One of the hardest parts of solo development is having no one to review your code.

Code review catches bugs. It improves design. It shares knowledge. When you're alone, you miss all of that.

AI can't replace a senior developer's experienced eye. But it can catch what you missed, challenge your assumptions, and give you someone—something—to think with.

Why Solo Devs Need Review

Without review, problems accumulate:

Blind spots persist. You have habits. Some are bad. No one tells you.

Bugs slip through. Fresh eyes catch things tired eyes miss. You only have tired eyes.

Design debt grows. Without pushback, expedient choices become permanent architecture.

Learning slows. Review teaches. Teaching yourself is harder.

AI review isn't perfect, but it's better than nothing.

What AI Review Can Catch

AI is genuinely good at:

Obvious bugs. Null checks, off-by-one errors, missing error handling. The mechanical stuff.

Style inconsistencies. Naming conventions, formatting, code organization.

Common patterns. "This could be simplified using X" or "Consider handling the edge case where Y."

Security issues. Common vulnerabilities like SQL injection, XSS, exposed secrets.

Documentation gaps. Missing comments, unclear function signatures, undocumented assumptions.

These are real catches. They're the things a reviewer would flag before getting to deeper issues.

What AI Review Misses

AI struggles with:

Business context. Is this the right feature? Does it match requirements? AI doesn't know what you're building.

Architecture fit. Does this code fit the larger system design? AI sees the tree, not the forest.

Team conventions. Beyond style guides, teams have unwritten rules. AI doesn't know yours.

Performance nuance. It might flag a loop as inefficient when it runs once on startup. Context matters.

Use AI for mechanical review. Keep your brain engaged for the rest.

The Manual Review Prompt

When you want focused review, ask specifically:

Review this code for:
1. Potential bugs or edge cases
2. Security vulnerabilities
3. Performance issues
4. Readability improvements

Context: This is [what the code does] in a [type of application].

[paste code]

Specific asks get specific answers. "Review this code" gets generic responses.

Review Triggers

When to request AI review:

Before committing. Quick sanity check. Any obvious issues?

After completing a feature. Holistic review. Does the implementation make sense?

When you're unsure. The code works but feels wrong. Get another perspective.

Before shipping. Final check for security issues and bugs.

Don't review everything—that's overhead. Review when it matters.

The Self-Review Ritual

Combine AI review with self-review:

  1. Write the code. Get it working.

  2. Step away. Even briefly. Fresh eyes help.

  3. Read your own diff. What would you flag if someone else wrote this?

  4. Ask AI. Share specific concerns plus general review.

  5. Implement feedback. Don't just read—act on valid points.

  6. Commit. With confidence.

This ritual catches more than either AI or self-review alone.

Avoiding Review Theater

Don't let AI review become checkbox exercise:

Read the feedback. Don't just run it to say you did.

Evaluate critically. AI suggestions aren't always right. It can be confidently wrong.

Dismiss with reason. If you disagree, know why. "I considered this and decided against it because X."

Act on good feedback. The point is improvement, not process.

Review that doesn't change anything is wasted time.

Building Review into Workflow

Make it automatic:

Pre-commit hooks. Run basic checks before every commit.

PR templates. Include AI review as a checklist item.

Weekly deep review. Set aside time for thorough review of recent work.

Before releases. Comprehensive review of everything shipping.

Habits beat intentions. Build review into your process.

The Feedback Loop

AI review teaches over time:

Track recurring issues. If AI keeps flagging the same thing, you have a habit to fix.

Notice patterns. What do you consistently miss? Focus learning there.

Improve prompts. As you learn what matters, ask for it specifically.

The goal isn't permanent dependence on AI review. It's getting better so you catch issues yourself.

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