AUTOMATIONSWITCH

Automation Engineering

Platform engineering, agent infrastructure, and production systems built to scale and govern.

Automation engineering is the discipline of building automation that survives contact with production. This pillar focuses on the infrastructure layer: platform engineering for automation teams, agent governance and compliance, CI/CD for workflow deployments, and the operational patterns that keep automated systems running reliably at scale. Articles here are written for engineering leads and platform teams who need to design systems that are auditable, maintainable, and resilient, with architectural context and governance frameworks drawn from real deployments.

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Dark editorial visual showing the agent-commerce category split into two sides. On the left, an agent labelled BUYER pays through an HTTP 402 response with a USDC payment chip. On the right, an agent labelled SELLER receives a 402 emit and a payment confirmation. A central vertical axis labelled X402 separates the two sides, marking the protocol that closes the autonomous-agent payment gap.
Fundamentals
Two questions every operator faces when agents become buyers and sellers.

What X402 Means for Autonomous Agents: The Payment Layer the Category Was Missing

Until x402, autonomous agents hit a hard ceiling at the moment they needed to pay for something. The model could decide; the agent couldn't transact. x402 closes that gap. The protocol, the implementations, the governance question, and what it means for the autonomous agent category.

May 2026
14 min read
Automation Switch
Case Study
From grep to glance: building a visibility layer for AI-native work
May 2026
7 min
Fundamentals
What Is an Agent Harness? (And How It Differs From an Agent Framework)
May 2026
10 min
Editorial hero card showing CLAUDE.md and AGENTS.md as a layered stack with the @AGENTS.md import line as the bridge between them, with sub-headline indicating the article reframes the comparison as a layering question rather than an alternative choice.
Tool Guide
Two files. One contract. The layering rule decides the rest.
CLAUDE.md vs AGENTS.md: When to Use Each (And Why You Need Both)
CLAUDE.md and AGENTS.md often get treated as alternatives. They are complementary layers. CLAUDE.md is the Claude-specific overlay; AGENTS.md is the cross-platform base. Most repos benefit from both.
May 2026·9 min
Editorial hero card showing memory.md as the agent-written notes file, with sub-headline indicating four mechanically distinct things get called memory across AI tools and the article reframes the taxonomy.
Deep Dive
Four mechanisms. Four trust models. One word.
memory.md and 'Claude Memory': What It Actually Is
memory.md and 'Claude memory' get used loosely. Four mechanically distinct things hide behind the word across Claude Code, Claude.ai, ChatGPT, and Cursor. The taxonomy.
May 2026·15 min
Editorial hero card showing CLAUDE.md as the Claude Code instruction file read at every session, with subtitles indicating four scoping levels and the AGENTS.md import pattern that pulls cross-platform rules into the Claude Code session.
Fundamentals
Edit it. Break it. Re-run.
CLAUDE.md: The Claude Code Instruction File Explained
CLAUDE.md is the Claude Code instruction file. Loaded every session, scoped four ways, importable from AGENTS.md. The standalone explainer of what to put in it, where it lives, and how it stacks with the agent-config family.
May 2026·11 min
Editorial hero card showing AGENTS.md as the universal contract every AI agent reads, with subtitles indicating cross-platform adoption across Claude, Cursor, Copilot, Codex, and Gemini.
Fundamentals
One file. Every agent. Keep it current.
AGENTS.md: The Universal Agent Contract Explained
AGENTS.md is the platform-neutral contract every AI agent in your repo reads. It works across Claude, Cursor, Copilot, Codex, and Gemini. The five-section anatomy and how to write one.
May 2026·10 min