare it to function calling.
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ai7 min read
Multi-Agent Orchestration in 2026 — Puppeteer, Specialist Agents, and Production Patterns
Build scalable multi-agent systems using the orchestrator-worker pattern. Learn task routing, state management, error recovery, and production deployment patterns.
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ai7 min read
Plan-and-Execute — Reducing LLM Costs by 90% With Heterogeneous Agent Fleets
Learn the Plan-and-Execute pattern for slashing AI inference costs. Use frontier models for planning, cheap models for execution, and optimally route tasks by type.
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RAG5 min read
Agentic RAG — When Your RAG Pipeline Thinks Before It Retrieves
Learn how agentic RAG systems use reasoning and iterative retrieval to outperform static RAG pipelines, including CRAG, FLARE, and self-ask decomposition patterns.
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