Harness Engineering: How to Evaluate, Iterate, and Guard AI Coding Agents

While macro benchmarks like SWE-bench evaluate overall task completion, they are often too slow and coarse-grained to isolate where an agent's reasoning fails. Google's developer team outlines a harness engineering methodology centered on behavioral evaluations: fast, unit-style checks that assert on intermediate tool calls and file modifications rather than final string matching. Combining these micro-checks with macro benchmarks enables teams to systematically catch regressions when refining system prompts or swapping foundation models.