Code reviews have always been a critical part of professional software development. In mature teams, they are not just about catching bugs. They are about knowledge sharing, enforcing standards, improving design quality, and reducing long-term maintenance cost.

With the rise of AI-generated code, the nature of code reviews is changing significantly. Reviewers are no longer only evaluating code written by humans. They are now reviewing code written with AI or sometimes entirely by AI. This shift affects how reviews are conducted, what reviewers should focus on, and what skills matter most.

This article explains how AI-generated code is changing code reviews, with a strong focus on Angular and frontend enterprise applications. It is written for senior developers, tech leads, and architects who are responsible for maintaining quality in large codebases.

No hype. No fear-mongering. Only practical realities and best practices.

1. Traditional Code Reviews: What They Were Optimised For

Before understanding what has changed, it is important to understand what code reviews were originally designed for.

Core Goals of Traditional Code Reviews

In most Angular teams, code reviews traditionally focused on:

Reviewers assumed:

This assumption no longer always holds true with AI-generated code.

2. What AI-Generated Code Actually Looks Like

AI-generated code is not bad by default. In fact, it is often:

But it has unique characteristics that affect reviews.

Common Traits of AI-Generated Angular Code

  1. Over-verbosity
    Code tends to be longer than necessary.

  2. Generic Patterns
    Uses common examples rather than project-specific conventions.

  3. Over-engineering
    Introduces abstractions that are not needed.

  4. Superficial Correctness
    Works for the happy path but ignores edge cases.

  5. Weak Context Awareness
    Misses business rules, domain nuances, and historical decisions.

A senior reviewer must recognise these patterns quickly.

3. The Biggest Shift: Reviews Are Now About Intent, Not Just Code

With AI-generated code, the most important question in a review is no longer:

“Does this code work?”

It is now:

“Why does this code exist in this form?”

Example: Angular Service Layer

AI might generate a service like this:

@Injectable({
  providedIn: 'root'
})
export class UserService {
  constructor(private http: HttpClient) {}

  getUsers(): Observable<User[]> {
    return this.http.get<User[]>('/api/users');
  }
}

This code is correct. But reviewers must ask:

AI does not ask these questions. Reviewers must.

4. Code Reviews Are Becoming Architecture Reviews

AI can generate code faster than humans, but it does not understand:

Impact on Angular Applications

In large Angular applications:

AI-generated code may violate these silently.

Example: Accidental Architecture Drift

AI might:

Each change looks small. Over time, architecture erodes.

Reviewer Responsibility

Code reviews must now:

5. Increased Volume, Reduced Signal

AI increases development speed. This leads to:

The Review Problem

Reviewers face:

AI-generated code often looks “clean”, which creates a false sense of safety.

Best Practice

Speed must not compromise understanding.

6. Reviewing Code the Author May Not Fully Understand

This is one of the biggest cultural changes.

In the past:

With AI:

New Rule for Reviews

If the author cannot explain:

Then the code should not be merged.

AI assistance does not remove accountability.

7. AI and Boilerplate: What Reviews Can Safely Ignore

Not everything requires deep scrutiny.

Low-Risk Areas

AI-generated code is usually safe for:

High-Risk Areas

Review carefully:

Senior reviewers must prioritise attention.

8. AI-Generated RxJS Code: A Major Review Hotspot

RxJS is an area where AI often struggles.

Common Problems

AI-generated RxJS code often:

Example Problem

this.userService.getUsers().subscribe(users => {
  this.users = users;
});

AI may omit:

Review Checklist for RxJS

RxJS mistakes can cause serious production issues.

9. Testing Code Reviews Are Changing Too

AI can generate tests quickly, but test quality varies.

Common AI-Generated Test Issues

Angular Testing Example

AI may generate:

it('should create', () => {
  expect(component).toBeTruthy();
});

This adds almost no value.

New Review Focus

Reviewers must ask:

Test quantity is meaningless without intent.

10. Code Reviews Are Becoming More About Deletion

One surprising effect of AI is code bloat.

AI tends to:

Senior Reviewers Must Be Comfortable Saying:

Removing AI-generated excess is now part of the job.

11. Security Reviews Matter More Than Ever

AI-generated code can introduce subtle security issues.

Angular-Specific Risks

AI may produce code that works but violates security policies.

Reviewer Responsibility

Security cannot be delegated to AI.

12. Changing Reviewer Skill Sets

The skills needed for good reviews are shifting.

Less Important Than Before

More Important Than Ever

AI raises the bar for reviewers.

13. How Angular Teams Should Adapt Their Review Process

Practical Changes

  1. Update review guidelines to mention AI usage

  2. Require authors to disclose AI-generated code

  3. Emphasise intent and design explanation

  4. Strengthen architectural checks

  5. Encourage deletion and simplification

Tooling Adjustments

Automation should catch basics so humans focus on thinking.

14. Cultural Changes in Teams

AI changes team dynamics.

Healthy Practices

Dangerous Practices

Culture matters more than tools.

15. The Future of Code Reviews in an AI World

Code reviews will not disappear. They will evolve.

What Will Increase

What Will Decrease

Reviews will become more valuable, not less.

Conclusion

AI-generated code is fundamentally changing code reviews. Not by making them obsolete, but by shifting their focus.

For Angular teams, the role of code reviews is now:

Senior developers and reviewers are now the last line of defence against architectural erosion, hidden complexity, and silent risk.

AI writes code faster than humans.
Humans must ensure that code deserves to exist.