Code Review
The systematic practice of having team members examine each other's code changes before merging, catching bugs, enforcing standards, sharing knowledge, and improving overall code quality.
Code review is one of the highest-leverage engineering practices. Studies consistently show that code review catches 60-90% of defects before they reach production. Beyond bug detection, reviews spread knowledge across the team, enforce consistent patterns, and provide mentorship opportunities for junior developers.
Effective code review has clear guidelines: review within 24 hours of submission, keep changes small (under 400 lines for effective review), focus on logic and design rather than style (use linters for style), provide constructive feedback with explanations, and approve changes that are "good enough" rather than demanding perfection.
For AI teams, code review should extend beyond application code. Prompt changes, model configuration updates, evaluation pipeline modifications, and data processing scripts all benefit from peer review. AI-specific review considerations include checking for prompt injection vulnerabilities, verifying evaluation coverage, ensuring model fallback paths are tested, and validating that data transformations preserve the statistical properties needed for model quality.
Related Terms
A/B Testing
A controlled experiment comparing two or more variants to determine which performs better on a defined metric, using statistical methods to ensure reliable results.
Feature Flag
A software mechanism that enables or disables features at runtime without deploying new code, used for gradual rollouts, A/B testing, and targeting specific user segments.
MLOps
The set of practices combining machine learning, DevOps, and data engineering to reliably deploy, monitor, and maintain ML models in production.
Model Serving
The infrastructure and systems that host trained ML models and handle inference requests in production, optimizing for latency, throughput, and cost.
Semantic Search
Search that understands the meaning and intent behind a query rather than just matching keywords, typically powered by embedding-based similarity comparison.
CI/CD (Continuous Integration / Continuous Deployment)
An automated software practice where code changes are continuously integrated into a shared repository, tested, and deployed to production, reducing manual intervention and accelerating delivery cycles.