4 posts tagged with "Deep Dives"

Users would ask Claude to "set up all my integrations," and Claude would call our provisioning tool. Then nothing. Users waited 45 seconds staring at a spinner while our server created API keys, configured webhooks, and set up OAuth clients. Most users gave up after 15 seconds, thinking it failed.

Then someone asked Claude to "clean up old bundles," and Claude dutifully deleted everything from the last 6 months. Because we let it.

We needed streaming for long-running work, chunking for large operations, and approval gates for anything scary. Here's what works.

Our bundle search tool was taking 12 seconds at P95. Users would ask Claude to "find the Slack integration," watch nothing happen, then ask again. Claude would make the same call twice, wait 24 seconds total, and users would close the tab thinking our service was down.

The tool worked perfectly. It just worked slowly. And in the world of AI assistants, slow might as well be broken.

Schemas are the contract the model learns. Great schemas make tools discoverable, hard to misuse, and easy to recover from errors.

I watched Claude hallucinate API endpoints that didn't exist, confidently call made-up functions, and crash our systems with broken JSON. Then we implemented the Model Context Protocol (MCP), and our error rate dropped from 28% to under 3%.

This is what I wish someone had told me when I started.