---
format: "aidr-story-markdown/v1"
id: "0f074711e20496b5e05a5337b546f482632aecb5f16cd73dc94f6760881b3fef"
canonical_url: "https://aidr.today/0f074711?lang=en"
title: "The Anatomy of Harness Engineering: How to Evaluate, Iterate, and Guard AI Coding Agents"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-09-15T19:46:17.000Z"
category: "Research"
topics: []
source_urls: ["https://developers.googleblog.com/the-anatomy-of-harness-engineering-how-to-evaluate-iterate-and-guard-ai-coding-agents/","https://developers.googleblog.com/how-to-evaluate-live-voice-agents-in-adk/"]
summary: "While end-to-end benchmarks like SWE-bench provide broad performance scores for AI agents, they are often expensive, slow, and lack the root-cause diagnostics needed to explain exactly where an agent's logic broke down. To solve this, developers should adopt behavioral evaluations—fast, local, unit-style tests that assert on discrete intermediate actions, such as verifying specific tool calls or file modifications rather than final string equality. By building these inexpensive micro-checks alongside macro benchmarks, engineering teams can confidently iterate on system prompts and upgrade models without the risk of regressions."
---

# The Anatomy of Harness Engineering: How to Evaluate, Iterate, and Guard AI Coding Agents

> [Open the canonical story](<https://aidr.today/0f074711?lang=en>)

**Published:** 2026-09-15T19:46:17.000Z
**Category:** Research

## Summary

While end\-to\-end benchmarks like SWE\-bench provide broad performance scores for AI agents, they are often expensive, slow, and lack the root\-cause diagnostics needed to explain exactly where an agent's logic broke down\. To solve this, developers should adopt behavioral evaluations—fast, local, unit\-style tests that assert on discrete intermediate actions, such as verifying specific tool calls or file modifications rather than final string equality\. By building these inexpensive micro\-checks alongside macro benchmarks, engineering teams can confidently iterate on system prompts and upgrade models without the risk of regressions\.

## Sources

- [Story source](<https://developers.googleblog.com/the-anatomy-of-harness-engineering-how-to-evaluate-iterate-and-guard-ai-coding-agents/>)
- [Story source](<https://developers.googleblog.com/how-to-evaluate-live-voice-agents-in-adk/>)