AI.
9 posts filed under AI.
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An Agentic Engineering Factory Inside GitHub
GitHub already has the governance layer coding agents need. I use it to route agent work from a human-triaged issue through review and back to a human merge decision.
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CRAFTS: The Agentic Coding Loop I Trust
I wanted agents I could leave alone and still trust. CRAFTS is the coding loop I built to make autonomous output more reliable, more secure, and less forgetful.
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Why I Put a Knowledge Base Inside My Codebase
Spec files get stale. Agents work from outdated assumptions. Here's how an in-codebase knowledge base fixes that - and how the agents maintain it themselves.
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TODO(HUMAN): The Case for Deliberate Presence in Agentic Development
Full agentic autonomy is fast, but speed compounds in both directions. TODO(HUMAN) is the checkpoint system I use to stay present, sharp, and accountable in AI-assisted software development.
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The n8n Rebuild Report: Real Numbers, Real Trade-offs, No Clean Ending.
I predicted $44-70/month. It came in at $90. Here's the honest breakdown - cost, stability, creative quality, and the trade-offs that don't clean up nicely.
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I Spent $330 on an OpenClaw Content Agent. Here's What I Got.
I built a 4-agent LinkedIn content pod on OpenClaw for an honest technical evaluation. Here's what worked, what broke, and why the cost math doesn't add up.
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Why I Scrapped My OpenClaw Content Pod and Rebuilt It in n8n
A spreadsheet audit of my Anthropic API costs revealed the real problem with agent-native automation. Here's what I rebuilt and the rule for evaluating AI agents.
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Building a Development Documentation MCP Server at Vimeo
I built an MCP server that provides AI coding assistants with development documentation for Vimeo's custom codebase patterns, conventions, and libraries resulting in roughly 75% better output.
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One User, One Banana: What My Failed AI Startup Taught Me About Validation
I spent 5 months building an AI startup, got 50 signups, and watched my only active user upload a banana. Here's what it taught me about enthusiasm vs. actual demand.