CrewAI vs AutoGen vs LangGraph: Choosing a Framework
CrewAI vs AutoGen vs LangGraph compared on architecture, state, multi-agent support, and operations, plus where Microsoft Agent Framework…
Category
AI
These AI guides cover language models, agents and the tools I use to ship real features. The aim is simple: less hype and more working detail.
For example, start with the MCP explainer or AI agent harnesses. After that, the AI tools matrix compares what is worth adopting. Each post also points to the deeper series under AI Agents, Claude and n8n.
40 articles
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LangGraph for Agents: Stateful, Cyclic Workflows
How LangGraph models agents as stateful, cyclic graphs: state schemas, nodes, checkpointing, human review interrupts, and when to…
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Human-in-the-Loop: Approvals, Escalation, and Guardrails
Designing human-in-the-loop agents: approval boundaries, escalation, review, override, audit trails, and how guardrails differ from permission checks.
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Planning and Reasoning: ReAct, Plan-and-Execute, and Tree-of-Thought
AI agent planning and reasoning patterns: how ReAct, plan-and-execute, and tree-of-thought work, and when each one earns its…
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Agent Memory: Short-Term, Long-Term, and Episodic
Agent memory for AI agents: short-term, long-term, and episodic stores, with write policies, retrieval, freshness, and how memory…
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Tool Use and Function Calling: Giving Agents the Ability to Act
How tool use and function calling work in AI agents: tool contracts, JSON schemas, validation, authorization, and error…
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When to Use an AI Agent (and When a Workflow Is Enough)
When to use an AI agent instead of a workflow: a decision framework comparing predictability, cost, and failure…
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The Anatomy of an AI Agent: LLM, Tools, Memory, and the Control Loop
Inside the anatomy of an AI agent: the control loop, model calls, tool execution, state transitions, memory, and…
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What Is an AI Agent? Definitions, Components, and How It Differs from a Chatbot
What is an AI agent? A practical definition: the components inside an agent system, how agents differ from…
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AI Agents: The Complete Guide to Architecture, Frameworks, and Production Deployment
A complete guide to building reliable AI agents: architecture, tools, memory, frameworks, evaluation, observability, security, and production deployment.
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MCP Explained: Model Context Protocol Guide
MCP standardizes how apps expose tools, resources, and prompts to LLMs. I cover architecture, security, and working server…
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AI Agent Harnesses, Explained
The model is the brain; the harness is the room it works in. A field guide to loops,…
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The Claude Skills Blueprint Part 5: Production & Scale
Ship Claude Skills past the demo: eval loops, versioning, shared repos, and the under/over-trigger failures that show up…
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The Claude Skills Blueprint Part 4: The Orchestration Engine
Claude Skills as the conductor over MCP tools: data pass-off, validation gates, and multi-step workflows that do not…
