You just ran a dependency scan and the report shows 133 vulnerabilities. 34 are Critical. 68 are High. The dashboard is red, the backlog is exploding, and every item looks urgent. The engineering team asks the obvious question: where do we start? This is where vulnerability remediation prioritization matters. Without a clear framework, teams either panic and chase the loudest CVE, or they ignore t
I was out walking with my dog Dexter, daydreaming on the first properly warm day of the year. I was lost in my own mind mulling over a conversation I'd had with a fellow Game Developer about how we've adapted to the use of AI as software engineers. None of the existing labels fit. "Vibe coding", Karpathy's term, elicits a culture of care-free one-shotting with little to no regard for the code qual
Vendredi matin, 9 h 15. Françoise est dans son cockpit — trois écrans, à gauche l'Excel-pointeuse qu'elle tient à jour depuis quinze ans, à droite Sage, et au milieu Rembrandt depuis trois semaines. Sa tasse à la main, celle avec sa tête imprimée dessus que quelqu'un lui a offerte à Noël. Elle pivote sur sa chaise et me lance depuis son bureau : « Michel, combien on a d'inscrits pour la rentrée, d
« Hold on, we need to talk, this doesn't add up » Friday morning, 9:15 AM. Françoise is in her cockpit — three screens: on the left the Excel attendance sheet she's kept up to date for fifteen years, on the right Sage, and in the middle Rembrandt for three weeks now. Cup in hand, the one with her face printed on it that someone gave her at Christmas. She swivels in her chair and calls over from
Practical post for engineers who've hit the wall where an AI proof-of-concept works on clean data but can't connect to the legacy systems that hold actual production data. Disclosure: I work at Ailoitte, which builds AI integration layers connecting legacy infrastructure to production AI. Sharing what the engineering actually looks like. AI models expect structured, consistently formatted data. Le
You write a detailed design doc. You paste it into your AI assistant. You wait. The output compiles. Tests pass. And yet — it's not quite what you designed. The auth middleware is in the wrong layer. The error handling pattern differs from the rest of the codebase. The field names don't match the schema. You fix it. Next task, same thing. This happens constantly, and it's not a model capability pr
Table of Contents Introduction Environment Requirements Core Features Core Design and Code Analysis Actual Execution Demo Architecture Overview How You Can Expand Future Plans & Conclusion What is this It is a basic debugger, running on Linux and implemented in C++, aiming to create a debugger that is easy to read and expand. In addition, Lavender's main function is to help users analyze the logic
I’ve been diving into Solana development for the past 10+ days as part of 100DaysOfSolana. Today, I successfully moved my scripts into the browser to build a functional Devnet Dashboard. It was a great exercise in handling RPC providers and managing BigInt data for UI display. Major shoutout to Major League Hacking for the challenge. Looking forward to the next arc!