Technical DebtCode QualityEngineering
Merlin AI Code Review

Using AI Code Review to Stop Technical Debt Before It Starts

February 24, 2025·7 min read·Merlin AI Code Review Team

Technical debt doesn't arrive in dramatic monoliths. It accumulates one pull request at a time — a workaround here, a copy-paste there, a test skipped under deadline pressure. By the time it's visible, it's already expensive. Merlin AI Code Review intercepts debt at the source: the PR.

How technical debt enters the codebase

Most technical debt comes from five common patterns that are each defensible in isolation but compound over time:

Each pattern is easy to spot in isolation. The problem is that human reviewers under time pressure miss them, or spot them but don't raise them to avoid slowing down the team. AI review doesn't get tired, doesn't feel social pressure, and applies the same scrutiny to every PR.

Catching duplication before it compounds

With RAG enabled, Merlin AI Code Review indexes your codebase and recognizes when a PR introduces logic that already exists elsewhere. Instead of a generic "consider abstracting this" comment, Merlin AI Code Review can say: "This validation logic is identical to src/utils/validators.ts:validateEmail() — consider reusing that function."

This is the kind of comment that only a reviewer who knows the entire codebase intimately can make — which is why it's so rarely made in practice.

Enforcing test coverage

The /test command generates unit tests for changed code and posts them as a PR comment. For teams that require tests before merge, this gives authors a starting point rather than a blank page — dramatically reducing the excuse of "it's complex to test". The /coverage command analyses which files in the PR lack test coverage and flags them explicitly.

Documentation debt prevention

The /add_doc command generates docstrings for changed public functions and posts them as GitHub suggestion blocks. One-click to apply. This eliminates the most common form of documentation debt at zero friction cost to the author.

Pattern violation detection via RAG

When your codebase has an established pattern for error handling, database access, logging, or API responses, RAG-enabled Merlin AI Code Review will flag PRs that deviate from those patterns — not because they're wrong in general, but because they're inconsistent with your specific codebase. Inconsistency is the primary driver of maintenance burden.

The compounding argument for early intervention

The math of technical debt is unforgiving. A duplication that takes 30 minutes to prevent at review time may take 3 days to refactor after it has been copied five more times, integrated into three services, and become load-bearing infrastructure. Catching 10 such patterns per week at review time saves potentially weeks of engineering effort per quarter.

Merlin AI Code Review's value isn't in the individual comments — it's in the consistent, compounding effect of catching debt before it compounds.