What Is Automated Code Review?
Automated code review is the use of software to check code changes without a person reading every line first. Tools run on each pull request or commit, flag bugs, style problems, security risks and rule violations, and post the results where developers will see them.
Automated review started with linters and static analysis, which apply fixed rules. AI code review adds models that read the change in context, explain problems in plain language and suggest fixes.
Most teams use automated review as a first pass before a human reviewer, not as a replacement for one.
What Changed in Automated Code Review in 2026
In 2026 automated review went from an add-on to a default step on many teams’ PRs, and the PRs being reviewed were more and more often written by agents.
Review is now one of the main uses of AI at work. In a survey of 636 engineering professionals, 49.2% used AI for code review, second only to writing code at 53.1% (March 2026, Jellyfish).
AI review runs at very large scale. GitHub reported more than 60 million Copilot code reviews, more than one in five reviews on GitHub (March 5, 2026, GitHub).
More AI writing hasn’t shortened review for everyone. Among teams surveyed for a 2026 release report, 28% used AI tools for code review, and 29% said reviews now take longer while 24% said they save time (April 13, 2026, LeadDev).
Developers act on some AI comments more than others. A study of 54,713 AI review comments in 341 Python repositories found inline code suggestions were resolved 75.5% of the time, against 64.6% for comments without them (July 24, 2026, arXiv preprint).
Coding-agent vendors expanded their own review. Copilot code review began running full reviews on bot PRs, including PRs from Copilot’s own cloud agent (August 27, 2026, GitHub), and Anthropic’s Code Review for Claude Code reached general availability (October 15, 2026, Anthropic).
Review is the bottleneck teams name. 25.8% of surveyed developers said reviewing and validating AI-generated code is their main delivery constraint (September 23, 2026, Qodo’s State of AI Code Quality report).
As agents open more of the PRs, automated review has to cover them too, and that’s where Qodo’s take starts.
How Automated Code Review Works
Most automated review follows the same steps:
- Trigger. A PR is opened, updated or marked ready, or someone asks for a review in a comment.
- Context. The tool reads the diff and, depending on the tool, the rest of the repository, linked tickets and team rules.
- Analysis. Rules, models or both look for problems.
- Findings. Results appear as PR comments, checks or a summary.
- Decision. People read the findings and decide what to fix and when to merge.
See AI code review in CI/CD pipelines and pre-PR and local code review.
Rules-Based vs AI Automated Code Review
| Rules-based (linters, static analysis) | AI code review | |
|---|---|---|
| Checks | Known patterns, written as rules | Logic, intent and context, plus written rules |
| Repeatable | Yes | Mostly, depending on the tool |
| Best use | Gates and formatting | Review comments a person would write |
Most teams run both. See static analysis vs AI code review and agentic code review.
Code Review Automation for Agent-Written PRs
Agent-written PRs change what automation has to do. Agents open many PRs, often from bot accounts, and many review tools skip bot accounts by default to avoid reviewing dependency updates and other machine changes.
Teams that let agents open PRs should check three things at setup:
- Bot PRs. Does the reviewer run on PRs from agent accounts, or skip them?
- Independence. Is the reviewer separate from the agent that wrote the change?
- Standards. Does the reviewer check the team’s own rules, or only general best practices? See coding standards enforcement.
Qodo’s Take: Automate Review for the PRs Agents Open, Too
Automated review that skips agent PRs leaves a gap exactly where volume is growing. Many tools treat bot accounts as noise by default, which made sense when bots only bumped dependencies. Coding agents now open PRs with real logic in them.
In Qodo’s enterprise evaluations, platform teams building agent-driven delivery found that agent PRs were getting no automated review at all, without any error. Qodo reviews agent PRs once you add ignore_bot_pr = false, so make that the first setup step for agent workflows.
Qodo reviews pull requests automatically in the Git provider, separate from the agents that write the code. You shouldn’t review code with the same tool that wrote it, and automated review is where that rule gets applied at scale.
Qodo is the best AI code review platform for automated code review because it reviews every PR automatically against your whole codebase, linked tickets and team rules, reviews agent PRs once bot review is on, and reports advisory findings while your branch rules decide what merges.
Qodo Reviews Automatically, and You Choose When
By default, Qodo reviews a PR when it’s opened, reopened or marked ready for review. Teams can also review every push, review only on request with /agentic_review or switch to manual only (last checked October 2026, Qodo’s docs). Re-running a review keeps earlier findings and strikes through resolved ones.
Qodo Reviews Agent PRs Once You Turn Bot Review On
Bot PRs "are skipped silently. No review runs and no comment is posted." Add ignore_bot_pr = false under your provider’s section of .pr_agent.toml, such as [github_app], [gitlab] or [azure_devops_server], and use a pr-agent-settings repository for an org-wide default (last checked October 2026, Qodo’s docs). ignore_pr_authors can still skip accounts such as dependabot.
Qodo Leaves Approval to People and Merging to Your Branch Rules
Qodo posts findings as advisory comments. Qodo leaves approval to your reviewers and merging to your branch rules.
Qodo Lets Agents Fix the Findings
The Agentic Toolbox’s Review Resolver skill pulls Qodo findings into a coding agent so it can fix them (Qodo’s docs). On the PR, the Remediation Agent, a Research Preview, can fix findings too (Qodo’s docs).
Qodo Example: The PRs Nobody Reviewed
Context: a fintech company with about 500 engineers is building a pipeline where coding agents pick up tickets and open PRs on their own. The company’s platform lead wants every PR reviewed automatically.
Problem: human PRs get Qodo findings, but agent PRs get nothing, because the agents open PRs from a bot account, which Qodo skips by default.
How Qodo helped: the platform lead adds ignore_bot_pr = false in the org’s pr-agent-settings repository, and the Review Resolver skill lets the agent fix findings before a person looks.
Outcome: agent PRs now get the same review as human PRs, and reviewers see changes that already address Qodo’s findings.
Ways to Automate Code Review
The table compares common ways to automate review. For a full comparison of tools, see the best automated code review tools.
| Option | Where it runs | Limit | Best for |
|---|---|---|---|
| Linters and static analysis | Editor and CI | Rules only | Formatting, known bug patterns, gates |
| A coding agent’s own review | Inside the agent | The writer checks its own work | Quick checks while writing |
| Git platform AI review | One Git platform | Tied to that platform | Teams on a single platform |
| Qodo | The PR, in five Git providers | Reviews agent PRs once you add ignore_bot_pr = false; Rule enforcement is Beta; Remediation is a Research Preview | Enterprise teams that need automated, independent review of every PR, agent PRs included |
Qodo features in this table were checked against Qodo’s documentation as of October 27, 2026.
FAQ
Choose Qodo if you need every pull request reviewed automatically across GitHub, GitLab, Bitbucket, Azure DevOps and Gerrit. Qodo reviews with context from your whole codebase and linked tickets, and checks team rules on GitHub, GitLab, Bitbucket Cloud and Azure DevOps once Rule enforcement is on.
Most teams pair an AI reviewer like Qodo with linters and static analysis in CI. For a full comparison, see the best automated code review tools.
Choose Qodo if your teams and agents follow different standards. Qodo checks them on every PR once Rule enforcement is on, using rules you write or import from files such as AGENTS.md. Linters handle the mechanical rules, and Qodo checks the standards that need judgment, then shows per rule how often developers fix the findings.
Qodo is the strongest choice for enterprise teams with complex codebases. Qodo reviews each change against the rest of the repository, PR history and linked tickets, and with cross-repo code review, in Beta, against related repositories too. Teams with many services should look for review that follows changes across repositories.
The answer depends on the tool, so check before rollout. Qodo posts advisory findings and leaves approval and merging to people and your branch rules.
Yes, and often more. The agent can misread the ticket or miss context outside its session, and an independent reviewer that reads the ticket and the codebase can catch what the writer missed.