Tag: ai
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Integrating SAST into Your CI/CD Pipeline: A Step-by-Step Guide
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If you’re looking to supercharge your software delivery while keeping security tight, integrating Static Application Security Testing (SAST) into your CI/CD pipeline is a game-changer. It’s not just about catching bugs — it’s about making security a seamless part of your development workflow, so your team can deploy confidently and quickly. Here’s how you can do it,…
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Revolutionizing Code Reviews: How AI is Transforming Technical Debt Management
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Let’s be honest: every software team, no matter how disciplined, wrestles with technical debt. As a CTO or Product Engineering Manager, you’ve seen how those “just this once” shortcuts and legacy code patches add up. Before you know it, your team is spending more time untangling old code than building new value. But here’s the…
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Optimize Your Codebase with Custom AI Training: Achieving Better Review Outcomes
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Imagine a world where every code review is lightning-fast, every vulnerability is caught before it ships, and every suggestion aligns perfectly with your team’s unique style and security policies. That’s not just a dream, it’s the reality for teams who have embraced AI code tools, but only if they take the crucial step of training…
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Reports VS Dashboards
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Back when I worked at Setu building the Data Business, I noticed something interesting. When the dashboard isn’t your core product, it becomes 100 times harder to get traction. On the other hand, sending a daily email report is much easier and helps you build the foundation for dashboard adoption. Dashboards are fancy. Dashboards are…
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In the AI Era, Why Solve for Just Code Reviews When the Whole SDLC Is Being Automated?
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When we started building Panto, we weren’t fixated on “what” we were building-we were obsessed with “why.” While most startups rush toward MVPs and quick launches, we sat with the discomfort of not knowing our exact direction. And yes, it was awkward to admit, especially when people would ask, “What are you guys building?” and…
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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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On-Premise AI Code Reviews: Boost Code Quality and Security for Enterprise Teams
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Engineering leaders must constantly balance rapid innovation with the need to protect code and data. Delivering features quickly is important, yet doing so without compromising quality or security remains a top priority. AI code reviews offer significant advantages, but relying solely on cloud-based solutions can introduce risks that many organizations, especially in regulated sectors, cannot…
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How to Reduce PR Merge Time from 14 Days to Under a Day?
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Imagine engineers finishing a new feature, only to see it sit idle in a pull request (PR) queue for days or even weeks. This delay is not just frustrating-it is expensive. According to Forrester (2024), slow PR merges cost teams up to $25,000 per developer each year. While competitors continue to release updates rapidly, delayed…
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How AI Is Reinventing Developer Onboarding — And Why Every Engineering Leader Should Care
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originally published on getpanto.ai Let’s be honest: onboarding new developers is hard. You want them to hit the ground running, but you also need them to write secure, maintainable code. And in today’s world, “getting up to speed” means more than just learning the codebase. It means understanding business goals, security protocols, and how to…