AUTOMATIONSWITCH

AI Workflows

AI agents, LLM pipelines, and intelligent automation for production systems.

AI workflows sit at the intersection of language models, agent frameworks, and automation infrastructure. This pillar covers how to build, deploy, and operate AI-powered systems: from single-prompt pipelines to multi-agent orchestrations that plan, execute, and verify autonomously. Guides here explore MCP server integration, Claude Code and Cursor workflows, RAG pipelines, and the governance layer that separates reliable agents from fragile demos. Each article is grounded in practitioner experience and benchmarked data, with clear architectural recommendations for teams moving from prototype to production.

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Dark hero showing a SKILL.md file on a cream card with an amber magnifying-glass overlay highlighting suspicious frontmatter fields, next to a pass/fail verification checklist.
Deep Dive
36.82% of community agent skills contain security flaws. Here is how to find them before they find you.

Agent Skills Security Audit Guide: How to Verify SKILL.md Files Before You Install

36.82% of community agent skills contain security flaws. 76 confirmed malicious payloads. A 15-point audit checklist, 8 vulnerability types with CVEs, and frameworks for verifying SKILL.md files.

Apr 2026
28 min read
Automation Switch
Tool Guide
SKILL.md Templates by Project Type: Starter Configs for Every Stack
Apr 2026
18 min
Tool Guide
21 Best SKILL.md Files Every Developer Should Install
Apr 2026
22 min
Dark hero showing MCP protocol architecture split into a solid auth layer and an open surface covering rate limiting, input validation, and audit logging.
Deep Dive
The protocol is everywhere. The security model is half-finished.
MCP Security: What the Spec Covers and What It Leaves to You
MCP connects AI agents to external tools. The auth spec is solid. The attack surface around it is wide open. Here is what the protocol enforces, what it leaves to you, and how to close the gaps.
Apr 2026·16 min
Dark hero showing three manifest files side by side on cream cards — SKILL.md, AGENTS.md, CLAUDE.md — with amber VS badges between them and the question When to use each? as headline.
Fundamentals
Three files. Three purposes. One system that actually works.
SKILL.md vs AGENTS.md vs CLAUDE.md: When to Use Each
CLAUDE.md sets project-wide defaults. AGENTS.md governs multi-agent behaviour. SKILL.md teaches a specific task. A decision matrix and project structure guide for choosing the right file.
Apr 2026·18 min
PydanticAI agent code alongside LangGraph StateGraph code, split-screen comparison of two Python agent frameworks
Tool Guide
Two production philosophies
PydanticAI vs LangGraph: Two Different Production Bets
PydanticAI brings type-safe, injection-first agents. LangGraph brings stateful graph execution. These are distinct production bets, each shaped by a different philosophy.
Apr 2026·12 min
Dark canvas header showing four agent framework names arranged as a branching decision path with LangChain, CrewAI, AutoGen and LangGraph as endpoints
Deep Dive
Deep Dive
LangChain vs CrewAI vs AutoGen vs LangGraph: Which AI Agent Framework Should You Actually Use?
Four frameworks, four different production problems. LangChain for breadth, CrewAI for prototyping speed, AutoGen/MAF for enterprise, LangGraph for execution control. Here is how to choose wisely.
Apr 2026·12 min
13 editorial components arranged in a systematic grid on a dark background with amber and blue accent colours, representing the AutomationSwitch component library architecture
Deep Dive
13 components. 5 profiles. One system.
How We Built a 13-Component Library That Structures Every Article on This Site
A codified component library with placement rules, justification tests, and content profiles governs every article on AutomationSwitch. Here is the full system and how to build your own.
Apr 2026·12 min
Step-by-step visual guide showing the progression from a simple Python script to a working AI agent with tool-calling and MCP integration
Tool Guide
Tutorial
Building Your First AI Agent: A Step-by-Step Guide
Go from zero to a working AI agent in under 100 lines. Tool-calling, reasoning loops, and MCP integration with practical Python code you can copy, run, and extend.
Apr 2026·15 min
Dark editorial visual showing the four components of an AI agent: language model, memory, planning, tool use, arranged around a central reasoning loop, with an amber highlight on the active node.
Fundamentals
Fundamentals
What Are AI Agents and How Do They Work
AI agents plan, execute, and verify tasks autonomously. This guide explains how they work, what separates them from chatbots, and where they fit in your automation stack.
Apr 2026·12 min
The Automation Switch Skills Hub: a directory of 46 production AI agent skills organised across nine categories
Standalone
Why we built the index the agent ecosystem was missing
The Automation Switch Skills Hub: What We're Building and Why
The Automation Switch Skills Hub is a curated directory of 46 production AI agent skills across nine categories. Here is what we are building, why we built the internal index, and what to expect as the hub grows.
Apr 2026·10 min
Map of MCP server discovery sources showing directories, registries, and meta-indexes across the ecosystem
Tool Guide
12,000+ servers across directories, registries, and indexes.
Where to Find MCP Servers in 2026: Every Directory, Registry, and Index
The navigation guide to MCP server discovery across 12,000+ servers. Compare PulseMCP, Smithery, Glama, MCP.so, the official registry, and every major index to find the right one for your workflow.
Apr 2026·10 min