Tag: ai code review
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Building a Healthy Code Review Culture: Lessons from Fast-Growth SaaS Teams
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In the world of modern software development, few processes play as significant a role in shaping product quality, team collaboration, and engineering culture as the code review. For fast-growing SaaS companies — where speed, scalability, and innovation are constant pressures — building a healthy, sustainable code review culture isn’t just a nicety. It’s a survival…
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How to Reduce Pull Request Cycle Time: 5 Proven Strategies for Faster Code Reviews
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Pull requests are the heartbeat of software collaboration. They allow developers to share work, catch bugs earlier, and maintain code quality at scale. But talk to any engineering leader at a growing SaaS or tech-enabled company, and you’ll hear the same frustration: pull requests that sit idle for days. What looks like a small delay…
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Why Bad Code Review Advice Still Hurts Your Team — and How Context-Driven AI Transforms Reviews
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While writing this piece, I’m also scrolling through developer Slack channels — sifting through endless discussions on AI code review tools, manual review habits, and “best practices” that range from helpful to… let’s just say, well-meaning chaos. If you’ve spent any time in engineering, you know the memes: comments about commas, nitpicks on personal style, or the…
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AI-Generated Code: Finding the Right Percentage for Your Development Team
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If you’ve ever asked yourself, “How much of our code should be AI-generated?”, you’re tapping into one of the most pressing questions in modern software development. The answer isn’t a fixed number but a nuanced balance between productivity, quality, and team confidence — all shaped by how AI integrates into your workflow. The Elusive “Right” Percentage While…
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The Illusion of Thinking: Why Apple’s Findings Hold True for AI Code Reviews
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Recent research has cast new light on the limitations of modern AI “reasoning” models. Apple’s 2025 paper The Illusion of Thinking shows that today’s Large Reasoning Models (LRMs) — LLMs that generate chain-of-thought or “thinking” steps — often fail on complex problems. In controlled puzzle experiments, frontier LRMs exhibited a complete accuracy collapse beyond a complexity threshold. In other…
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Build vs. Buy: Panto’s Take on AI Code Reviews and Code Security
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As we talk to CTOs and engineering leaders, a common refrain we hear is, “We could just build this ourselves.” The idea of a custom, home-grown AI code review or code security tool can be tempting. It offers promises of full control, perfect fit to internal processes, and no subscription fees. It sounds great on…