AI coding agents generate more code, but not more software

Study finds coding efficiency gains get "absorbed" by human review "bottleneck."

Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools

How do the productivity effects of AI evolve across successive generations of tools, and to what extent do task-level gains ultimately translate into final output? We study these questions in the context of software development, using data on more than 100,000 GitHub developers combined with their AI usage telemetry. In a matched event study design, we find that autocomplete, interactive coding agents, and autonomous coding agents each significantly increase coding activity ("commits"), with respective cumulative effects of 40%, 140%, and 180%. These gains, however, attenuate sharply across the production hierarchy: the 180% cumulative effect falls to 50% for the number of projects, and to 30% for actual releases. This pattern is consistent with the weak-link hypothesis: the strong productivity gains from AI are attenuated by human bottlenecks in the production chain, with an estimated elasticity of substitution of 0.25 between AI and human effort, which indicates strong complementarities. We further confirm these results across four major app marketplaces, finding a moderate increase in the number of new apps but no increase in total usage. Large task-level AI productivity gains have therefore translated only partially into shipped and used software thus far.

AI boosts worker productivity — but does that translate to final outputs? | MIT Sloan

A new study found that developers using AI tools can write much more code than those working without AI, but they don’t release as much new software.

Opinion | A.I. Slopware Is Everywhere Now. Nobody Is Using It.

Just because A.I. is revolutionizing coding, doesn’t mean it will automatically revolutionize our apps.

The LLM post - Bailey's Retrospective

Personal thoughts when the job changes

Using AI to write better code more slowly

A lot of people seem convinced that the point of AI coding is to write low-quality code as fast as possible. Spew out barely-passable slop, open massive PRs, and merge them unvetted. Ship it! But t…

「コードは一行も書いていない」　アイドルの宮本佳林さん、AIで配信システムを丸ごと構築　“技術ブログ”が話題

元Juice=Juiceの宮本佳林さんが8月1日、10時間のYouTube生配信を支えるシステムをAIとともに自作したと自身のブログで公開した。プログラミング経験ゼロで作り上げた開発の裏側をつづった“技術ブログ”に、X上では驚きの声が広がっている。

【やじうま配信者Watch】 宮本佳林さん、コード記述ゼロで10時間生配信システムを構築したことが話題に

コードが書けないアイドルが、 AIと一緒に10時間配信のシステムを 全部作った話。https://t.co/IHDrEc55um 技術面でまとめたものも書きました。https://t.co/cW5CuIzF21 是非見てみてね！

宮本佳林：元アイドルがバイブコーディングできるようになるまで。

こんにちは！2020年までハロー！プロジェクト Juice=Juiceで活動をし、卒業以降はソロで音楽活動をしております。 宮本佳林です！はじめましての方もこ…

The AI Engineering Report 2026: The AI Acceleration Whiplash - Ten Takeaways

What two years of telemetry data from 22,000 developers reveals about AI's real impact on developer productivity, code quality, and business risk in 2026.

Google Employees Internally Share Memes About How Its AI Sucks

Google’s CEO says 75% of the company’s code is AI-generated. The people who write that code say the AI they’re using is overhyped.

Stuck in the middle: Being an engineer & artist in the AI era | Annie Sexton | Offprint

I'm an AI skeptic, through and through. But I also voluntarily use AI nearly every day. So naturally, you might be asking: what the heck?

Mitchell Hashimoto (@mitchellh)

I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out. I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really). It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely. The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture. We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying. I worry.

AI Code Is Producing a Quality Crisis Nobody Wants to Talk About

The productivity numbers look great. AI coding tools are everywhere.

AI-generated code is 'pain waiting to happen'

The boom is piling up technical debt, warns Lightrun's Moshe Sambol

Software Developers Say AI Is Rotting Their Brains

“It's making me dumber for sure.”