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Software Engineering

The Code Review Bottleneck Nobody Scaled For

Software Engineering

6 min read

When writing code was the slowest part of delivery, review capacity was rarely the constraint. Now that generation is fast, review has quietly become the bottleneck almost every team underestimated — and rubber-stamping under volume pressure is how real defects slip through.

Scaling review capacity to match generation speed is an organisational design problem, not a tooling problem that a better linter solves.

Why adding more reviewers doesn't scale the way it looks like it should

Review quality depends on context the reviewer holds in their head about the system, not just time spent reading a diff. Adding reviewers who lack that context increases throughput of approvals, not quality of review — a dangerous substitution to make under deadline pressure.

The actual lever is reducing how much needs deep human review per change, by raising automated verification standards for the routine parts and reserving human attention for the judgement calls.

What should automatically clear review versus what never should

Changes with strong behavioural test coverage, low blast radius, and a clear, narrow intent are reasonable candidates for lighter-touch automated gating. Changes touching authentication, data migration, financial calculation, or anything irreversible should never have review depth reduced regardless of how confident the generating agent appeared.

Faster code generation without faster, honest review capacity doesn't ship faster. It ships riskier.MNB Software Engineering Practice

Key actions

  • Measure review depth, not just review turnaround time
  • Reserve deep human review for high-blast-radius changes specifically
  • Raise automated verification standards for routine, low-risk changes
  • Never let deadline pressure reduce review depth on irreversible changes

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