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Agent Engineering Notes

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OpenClaw vs Claude Code: Which Agent Layer Are You Actually Choosing?

One is a persistent, self-hosted runtime across channels. One is an agentic coding tool with deep repo execution. They overlap less than people think, and that is exactly why this comparison matters.

OpenClaw vs Hermes Agent: Ecosystem Reach or Learning Depth

Two open, self-hosted agent runtimes. Same problem class, different center of gravity — and the choice is mostly about what you want the system to compound on over time.

The Three Memory Layers Every Agent Team Needs (And the Specific Failure You Get Without Each)

Most agent failures are memory architecture failures wearing a prompt-quality mask.

3 Things You Might be Building When You Think You’re Building an Agent (and which one you actually want)

Every option looks like a loop with tools until you define what has to be true for the run to have succeeded.

10 Prompting Mistakes That Only Show Up in Multi-Agent Systems — And How to Fix Each One

Every vague word in your system prompt is a decision your agent makes without you.

What OpenClaw Gets Right That Most Agent Setups Get Wrong

Five design decisions that look obvious in hindsight.

Build the Content Company from Scratch with Paperclip AI

Roles, config, delegation chain — and the three things I got wrong before it worked.

Paperclip Lets You Build an AI Company, Not Just an AI Workflow

Here's the difference — and five real patterns worth stealing

Welcome to Agent Engineering Notes — here's what you're in for

The newsletter about AI agents I kept writing by accident — now on purpose.

7 Things That Break When AI Agents Try to Work Together

Everyone is excited about AI agents. Very few have actually tried running a team of them. Here is what happens when you do.