In a nutshell: Verification loops enable Claude to autonomously perform and iterate on deterministic, project-specific quality checks without manual intervention between development steps.
Anthropic shows how to map review steps in the code development process as automated verification loops in Claude Code. This allows the AI agent to independently review and iteratively correct its work instead of developers having to repeat manual control steps.
The classic agentic loop follows a pattern: request → gather context → take action → review results → iterate if needed. Verification is the step in which the agent checks its work before providing feedback. Claude already uses deterministic signals from the codebase for this: type checkers, linters, tests, and runtime errors. Anything Claude cannot automatically detect remains a manual control task.
In Claude Code, these manual steps can be converted into automated verification loops. Anthropic lists the following built-in options: the /verify skill (compiles, executes, and monitors changes), toolchain integration (Claude responds to error codes and warnings from linters or build tools), code review in research preview mode (automated PR review), GitHub Actions (verifies on every push or PR), spec validation (checks changes against a Markdown specification), and rubrics in Claude Managed Agents (separate grader agents with automatic rework on failures).
To write custom verification loops, developers should first document which control steps they perform repeatedly by hand. This should be recorded in plain English—like an onboarding guide for new team members on day one. If articulating this proves difficult, developers can ask Claude for best practices beforehand and then adapt them to project specifics. Particularly valuable are rules that no generic linter captures, such as “reject migrations without a backfill step”. Anything that must be regularly enforced manually is a candidate for an automated loop.
Source: claude.com · Published 21 July 2026
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