A recent industry retreat of senior engineering practitioners published their findings on where software development is heading. Reading it felt like someone had been reading my mind — and the minds of the people I follow online — and synthesized it all into one document. When a lot of people arrive at the same conclusions independently, that’s signal worth paying attention to. Here’s my take on each major theme.
The era of fixed-fee AI spending just ended. If you’re a CTO or engineering leader and you haven’t noticed yet, you will very soon — probably around September 2026 when some budget alerts start firing.
There’s a reckoning coming for a specific type of software engineering manager. Not the good ones. The ones who turned themselves into human Jira routers. The ones whose primary skill is translating documents into tickets and running standups. Those jobs? Gone. Faster than you think.
Look, I’m going to be direct here. If you are not using AI agentic coding methods right now - today - you are going too slow. Not “a little behind.” Not “maybe missing something.” Too damn slow.
One morning I opened my HP ZBook Ultra G1a and the trackpad was dead. Keyboard fine. Touchscreen fine. External mouse fine. Trackpad: nothing. Twelve hours earlier it had worked. I hadn’t changed anything. Welcome to bleeding-edge silicon on Linux.
Open source is about to get a lot messier. Not because the code is getting worse – because AI agents just changed the economics of “fork it and fix it yourself.”
I’ve been thinking a lot about excellence lately. Not the motivational-poster kind. The real kind – the kind that gets baked into your bones when you’re twenty-two years old and surrounded by people who simply will not accept anything less. For me, that happened on a nuclear submarine.
I have a confession. I have a folder full of tiny bash scripts that make my life with GitHub dramatically easier. They’re not fancy. They’re not trying to be a framework. They are blunt instruments that solve real problems I have every single day.
The AI models are good enough. There, I said it. The bottleneck isn’t the model anymore – it’s how you use it.
Grace Hopper built the first compiler in 1952. They said “you can’t make them understand English-like instructions.” She had a running compiler and nobody would touch it. Sound familiar? Grace had some thoughts about this kind of thinking. She had a lot of thoughts, actually.