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Second opinion

Why your code needs a second opinion

Whoever wrote the code, you or an AI agent, is the worst-placed to review it. They know what it's supposed to do, so they read what they meant, not what's there. A second opinion with fresh eyes, a fixed checklist and evidence from the code catches what tests and the author miss.

Last reviewed by the Forge team

What goes wrong

What it costs when this is missed

High

Blind spots

Authors test the paths they thought of. The bugs live in the paths they didn't.

High

Code nobody read

Solo projects and agent-written code often ship with no review at all: the first reader is a user.

Medium

AI reviewing itself

Asking the model that wrote the code to review it tends to repeat its own assumptions.

Medium

Green tests, false confidence

Tests prove what they check. They say nothing about the checks nobody wrote.

Common problems

What to look for in your code

Each one: why it hurts, and how to spot it in your own project.

01Reviewing your own work

You read your intent, not your code. That's why typos survive proofreading and why the missing permission check looks fine to its author.

How to spot it: If the person or model that wrote a change is also its only reviewer, it hasn't really been reviewed.

02Only ever reviewing diffs

Pull request reviews see one change at a time. Problems no single diff introduced (a cycle, a rule copied five times, a route that never had an auth check) are invisible to them.

How to spot it: When did someone last review the whole codebase, rather than the latest change?

03Reviews without a checklist

Without a list, reviewers check whatever comes to mind. A fixed list per area (security, SEO, structure) makes coverage repeatable.

How to spot it: Can you say which topics your last review covered, and which it didn't?

04Findings without evidence

'This might be insecure' wastes everyone's time. A useful finding names the file and line, quotes the code and says what goes wrong.

How to spot it: Check whether review comments point at real code, and whether anyone confirmed the code says what the comment claims.

05Everything marked urgent

A list of 80 issues with equal weight gets ignored. Reviews need to say what to fix now, what next, and what to just watch.

How to spot it: Does your last review's output tell you the first three things to do?

06Audits that go stale

An audit from six months ago describes a different codebase. Without re-checks, you don't know what's fixed, what's new, and what got worse.

How to spot it: Can you tell which past findings are fixed today?

Quick self-check

How does your project do?

Tick each one that's true today. Anything left unticked is worth a closer look.

Tick what's true for your project. 7 checks.

How Forge checks this

A second opinion on your code, from the Issues, SEO and Structure scans.

  • Reviews your repository on your computer, with a written brief per scan that lists the topics it must cover.
  • Every finding must quote the code. Forge checks each quote exists at that file and line, and drops or demotes what it can't confirm.
  • Findings go into lanes (Now, Next, Watch), so the first moves are obvious.
  • Re-audits look only at what changed, and say what's fixed, new, worse or better.
  • Read-only: Forge never edits your code.

Questions

Isn't a pull request review enough?

PR reviews are essential, but they see one change at a time and depend on the reviewer's time that day. A periodic whole-codebase review catches what builds up between pull requests.

Can an AI give a real second opinion?

Yes, if it's held to evidence. A review that must quote the code, and gets checked against it, is far more useful than one that just has opinions. Use a different setup from the one that wrote the code.

How often should I get one?

Before launch, before big releases, and after a burst of fast changes such as an AI-assisted sprint. Incremental re-checks keep it cheap in between.

Related guides

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