So where are all the AI apps?
TL;DR Highlight
No visible inflection in PyPI package creation after ChatGPT launch — structural reasons why AI productivity gains do not translate into more public software
Who Should Read
Developers questioning AI tool ROI; engineering leaders evaluating AI adoption impact
Core Mechanics
- No clear inflection in new PyPI packages post-ChatGPT — spam/malware spikes excluded
- Post-ChatGPT packages update more frequently in their first year (6→13 releases/year)
- Key reasons: AI-built apps stay internal; first 90% easier but last 10% harder (large codebase, low familiarity)
Evidence
- Answer.AI analyzed total PyPI package count and update frequency by cohort across the top 15,000 most-downloaded packages
- HN comments: iOS App Store new submissions up 24% — metric-dependent picture
How to Apply
- Measure AI productivity gains via internal deployments and automation increases rather than public artifacts like package counts
- After adopting AI tools, invest separately in maintaining debugging competency — technical debt compounds when code is shipped without understanding
Terminology
PyPI(Python Package Index)Official repository for Python packages — used as a proxy metric for software productivity