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Agents Are Where Microservices Were in 2015 — Roberto Milev & Uday Kanagala, Navan

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youtube.com
Author
AI Engineer
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Context

A travel that buys a ticket days after receiving an instruction raises a specific authorization problem: whose permission applies when the purchase actually happens? Travel-and-expense company Navan uses this example in its conference talk to explain why its checks surround individual tool calls. The system examines actions before and after execution, where the consequences become concrete.

The same reasoning changes testing. Navan describes evaluating the sequence of steps an agent takes, rather than judging only its final answer. A plausible confirmation message is insufficient evidence that the agent followed an acceptable process to reach it.

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.
  • guardrails — The checks around a model that block bad inputs and outputs — filters, validators, and permission rules the model itself can't override.
  • context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
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