While AI significantly boosts developer productivity, it also introduces challenges such as hallucinations, mistakes, and potential security vulnerabilities in the generated code.
The increased volume of AI-generated code is causing the outer loop (code review, testing, merging, and deployment) to become a major bottleneck.
This challenge, previously common only for large companies, is now affecting all companies, necessitating new tools for prioritizing, tracking, reviewing, merging, and deploying code.
The problems created by AI can also be solved by AI, by streamlining traditionally manual and undesirable parts of the code review process.
The goal is to develop "self-driving code review solutions" that automate manual tasks, allowing developers to focus on product delivery and feature functionality.
It's crucial for the entire developer toolchain, not just the Integrated Development Environment (IDE), to be AI-native to effectively support the significantly increased developer productivity.
Introducing Graphite's Diamond AI Code Review Platform 04:16
Graphite developed Diamond, an AI code review platform designed for high signal and low noise, with a deep understanding of the codebase and its change history.
Diamond summarizes, prioritizes, and reviews code changes, integrating with Continuous Integration (CI) and testing infrastructure to identify and help correct errors and failures.
The platform aims to reduce code review cycles, enforce quality and consistency, and maintain code privacy and security.
Diamond offers actionable one-click suggestions and is customizable; its AI bot comments are downloaded at less than a 4% rate.
Diamond's comments are accepted at a 52% rate, which is higher than the 45-50% acceptance rate for human comments, with this 52% figure being new as of March.