927: Automating Code Review with AI, feat. CodeRabbit’s David Loker
Earlier this year, David Loker joined CodeRabbit as their Director of AI. As more people come to write code with the help of large language models, David believes CodeRabbit will become a helpful assistant for code reviewing and pull requests. He tells Jon Krohn how CodeRabbit assists developers with real-time feedback, as well as the reality of vibe coding, the optimization challenges of agentic AI, and other pressing questions in AI and tech.
This episode is brought to you by the Dell, by Intel, by Gurobi and by ODSC, the Open Data Science Conference.
Additional materials: www.superdatascience.com/927
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(01:26) How CodeRabbit helps with coding
(17:30) Context engineering in context
(40:40) How CodeRabbit keeps data secure
(46:10) David’s thoughts on “vibe coding”
(1:03:04) If machines will ever be truly creative
#287 Sahil Bansal: Why Developers Are Switching to CodeRabbit's AI Code Reviews
Try OCI for free at http://oracle.com/eyeonai This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved. AI-generated code is exploding, but reviewing it all has become the new bottleneck for engineering teams. In this episode, Sahil Bansil from CodeRabbit reveals how their AI-powered platform is transforming the code review process, helping developers ship faster without compromising quality. He explains how CodeRabbit uses advanced LLM context engineering to deliver senior-level review quality, reduce pull request merge times by up to 50%, and catch more bugs before they reach production.
Whether you're a developer, engineering manager, or CTO, this conversation shows why automated code review is essential in the AI era and how CodeRabbit can help your team scale software delivery while keeping quality high.
Cut Code Review Time & Bugs in Half. Instantly with CodeRabbit: https://www.coderabbit.ai/
Stay Updated: Craig Smith on X:https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI (00:00) LLMs & Why Context Matters (02:26) Meet Sahil Bansil from CodeRabbit (04:04) AI Code Boom & The Review Bottleneck (06:05) Why CodeRabbit Focused on Reviews, Not Generation (09:55) Keeping Humans in the Loop for Code Quality (14:30) IDE Reviews vs PR Governance (17:51) Inside CodeRabbit's Context Engineering (20:42) Building Context from Code Graphs & Jira Tickets (22:15) Eliminating AI Hallucinations with Verification (27:19) Empowering Junior Developers & Legacy Code Support (32:40) CodeRabbit's Open Source & Enterprise Success Stories (36:56) Cutting Review Times & PR Merge Delays (44:35) Scaling CodeRabbit & The Growing Market
Conversations at the Intersection of AI and Code with Harjot Gill
AI is rewriting the rules of code review and CodeRabbit is leading the charge. In this featured episode of Screaming in the Cloud, Harjot Gill shares with Corey Quinn how his team built the most-installed AI app on GitHub and GitLab, nailed positive unit economics, and turned code review into a powerful guardrail for the AI era.
Show Highlights
(0:00) Entrepreneurial Journey and Code Rabbit's Origin
(3:06) The Broken Nature of Code Reviews
(5:47) Developer Feedback and the Future of Code Review
(9:50) AI-Generated Code and the Code Review Burden
(11:46) Traditional Tools vs. AI in Code Review
(13:41) Keeping Up with State-of-the-Art Models
(16:16) Cloud Architecture and Google Cloud Run
(18:21) Context Engineering for Large Codebases
(20:52) Taming LLMs and Balancing Feedback
(22:30) Business Model and Open Source Strategy
About Harjot Gill
Harjot is the CEO of CodeRabbit, a leading AI-first developer tools company.
Links
Harjot on LinkedIn: https://www.linkedin.com/in/harjotsgill/
Sponsor
CodeRabbit: https://coderabbit.link/corey
CodeRabbit and RAG for Code Review with Harjot Gill
One of the most immediate and high-impact applications of LLMs has been in software development. The models can significantly accelerate code writing, but with that increased velocity comes a greater need for thoughtful, scalable approaches to codereview. Integrating AI into the development workflow requires rethinking how to ensure quality,security, and maintainability at scale.
CodeRabbit is a startup that brings generative AI into the code review process. It evaluates code quality and security directly within tools like GitHub and VS Code, acting as an AI reviewer that complements existing CI/CD pipelines. Harjot Gill is the founder and CEO of CodeRabbit. He joins the podcast with Kevin Ball to discuss CodeRabbit’s architecture. Its multi-model LLM strategy, how it tracks the reasoning trail of agents, managing context windows, lessons from bootstrapping the company, and much more.
Full Disclosure: This episode is sponsored by CodeRabbit.
Kevin Ball or KBall, is the vice president of engineering at Mento and an independent coach for engineers and engineering leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript meetup, and organizes the AI inaction discussion group through Latent Space.
Please click here to see the transcript of this episode.
Sponsorship inquiries: sponsor@softwareengineeringdaily.com
The post CodeRabbit and RAG for Code Review with Harjot Gill appeared first on Software Engineering Daily.
The New Bottleneck: AI That Codes Faster Than Humans Can Review
CodeRabbit, led by founder Harjot Gill, is tackling one of software development's biggest bottlenecks: the human code review process. While AI coding tools like GitHub Copilot have sped up code generation, they’ve inadvertently slowed down shipping due to increased complexity in code reviews. Developers now often review AI-generated code they didn’t write, leading to misunderstandings, bugs, and security risks. In an episode of The New Stack Makers, Gill discusses how Code Rabbit leverages advanced reasoning models—OpenAI’s o1, o3 mini, and Anthropic’s Claude series—to automate and enhance code reviews.
Unlike rigid, rule-based static analysis tools, Code Rabbit builds rich context at scale by spinning up sandbox environments for pull requests and allowing AI agents to navigate codebases like human reviewers. These agents can run CLI commands, analyze syntax trees, and pull in external context from Jira or vulnerability databases. Gill envisions a hybrid future where AI handles the grunt work of code review, empowering humans to focus on architecture and intent—ultimately reducing bugs, delays, and development costs.
Learn more from The New Stack about the latest insights about AI code reviews:
CodeRabbit's AI Code Reviews Now Live Free in VS Code, Cursor
AI Coding Agents Level Up from Helpers to Team Players
Augment Code: An AI Coding Tool for 'Real' Development Work
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