Decision graph tooling for AI-assisted development - track every choice, query your reasoning
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.
My Thoughts on AI, Part 2: Agent Setup, Workflow, and Tools
My own personal AI development setup, workflow, and tooling
Models.dev — An open-source database of AI models
Models.dev is a comprehensive open-source database of AI model specifications, pricing, and features.
We build AI that works for humans
Imbue builds AI to help people think, create, and build. We share our tools openly because we believe progress in AI should be collaborative and developer-driven
Meet Foundry: An AI Startup that Builds, Evaluates, and Improves AI Agents
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...
AI-native project management | Plane
Project management for teams and AI agents. Plan, track, and ship with Projects, Wiki, and AI. Available on cloud, self-hosted, and air-gapped.
Primitive | Decision infrastructure for AI agents
Primitive captures your decisions as you build, shares them with your team, and holds your agents to them.
My AI Content Journey
I apologize ahead of time, what follows has no tooling applied to it. No grammar checks, no AI, and...
Fulcrum - Leverage for Discovery
We place AI engineers with research labs working on hard scientific problems.
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 ...
Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
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 February-June 2025 frontier affect the productivity of experienced open-source developers. 16 developers with moderate AI experience complete 246 tasks in mature projects on which they have an average of 5 years of prior experience. Each task is randomly assigned to allow or disallow usage of early 2025 AI tools. When AI tools are allowed, developers primarily use Cursor Pro, a popular code editor, and Claude 3.5/3.7 Sonnet. Before starting tasks, developers forecast that allowing AI will reduce completion time by 24%. After completing the study, developers estimate that allowing AI reduced completion time by 20%. Surprisingly, we find that allowing AI actually increases completion time by 19%--AI tooling slowed developers down. This slowdown also contradicts predictions from experts in economics (39% shorter) and ML (38% shorter). To understand this result, we collect and evaluate evidence for 20 properties of our setting that a priori could contribute to the observed slowdown effect--for example, the size and quality standards of projects, or prior developer experience with AI tooling. Although the influence of experimental artifacts cannot be entirely ruled out, the robustness of the slowdown effect across our analyses suggests it is unlikely to primarily be a function of our experimental design.
My AI Adoption Journey
My experience adopting any meaningful tool is that I've necessarily gone through three phases: (1) a period of inefficiency (2) a period of adequacy, then finally (3) a period of workflow and life-altering discovery.
ARC-AGI-3
ARC-AGI-3 is the first interactive reasoning benchmark for AI agents—play as humans and build agents that learn in novel environments.
