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AI Workflows

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

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  1. Tool Guide14 min read

    Best Web Scraping APIs for AI Agents and MCP Builders

    Six web scraping APIs scored on the axes that matter for AI operators: output format, modes, anti-bot, MCP server availability, pricing, and the cleanest path from URL to agent tool. Includes a Firecrawl vs Apify vs Tavily head-to-head.

  2. Fundamentals18 min read

    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.

  3. Fundamentals12 min read

    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.

  4. Standalone10 min read

    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.

  5. Deep Dive12 min read

    Notion Component Library Sync Demo

    A live sync demo showing how a strict Notion component grammar maps into Sanity schema blocks and renders with parity on Automation Switch.

  6. Deep Dive9 min read

    SKILL.md Files: The Agent Skills Directory

    SKILL.md files are the configuration layer for AI agent behavior. How they work, how to write them, and the emerging directory of community-built skills.

About this topic

Explore ai workflows.

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. Use the sources and methods attached to each article to assess the evidence, then choose a small, useful next step for your own context.