We are Changing our Developer Productivity Experiment Design

Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity

We conduct a randomized controlled trial to understand how early-2025 AI tools affect the productivity of experienced open-source developers working on their own repositories. Surprisingly, we find that when developers use AI tools, they take 19% longer than without—AI makes them slower.

AI | 2025 Stack Overflow Developer Survey

84% of respondents are using or planning to use AI tools in their development process, an increase over last year (76%). This year we can see 51% of professional developers use AI tools daily.

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 outp

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 outp

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.

The ‘productivity paradox’ of AI adoption in manufacturing firms | MIT Sloan

Companies that adopt industrial artificial intelligence see productivity losses before longer-term gains, according to new research.

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 coding agents generate more code, but not more software

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

Arvind Narayanan on Twitter / X

To understand and empathize with how workers in many or most fields outside software experience advances in AI capabilities, I propose a little thought experiment. https://t.co/QZG24aRiBe— Arvind Narayanan (@random_walker) July 28, 2026

Developers, Reinvented – Thomas Dohmke

What started as fear of AI replacing developers is switching to pragmatically embracing the ambitious reality of AI and viewing it as a growth opportunity. As we build the tools of tomorrow, we can usher developers through this reinvention of their role in ways that are intuitive, delightful, and cater to developers’ curiosity, keeping them fulfilled and happy during the transition. That makes us optimistic. Realistically.

Measuring the Impact of Early-2025 AI on Experienced Open-Source...

Despite widespread adoption, the impact of AI tools on software development in the wild remains understudied. We conduct a randomized controlled trial (RCT) to understand how AI tools at the...

Tech companies are cutting jobs and betting on AI. The payoff is far from guaranteed

AI experts say we’re living in an experiment that may fundamentally change the model of work

How building software is changing at Anthropic

A deepdive on what’s changed in how the leading AI lab makes software. Ever more code review and testing is done by AI, two-pizza teams very much alive, and more. Details from inside of Anthropic

Study finds AI tools made open source software developers 19 percent slower

Coders spent more time prompting and reviewing AI generations than they saved on coding.

The Recurring Cycle of 'Developer Replacement' Hype

AI isn't replacing developers, it's transforming them. Just as NoCode created specialists and cloud turned sysadmins into DevOps engineers, AI elevates engineers from code writers to system architects. The most valuable skill isn't writing code, it's designing coherent systems.