Someone made the argument that most developers were never really engineering — they were sourcing solutions from Stack Overflow and Reddit, and AI just swaps the supplier. It's an uncomfortable take. It's also not entirely wrong.
I've been asking 'can an agent do this?' so reflexively that I stopped noticing when the answer should have been 'but should it?'
I pointed an AI agent at a product initiative and didn't write a single line of code or a single word of copy. Two days later: 11 prototype pages, 4 strategic documents, cross-industry research with 30+ citations. And a trust problem I still can't solve.
Every productivity wave in software history expanded demand for developers instead of shrinking it. AI should follow the same pattern. Unless the thing it produces is just good enough to ship and just bad enough to compound.
Maybe the highest-value skill in the AI era isn't making or judging. It's matching — knowing what's right for this moment, this audience, this context.
AI can produce endlessly. But it can't tell you what's good. That gap — between generation and judgment — might be the only thing that matters now.
We keep reaching for craft metaphors — chef, artisan, architect — because 'person who types instructions' doesn't feel like enough. Why?
I published a prediction deck about the agentic web last September. Six months later, some of it looks prescient, some of it looks naive, and the most important developments weren't in the deck at all.
I just mapped the civil war inside every agent system. Both paths sound reasonable. But what if splitting investment across both means neither gets finished?
Every agent system is fighting the same battle: learn to navigate human interfaces, or demand native ones. The industry is doing both. The question is who adapts to whom.