So where are all the AI apps?

Summary

Fans of vibecoding and agentic tools say they are 2x as productive, 10x as productive – maybe 100x as productive! Someone built an entire web browser from scratch. Amazing! So, skeptics reasonably ask, where are all the apps? If AI users are becoming (let’s be conservative) merely 2x more productive, then where do we look to see 2x more software being produced? Such questions all start from the assumption that the world wants more software, so that if software has gotten cheaper to make then people will make more of it. So if you agree with that assumption, then where is the new software surplus, what we might call the “AI effect”? We’ll look at PyPI, the central repository for Python packages. It’s large, public, and consistently measured, so we should expect to see some AI effect there. Counting packages There it is, see it? The release of ChatGPT. Does it look like an epochal revolution of software productivity on the upper chart? No. There are a few spikes in the lower chart showing new packages/month, in what you might call the “AI era” of 2020 onward. But those reflect spam and malware floods, not genuine package creation. Two-panel chart showing PyPI total packages growing exponentially to 800k and new packages per month fluctuating around 5-15k, with ChatGPT release marked showing no obvious inflection point This is curious. If AI is making software engineers more productive, why aren’t they producing more software? Counting updates But, you might say, package creation is not the right measure. Anyone can create and upload a “package” which is nothing but a hello world demo. This is always easier than creating something durable which people actually use. We want to look at “real” packages, packages which are actually downloaded, used, and maintained over time. Okay, so let’s consider a different chart. We start by gathering the 15,000 most downloaded Python packages on PyPI in December 2025. Then we split the packages into cohorts based on their birth-year, ...