Daily Dose of Data Science on Twitter / X

AI Coding Agents: Adoption Trends - The JetBrains Blog

How many developers use AI coding agents (Claude Code, Codex, Cursor, JetBrains Junie, and others)? Evidence from the Developer Ecosystem Survey 2026.

How Do Scientists Use Claude Code?

Measuring Claude Code adoption among 16,000 scientists on GitHub

Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Running an AI-native engineering org | Claude

How the Claude Code engineering team’s processes and structure changed once agentic coding became the default way of working.

Supporting Our AI Overlords: Redesigning Data Systems to be Agent-First

Large Language Model (LLM) agents, acting on their users' behalf to manipulate and analyze data, are likely to become the dominant workload for data systems in the future. When working with data,...

Adoption and Impact of Command-Line AI Coding Agents: A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI

Organizations rolling out agentic command line tools like Anthropic's Claude Code and GitHub's Copilot CLI need to know who will try them, who will keep using them, and whether the tools produce enough output to justify their cost. At organizational scale, token spend can run into millions of dollars annually, so misreading adoption, retention, or impact can make a rollout expensive without changing engineering velocity. Studying tens of thousands of engineers at Microsoft over its early-2026 rollout, we find that first use spread primarily through social networks, retention was associated more with engineers' coding activity than with demographics, and adopters merged roughly 24% more pull requests than they would have otherwise. We use merged pull requests as our proxy for output -- acknowledging that a merged PR is not the same as the value it delivers -- and the lift persists across our four-month window. These results suggest that CLI coding agents are neither uniformly adopted nor mere novelty effects and that organizations should treat visible peer use as central to rollout strategy.

Impressions from visiting OpenAI, Anthropic, & Cursor

A peek into where software engineering is headed from inside the sector’s leading AI labs. Agents running in the cloud are a major trend, while coding harnesses are spreading beyond the craft

The Agents Are Waking Up

The Intelligence Revolution that swept through the software industry this past winter is coming to knowledge-work next.

klöss on Twitter / X

let me explain what Karpathy just sharedhe’s spending way less time using AI to write code and more time using it to build personal knowledge basesthe full breakdown: → he dumps raw sources (articles, papers, repos, datasets, images) into a folder. then has an LLM organize… https://t.co/Kdq1Q48S5P pic.twitter.com/XajJKR7xgT— klöss (@kloss_xyz) April 4, 2026

Georgi Gerganov on Twitter / X

llama.cpp at 100k starsnow that 90% of the code worldwide is being written by AI agents, I predict that within 3-6 months, 90% of all AI agents will be running locally with llama.cpp 😄Jokes aside, I am going to use this small milestone as an opportunity to reflect a bit on… pic.twitter.com/BpN5VL1bYV— Georgi Gerganov (@ggerganov) March 30, 2026

Digital Science on Twitter / X

An AI-native workspace that already knows your project?The new Papers AI from Digital Science keeps your drafts, data & references together, so the AI assistant has full context of your work - instead of starting fresh each time. 👉 Available now: https://t.co/DNcG173GDk… pic.twitter.com/FQWxdfKfS4— Digital Science (@digitalsci) August 4, 2026

We Got Claude to Fine-Tune an Open Source LLM

We’re on a journey to advance and democratize artificial intelligence through open source and open science.