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Build-Time vs. Run-Time: Why Dev Tools Fail in Production — Averi Kitsch & Prerna Kakkar, Google

Source
youtube.com
Author
AI Engineer
Date

Context

A database 's freedom should depend on the job its tools are meant to perform. A conference talk describes the difference between flexible developer tools and production tools built around predefined database queries. Fixing the query's structure limits what the agent can ask the database to do.

The application can also supply values the model should not choose. Toolbox's parameter-binding documentation explains how a bound value is fixed so the model does not request or modify it during . Combining constrained queries with application-supplied parameters puts part of the control in executable software rather than relying entirely on instructions to the agent.

Terms in this piece · Glossary
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
  • MCP — The Model Context Protocol — an open standard that lets any AI assistant plug into any tool or data source without custom integration code.
  • tool use — A model's ability to call external functions — run code, search the web, edit files — instead of only generating text.
Chapters
  • 0:00Introductions, MCP Toolbox and managed MCP
  • 2:56Common tool patterns for databases
  • 4:37Structured SQL tools for production
  • 5:20Build time against run time
  • 6:16When a build time tool deletes the table
  • 8:46Your database is only as secure as your agent
  • 9:13The lethal trifecta and the confused deputy
  • 11:19Separating user, application, and agent identity
  • 12:33Evolving a tool from super user to constrained
  • 14:55Custom tools and prepared statements
  • 15:52Best practices for tool quality
  • 17:39Bound parameters, keeping PII from the agent
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