A research-backed AI scenario forecast.
Europe 2031 — What getting AI wrong means for us
A five-year scenario about AI and Europe's impending slide into irrelevance, with a 2034 epilogue that describes how the collapse of the European model could have been prevented.
More Than a Tool
What We Learned from a Year of Conversations About AI
AI Index | Stanford HAI
The mission of the AI Index is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI. To achieve this, we track, collate, distill, and visualize dat
A Short Guide to Data Strikes and Conscious Data Contribution in the Context of 2026 Frontier AI
Back to the basics of data leverage.
The Future of Software Engineering Isn’t What You Think
Over the past two decades, I’ve watched software eat the world, then hardware catch up, then Generative AI reshape both at the same time…
The AI "Evaluation Crisis" Is an Opportunity to Get Data Flow Right
Why the AI evaluation crisis could force a reckoning on dataset provenance, attribution, and consent.
On AI and building your own GIS software
Of the thousands of essays over the past two years surrounding AI and its implications are some very thought provoking ones with enormous implications for GIS. Some of the essays are around the the…
Resetting on engineering expectations in the age of AI
I’m accepting new sponsorships for The Modern Leader for 2026. If you’re interested (or you think your company may be interested), you can learn more here.
Datacurve | The data engine for frontier AI
Custom data for long-horizon reasoning, software engineering, and data science.
The Singularity Is Not What It Seems
Whatever the AI future is, we’re in it right now.
The Singularity Is Not What It Seems
Whatever the AI future is, we’re in it right now.
The New Software Lifecycle
I co-wrote a Google whitepaper about how AI is changing the software lifecycle. I'm not going to summarize the whole thing. Instead, here are the handful of ...
The Eternal Sloptember
I’m calling it now, the adoption of AI agents into software development will be one of the most costly mistakes in the field’s history. Agents cannot program, and it’s taking longer and longer to realize that they can’t. They are a highly sophisticated statistical model designed to mimic the distribution of programming. The output is broken, but in a way that’s getting harder and harder to detect. Which is exactly what you’d expect from an increasingly accurate statistical model.
Labor market impacts of AI: A new measure and early evidence
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
An Alignment Journal: Features and policies — LessWrong
We previously announced a forthcoming research journal for AI alignment. This cross-post from our blog describes our tentative plans for the features…
Import AI 446: Nuclear LLMs; China's big AI benchmark; measurement and AI policy
Will AIs be jealous of one another?
