Friday afternoon. An engineer at Anthropic wrote a spec for a new plugin feature, pointed Claude at an Asana board, and went home for the weekend.
Monday morning. The AI had broken the spec into tickets, spawned separate agents for each one, built the feature independently across all of them, and it was done.
No human intervention. No check-ins. No pair programming. A production feature, built and shipped in 48 hours by AI agents working autonomously.
Around the same time, Andrej Karpathy — former Tesla AI lead, OpenAI founding member, and one of the most credible voices in the field — tweeted: “Hard to communicate how much programming has changed due to AI in the last 2 months.“
Two months. Not two years.
I find Karpathy’s framing interesting. He didn’t say “programming has improved“ or “programming is faster.“ He said it has changed. And he said it’s hard to communicate how much — which, from someone who literally builds these systems, suggests the shift is bigger than even informed observers expect.
Here’s what I think this means practically.
The bottleneck in software development has moved. It used to be: can we build this? Now it’s: should we build this, and can we describe what we want clearly enough?
The “10x engineer“ was someone who could write code faster and cleaner than their peers. The valuable person now is whoever can write the clearest spec. Articulate the goal precisely, define the constraints, describe what “done“ looks like — and the AI handles execution.
For PE-backed businesses, this has immediate implications. That 15-person dev team you’re funding? Within 12 months, the same output could come from 3 people with AI agents. Not because the other 12 are bad at their jobs, but because the nature of the job has changed.
The companies that reorganise around this reality will move faster and spend less. The ones that don’t will wonder why their competitors keep shipping features they can’t match.
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