Table of Contents
TL;DR
Code reviews should teach, not just catch bugs. Stop nitpicking syntax and start building autonomous developers. Focus on architectural patterns, ask guiding questions instead of giving orders, and eliminate multi-team approval bottlenecks that delay delivery.
Good reviews create learning opportunities that scale your team’s expertise.
Code reviews shouldn’t be about catching syntax errors or enforcing personal preferences. They’re your best tool for spreading architectural knowledge and building stronger development teams. But most teams get this wrong, creating bureaucratic bottlenecks instead of learning opportunities.
The Broken Review Process I Lived Through
In a previous role leading a product modernization effort at a mid-sized fintech, our team had to get every PR approved by two separate teams , the repo owner team and our sister team. Even for low-risk internal changes, we needed both approvals. The review process became a 14-16 day nightmare.
A simple bug fix in our Angular user service would sit for a week waiting for the repo owners, then another week for the sister team to weigh in. Meanwhile, I’m getting heat from product managers asking why my feature estimates keep slipping. The code was done in 2 days, but delivery took 3 weeks.
“If the code’s ready, why haven’t we shipped?” one frustrated PM asked. I had no good answer , except bureaucracy.
Developers were demotivated, knowing their high-quality work would sit idle for weeks. Some started gaming the system , pushing smaller, isolated PRs just to bypass review friction.
I started adding explicit review time buffers to my feature estimates , essentially padding every story with 2 weeks of “review overhead.” Product wasn’t happy, but it set realistic expectations about our actual delivery capacity.
This was a textbook case of the Two-Gate Anti-Pattern , where dual-team reviews paralyze progress while pretending to ensure quality.
We’ve proposed moving toward domain-based ownership , where only one team has final approval rights and others can comment , but it’s still under discussion. Until then, we continue to absorb 10+ days of delay due to the dual-review requirement.
The lesson still stands: Code review should not be a permission slip. It should be a feedback loop.
What Not to Say in Reviews
Skip the nitpicking. Comments like “use var instead of string” or “add a space here” waste everyone’s time. Your IDE and linting tools handle formatting. Focus on substance.
Avoid vague feedback: “This doesn’t look right” tells the developer nothing. Instead, explain the specific issue: “This N+1 query will hit the database 50+ times for a typical user list. Consider using Include() for the related entities.”
Don’t make it personal. Replace “You forgot to handle nulls” with “This method needs null checking for the user parameter.” The code has the issue, not the person.
Don’t default to “more tests” as your only comment. For example, asking “Why didn’t you unit test sorting for every column?” when the code path is identical is not helpful. A loop that verifies sorting behavior across all columns isn’t always necessary if the implementation is generic and test coverage on one path proves correctness.
Ask why additional coverage adds value:
“Is there any column with custom logic or sort direction? If not, is testing a representative column enough?”
This builds trust in testing strategy and avoids cargo-cult testing just to “check the box.”
Using Reviews to Teach Architectural Thinking
Good reviews connect individual changes to broader system design. When you see a developer adding direct database calls to a controller, don’t just say “move this to a service.” Explain why:
// Instead of just flagging this
public class UsersController : ControllerBase
{
public async Task<IActionResult> GetUser(int id)
{
var user = await _context.Users.FindAsync(id);
return Ok(user);
}
}
Frame your feedback around architectural principles: “This violates separation of concerns and makes the controller hard to test. Consider injecting a IUserService that handles the data access logic. This keeps controllers thin and business logic reusable.”
Point out patterns that scale poorly. When reviewing Angular components, highlight tight coupling:
// Flag this pattern early
export class UserListComponent {
constructor(private http: HttpClient) {}
loadUsers() {
return this.http.get('/api/users'); // Tight coupling to HTTP implementation
}
}
Suggest: “Consider injecting a UserService instead of HttpClient directly. This makes the component testable and lets us swap data sources without changing UI logic.”
Building Autonomous Developers
Autonomy doesn’t come from telling people what to do , it comes from enabling them to think independently with just enough guidance.
Let’s say you’re reviewing an Angular pull request that implements a data table component. Instead of saying:
“You forgot to debounce the search input.”
Say:
“Looks good overall , quick question: what happens if the user types quickly in the search box? Should we consider debouncing the input stream to avoid flooding the API?”
This approach encourages the dev to investigate and learn RxJS patterns (like debounceTime), avoids making them feel like they “missed” something obvious, and builds long-term thinking: “Next time I’ll check for that on my own.”
Another example , someone uses any in a component input:
Instead of:
“Don’t use any , use a proper interface.”
Say:
“Would it help long-term readability if we extract a model or DTO here? What edge cases might we miss with any?”
This nudges them toward understanding type safety, reusability of interfaces, and cleaner contracts between components.
Final example , API call directly inside an ngOnInit:
Bad review:
“Move the API call to a service.”
Better:
“Curious: is this call reusable? If other components need it later, maybe it belongs in a service. Also, should we consider canceling the request on component destroy?”
You’re not just correcting code , you’re teaching system design and Angular idioms.
Avoiding Gatekeeper Behavior
Clear ownership prevents the review bottleneck I experienced. Assign domain experts as primary reviewers, but allow anyone to comment. The domain owner makes the final call.
Set review timeframes. Primary reviewers respond within 24 hours. Secondary comments don’t block merging unless they raise critical issues.
Use automated checks for routine standards. Let ESLint catch Angular formatting issues. Use SonarQube for C# code quality metrics. Reserve human reviews for architectural decisions and business logic.
When planning features, factor in review time realistically. If your process typically takes 2 weeks for approvals, include that in estimates. It forces conversations about whether the review overhead is worth it.
Performance-Focused Reviews
Reviews should catch performance issues before they reach production. Look for common anti-patterns:
- Entity Framework queries without projections
- Angular components that don’t use OnPush change detection
- SQL Server queries missing indexes on filtered columns
When you spot these, provide specific metrics: “This query took 2.3 seconds against our staging database with 50k records. Adding an index on CreatedDate dropped it to 45ms.”
Making Reviews Scale
Senior developers can’t review everything. Train mid-level developers to handle routine reviews, reserving architect-level review for complex changes affecting multiple systems.
Create review checklists for common scenarios. A deployment checklist might include: database migrations tested, feature flags configured, monitoring alerts updated.
Use draft PRs for architectural discussions. Developers can share design approaches early, get feedback on direction, then implement with confidence.
Code reviews done right create a learning culture where knowledge spreads naturally. Developers gain confidence making architectural decisions, code quality improves systematically, and your team becomes more autonomous. The investment in thoughtful reviews pays dividends in reduced technical debt and faster feature delivery.