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The Hidden BottleneckWhy Reviews Take So LongProblem 1: PRs Are Too LargeProblem 2: No Clear OwnershipProblem 3: Reviewers Don't Know What to Look ForThe System That WorksRule 1: 4-Hour SLARule 2: Small PRs OnlyRule 3: PR Descriptions Are MandatoryWhat this PR doesWhyHow to testScreenshots (if UI change)RisksRule 4: Automate the Boring StuffRule 5: Two Types of CommentsMeasuring Review HealthThe Cultural ShiftWhat Good Review Culture Looks LikeWhat Bad Review Culture Looks LikeStart This Week
  1. Insights
  2. Engineering
  3. Code Review Is a Bottleneck — Here's How to Fix It

Code Review Is a Bottleneck — Here's How to Fix It

January 19, 2026·ScaledByDesign·
code-reviewengineeringproductivityprocess

The Hidden Bottleneck

Your engineers write code for 2 hours. Then the PR sits for 2 days waiting for review. Multiply by every engineer, every PR, every week — and code review is quietly killing your velocity.

Most teams don't measure this. They should.

The math on a typical team of 8:
  PRs opened per day: ~12
  Average time to first review: 18 hours
  Average review cycles: 2.3
  Average time from PR open to merge: 3.2 days

  That's 3.2 days of context-switching, waiting,
  and rebasing — for every single change.

Why Reviews Take So Long

Problem 1: PRs Are Too Large

PR size vs review quality (industry data):

  < 200 lines:   Review takes 15 min, catches 85% of issues
  200-500 lines:  Review takes 45 min, catches 60% of issues
  500-1000 lines: Review takes 90 min, catches 40% of issues
  > 1000 lines:   Reviewer gives up, approves with "LGTM"

The biggest PRs get the worst reviews.

The fix: Maximum 400 lines per PR. No exceptions. If the feature is larger, break it into stacked PRs with clear boundaries.

Problem 2: No Clear Ownership

Bad: PR assigned to "the team" (everyone's problem = nobody's problem)

Good: Explicit review assignment with rotation
  Monday:    Sarah reviews Alex's PRs, Alex reviews Mike's
  Tuesday:   Mike reviews Sarah's PRs, Sarah reviews Jordan's
  Wednesday: Jordan reviews Mike's PRs, Mike reviews Alex's
  ...

Problem 3: Reviewers Don't Know What to Look For

A good code review checks (in priority order):

1. Correctness: Does it do what it's supposed to?
2. Edge cases: What happens with empty input, nulls, failures?
3. Security: Any auth bypasses, injection risks, data leaks?
4. Performance: Any O(n²) loops, missing indexes, N+1 queries?
5. Maintainability: Will someone understand this in 6 months?

A bad code review checks:
  ✗ Naming conventions (use a linter)
  ✗ Formatting (use a formatter)
  ✗ Import order (use a tool)
  ✗ Whether the reviewer would have done it differently

The System That Works

Rule 1: 4-Hour SLA

Every PR gets a first review within 4 business hours. Not a full review — a first pass.

How to enforce:
  - Bot posts in Slack when a PR has no reviewer after 2 hours
  - Daily standup includes "any PRs blocked on review?"
  - Track time-to-first-review as a team metric
  - Manager reviews the metric weekly

Rule 2: Small PRs Only

PR size guidelines:
  Feature work: Max 400 lines changed
  Refactoring: Max 600 lines (moves are cheap to review)
  Config/generated: No limit (but flag as "generated, no review needed")

How to break up large features:
  1. Data model changes (migration + model, no UI)
  2. Backend logic (service layer, tested independently)
  3. API endpoint (thin layer, calls service)
  4. Frontend (UI consuming the API)
  5. Integration tests (end-to-end verification)

Rule 3: PR Descriptions Are Mandatory

## What this PR does
[1-2 sentences explaining the change]
 
## Why
[Link to ticket/RFC, or brief explanation]
 
## How to test
[Steps to verify this works]
 
## Screenshots (if UI change)
[Before/after screenshots]
 
## Risks
[What could go wrong? What should reviewers pay attention to?]

Rule 4: Automate the Boring Stuff

# Everything that can be automated, should be:
ci:
  - linting (ESLint, Prettier)
  - type checking (TypeScript)
  - unit tests
  - integration tests
  - security scanning (Snyk, Dependabot)
  - bundle size check
  - performance benchmarks
 
# Humans should review:
  - Logic correctness
  - Architecture decisions
  - Edge case handling
  - Security implications
  - Whether the approach makes sense

Rule 5: Two Types of Comments

Blocking (must fix before merge):
  "This SQL query is vulnerable to injection. Use parameterized queries."
  "This will cause a null pointer exception when the user has no address."

Non-blocking (suggestion, take it or leave it):
  "nit: Consider renaming this variable for clarity"
  "optional: You could simplify this with a reduce()"

Prefix non-blocking comments with "nit:" or "optional:"
so the author knows they can merge without addressing them.

Measuring Review Health

Track weekly:

Time Metrics:
  Time to first review:    Target < 4 hours
  Time to merge:           Target < 24 hours
  Review cycles:           Target < 2

Quality Metrics:
  PRs merged without tests: Target 0 (except config changes)
  Production incidents from merged PRs: Track, aim for 0
  Post-merge issues found:  Target < 5% of PRs

Volume Metrics:
  Reviews per engineer per day: Target 2-4
  PR size (median lines):  Target < 300
  PRs open > 48 hours:     Target 0

The Cultural Shift

What Good Review Culture Looks Like

  • Reviews are a priority, not an interruption
  • Feedback is about the code, not the person
  • Authors respond to feedback quickly (same day)
  • Disagreements are resolved in comments, not meetings
  • Everyone reviews, including senior engineers and managers who code

What Bad Review Culture Looks Like

  • Reviews pile up because "I'm heads down on my feature"
  • Senior engineers' PRs get rubber-stamped
  • Feedback is personal or nitpicky
  • PRs are abandoned and re-created because they went stale

Start This Week

  1. Measure your current time-to-first-review (check your Git platform's analytics)
  2. Set a 4-hour SLA and announce it to the team
  3. Reject any PR over 400 lines — ask the author to split it
  4. Add a PR template with the description format above
  5. Automate linting, formatting, and type checking in CI

Code review should make your team faster and your code better. If it's doing neither, the process is broken — not the concept. Fix the process.

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