Tagged: LLM
7 posts · browse all tags
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AI Part 9: From Draft-Only to Whole-Site — the v2.4 Tool Surface and the Rails Behind It
Parts 7 and 8 went out to other people's tool servers. This one comes home. v2.4 turns my blog's MCP server from a draft-publishing surface into one that can read, grep, write, and illustrate the whole site — and the interesting part was never the tools. It was the guardrails.
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AI Part 1: Why I Gave Claude Write Access to My Site
A year ago I would have called this irresponsible. Today an MCP server lets Claude write to my site. The trust model isn't "I trust the model" — it's "I trust the blast radius".
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AI Part 2: The Minimum Viable MCP Server
A personal MCP server is a tiny HTTP service. The spec accommodates a lot of complexity that, if you're the only user, you can stop building. Here's the inventory of what I have running, and what I deliberately left out.
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AI Part 3: Designing Tools for an LLM, Not for Yourself
The verb in the tool name is the most important part. Descriptions answer the questions a chooser asks, not the questions a maintainer asks. Allowlists fail closed; blocklists fail open. Error messages are also instructions.
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AI Part 4: Safety Rails — Allowlists, Atomic Writes, Audit Logs, Rollback
About two hundred lines of code, none of them clever, all of them the reason I sleep fine with the service running. Allowlists, atomic writes, an audit log, and a manual rollback path.
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AI Part 5: Prompt-Driven Authoring in Practice
What's it actually like to use? The honest answer, including where the loop is tight, where it's still clumsy, and the three things I'd warn anyone trying this.
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AI Part 6: Connector Quirks, Cache Traps, and What I'd Do Differently
Six months in. The cache layer you don't see, OAuth refresh edge cases, and the short list of decisions I'd make differently if I were doing this again from scratch.