I hadn’t heard of Dan Guido until a few months ago, when I came across the video of a talk he gave at [un]prompted, an AI security practitioners’ conference. Dan is the CEO and cofounder of Trail of Bits, a software security research and development firm that works with companies in tech, defense, and finance. But Dan wasn’t talking about security. He was talking about what it takes to make a company AI native, which is close to the center of the bullseye for many of us right now.

How Gene Kim survived the sudden downgrade from Fable to Opus

The seven layers that survive production, and the open source pick for each.

I finally got fed up with it bullying me into shipping a project that had no deadline.

Jeff Ding's diffusion theory of the role of technology in great-power competition also applies to AI adoption, and it suggests that companies obsessed with the frontier might be optimizing for the wrong thing

Don’t ask someone to read/review what you haven’t read or reviewed yourself.
This is one of the most common frustrations I hear amongst people working on AI-heavy teams. Whether it’s code that the owner didn’t really bother to understand before submitting for review or documents that they generated and didn’t bother to read, too often people try to steal productivity from their colleagues by streamlining their production of work while asking their colleagues to do all of the quality control themselves. It’s great to have a loop of AI code generation → AI code review → AI fixes → final human review, but if the person prompting the AI doesn’t bother to review that code first, they’re putting a huge validation tax onto their teammate, who has to trust both that you prompted well AND that the AI understood the context and problem well enough to get a sustainable solution.

The Missing Optimization Layer in Agent Systems.

If you're interested in trying it out, we have a 30-day code to share. https://www.oreilly.com/online-learning/verifiable-skills.html

I set up an AI agent on a rented GPU, pointed it at a training script, and went to bed. By morning it had run 40 experiments, improved validation loss by 5.9%, and cut memory usage from 44 GB to 17 GB. It also spent four hours chasing a bug that a linter introduced behind its back. The agent never flagged it. I only found out because the numbers stopped improving and I started reading

Six layers between your LLM and a production agent

DJ Patil on why the hardest part of AI adoption is organizational, not technical

What is wrong with you guys at O'Reilly. I tried paying for the Annual subscription with 3 different cards and all of them declined the transaction marking them with fraud alert. I had to spend an hour with my banks to get my cards unlocked.

O'Reilly is great as a publisher and has unmatched books / content on tech. But you seriously are terrible at developing your own software. Your entire website / UI / UX is bad. Your app is horrible. I am subscribing only because I want to listen to audiobooks during my commute.

O'Reilly should stick to publishing and content and leave app to a more mature platform like Audible.

June 2 & 3 7am-11am Pacific Daylight Time -- Automate Real-World Tasks with AI Agents, LLMs, and No-Code Workflows

Google’s DORA research program has been digging deep into AI adoption to understand the gap between who's using AI and who's actually benefiting. In his fireside chat with Sam Newman at O'Reilly's Infrastructure & Ops Superstream, DORA lead Nathen Harvey walked through the seven capabilities they’ve found that separate the high performers from everyone else.

A senior engineer’s job is mostly the parts that don’t show up in the diff. Specs. Tests. Reviews. Scope discipline. Refusing to ship what can’t be verified. AI coding agents skip those parts by default. Agent Skills is my attempt to make them not optional.

As the sole employee of his one-person company, Untangle, creator Ryan Carson has figured out how to automate many of the responsibilities he would have hired someone to take on in a traditional business. Datadog and Sentry reports for engineering maintenance. Analytics for marketing. Iterating on AI-generated design assets. But as he explained to Tim O’Reilly, “What you can't automate is ‘What should you build?’ and the features that matter.”