DORA is a long running research program that seeks to understand the capabilities that drive software delivery and operations performance. DORA helps teams apply those capabilities, leading to better organizational performance.
LukeW | Common AI Product Issues
At this point, almost every software domain has launched or explored AI features. Despite the wide range of use cases, most of these implementations have been t...
Figma’s CEO on his new approach to AI
Figma is coming for the entire creative software industry.
Stories | Cyrus
Insights, tutorials, and case studies on AI-powered development workflows. Learn how teams use Cyrus with Linear and Claude Code to ship 20x faster.
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...
From OSS to Open Source AI: an Exploratory Study of Collaborative...
AI development is embracing open-source paradigm, but the fundamental distinction between AI models and traditional software artifacts may lead to a divergent open-source development paradigm with...
After automation: Software will work for you, not on you
Alex Komoroske, CEO and cofounder, Common Tools — AI promises “infinite software”—endless tools tailored to every need—but funneled through today's app stores, that abundance just means more silos, more trapped data, and more to orchestr...
Has This Report EXPOSED THE TRUTH About AI Assisted Software Development?
A Deep Dive Into MCP and the Future of AI Tooling | Andreessen Horowitz
We explore what MCP is, how it changes the way AI interacts with tools, what developers are already building, and the challenges that still need solving.
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 ...
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.
Introducing MAI-Cyber-1-Flash inside MDASH | Microsoft AI
Today we’re announcing MAI-Cyber-1-Flash inside of MDASH, our multi-agent vulnerability identification and remediation harness. Together they deliver world-class performance at 50% of the cost of leading models.
State of AI 2026 | The Industry-Defining Report
Explore how AI is shaping the digital economy in 2026, with 80+ pages of data on ad spend, app downloads, web behavior, user demographics, and so much more.
Arnau Gómez | Software Engineer | Web, Desktop & Mobile
I am Arnau, a software engineer at Tiptap (YC S23). For the past 6 years, I have helped companies like Amazon integrate AI into their web and mobile aplications. My focus is on TypeScript, React and PyTorch, with an emphasis on performance, QA and scalability. At Tiptap, I'm building the AI Toolkit, a platform where AI can work with documents on complex tasks.
State of AI Report 2025
The State of AI Report analyses the most interesting developments in AI. Read and download here.
LukeW | The Evolution of AI Products
At this point, the use of artificial intelligence and machine learning models in software has a long history. But the past three years really accelerated the ev...
Getting Started with ML and AI in Research Software | Software Sustainability Institute
Getting started with ML in research software means embracing a shift in how results are produced and reproduced. Instead of a fixed execution path, research software teams work with systems whose behaviour emerges from data, configuration, and training dynamics. Reproducibility becomes a matter of capturing the process rather than relying solely on the code. The tools and techniques outlined here can be adopted incrementally into existing projects, and together they provide a practical foundation for reproducible ML research.