How to build and direct data science agents, and make each investigation improve the next.

I’ve known Jesse Vincent for more than 20 years, since the days when I was still editing and publishing Perl books and organizing the Perl Conference and he

Using AI productively

The buildings and physical infrastructure for a new hyperscale data-center region are complete. Power is live and redundant, the cooling loops are balanced,

Why graph modeling deserves as much attention as graph learning, GraphRAG, agents, and graph foundation models

How sandboxed computers let agents run code, use browsers, and work independently of your machine

The following article originally appeared on Arize’s blog and is being reposted here with the author’s permission.This week the AI community was in uproar

My conversation with Dan Gookin, the original For Dummies author and now mayor of Coeur d’Alene, Idaho, started as a publishing reunion. It ended with a much

A field guide to building a software factory that still has an owner.

What Model Context Protocol actually changes for agentic systems, and what it doesn’t

Learn software architecture directly from top experts with O'Reilly's immersive six-week cohort.

Slow AI is smooth AI, smooth AI is fast AI

Using Claude, Copilot, and other AI tools to save time and work more efficiently

Walk through the pipeline that made ChatGPT such an improvement over GPT-3

AI as an Enterprise Operating System, a keynote from Ai4 2026

Learn software architecture directly from top experts with O'Reilly's immersive six-week cohort.

The following article originally appeared on Addy Osmani’s blog and is being republished here with the author’s permission.A software factory harnesses

The way we talk about data is changing faster than the way we build it. Every quarter a vendor ships a new approach, coins a new term for it, or quietly adopts

Tacit knowledge is the hardest requirement in enterprise AI. Here's how a data and knowledge architect designs, and evaluates, for it.

What AI’s mathematical breakthroughs mean for human understanding, corporate power, and the future of knowledge work

My guest on this past week’s Live with Tim O’Reilly was Emmanuel Ameisen, a researcher on Anthropic’s AI interpretability team. I’d heard him give a short talk

How LLMs enable reasoning across heterogeneous enterprise data without centralized data consolidation

What agent interoperability standards change

How explicit organizational state helps agent platforms avoid exception drift

Learn software architecture directly from top experts with O'Reilly's immersive six-week cohort.

Why loop engineering needs a human at the boundary

Build reusable workflows in Claude and the Claude for Excel add-in

The following article originally appeared on Sean Goedecke’s blog and is being republished here with the author’s permission.In the 2010s, if you had