Engineering

Working with AI to generate code is extremely satisfying. In a matter of minutes, you get something that looks great and, in most cases, does what you wanted it to do and even more. But many times, what looks ready for production is far from being production-safe. A large-scale study conducted by two researchers at FernUniversität in Hagen analyzed 7,703 files from public GitHub repositories explicitly attributed to AI tools. Using CodeQL, the researchers identified 4,241 CWE instances across 77 different vulnerability types. While 87.9% of the analyzed AI-generated code contained no identifiable CWE-mapped vulnerabilities, the risk came from code that appeared to work fine. It compiled, it solved the visible task, but it still carried hidden assumptions, unsafe patterns, and security debt. ...

A developer recently gave Claude Code write access to a live Meta Ads account. The agent’s read-only analysis was genuinely valuable; it correctly identified the cheapest campaign as having the worst ROI. The insight was good. The judgment about what to do next was absent. The agent executed autonomously, triggered API rate limits through automated publishing, and resulted in the account being permanently banned. The read was right, the write destroyed the business relationship. ...

Anyone Can Prompt. Not Everyone Can Engineer. What the AI coding revolution actually changes, and what it doesn’t. The Translation Layer Is Gone I recently watched an IBM video that made a point I’ve been thinking about ever since. The speaker walked through the entire history of programming languages, from machine code and assembler, through COBOL and FORTRAN, to object-oriented, web, and scripting languages, and made a simple observation: every generation moved a little closer to the way humans actually think and speak. ...

I heard Satya Nadella describe this week on the All-In podcast how LinkedIn has been collapsing product management, UX, and engineering roles into a single “full-stack builder” role. The framing was optimistic: AI reduces construction costs and speeds up delivery. At a surface level, this makes sense. AI dramatically accelerates prototyping, implementation, and iteration. In many environments, the traditional separation between PM, design, and engineering really does introduce friction that slows learning and execution. ...

Early in my career, coming from industrial engineering, I learned a simple rule that has shaped the way I think about software development ever since. Software may look abstract, creative, fluid. But underneath, it behaves like a production system. The best articulation of this idea appears in The Goal by Eliyahu M. Goldratt, one of the most influential books I have ever read. In production, every system revolves around three outputs you can influence: ...