In this episode, Ben Lorica and Drew Breunig, a strategist at the Overture Maps Foundation, talk all things context engineering: what’s working, where things are breaking down, and what comes next. Listen in to hear why huge context windows aren’t solving the problems we hoped they might, why companies shouldn’t discount evals and testing, and […]| Radar
This article is part of a series on the Sens-AI Framework—practical habits for learning and coding with AI. AI-assisted coding is here to stay. I’ve seen many companies now require all developers to install Copilot extensions in their IDEs, and teams are increasingly being measured on AI-adoption metrics. Meanwhile, the tools themselves have become genuinely […]| Radar
“Strange was obliged to invent most of the magic he did, working from general principles and half-remembered stories from old books.” — Susanna Clarke, Jonathan Strange & Mr Norrell Fairy tales, myths, and fantasy fiction are full of magic spells. You say “abracadabra” and something profound happens.1 Say “open sesame” and the door swings open. […]| Radar
In a fascinating op-ed, David Bell, a professor of history at Princeton, argues that “AI is shedding enlightenment values.” As someone who has taught writing at a similarly prestigious university, and as someone who has written about technology for the past 35 or so years, I had a deep response. Bell’s is not the argument […]| Radar
The agentic AI landscape is exploding. Every new framework, demo, and announcement promises to let your AI assistant book flights, query databases, and manage calendars. This rapid advancement of capabilities is thrilling for users, but for the architects and engineers building these systems, it poses a fundamental question: When should a new capability be a […]| Radar
A common misconception about O’Reilly is that we cater only to the deeply technical learner. While we’re proud of our deep roots in the tech community, the breadth of our offerings, both in books and on our learning platform, has always aimed to reach a broader audience of tech-adjacent and tech-curious people who want to […]| Radar
This article originally appeared on Medium. Tim O’Brien has given us permission to repost here on Radar. When you’re working with AI tools like Cursor or GitHub Copilot, the real power isn’t just having access to different models—it’s knowing when to use them. Some jobs are OK with Auto. Others need a stronger model. And […]| Radar
Teaching developers to work effectively with AI means building habits that keep critical thinking active while leveraging AI’s speed. But teaching these habits isn’t straightforward. Instructors and team leads often find themselves needing to guide developers through challenges in ways that build confidence rather than short-circuit their growth. (See “The Cognitive Shortcut Paradox.”) There are […]| Radar
This month we have two more protocols to learn. Google has announced the Agent Payments Protocol (AP2), which is intended to help agents to engage in ecommerce—it’s largely concerned with authenticating and authorizing parties making a transaction. And the Agent Client Protocol (ACP) is concerned with communications between code editors and coding agents. When implemented, […]| Radar
From Autocomplete to Agents: Analyzing 90 Tools from Industry and Academia| O’Reilly Media
On April 22, 2022, I received an out-of-the-blue text from Sam Altman inquiring about the possibility of training GPT-4 on O’Reilly books. We had a call a few days later to discuss the possibility.| O’Reilly Media
In this episode, Ben Lorica and Anthropic interpretability researcher Emmanuel Ameisen get into the work Emmanuel’s team has been doing to better understand how LLMs like Claude work. Listen in to find out what they’ve uncovered by taking a microscopic look at how LLMs function—and just how far the analogy to the human brain holds. […]| Radar
This article is part of a series on the Sens-AI Framework—practical habits for learning and coding with AI. AI gives novice developers the ability to skip the slow, messy parts of learning. For experienced developers, that can mean getting to a working solution faster. Developers early in their learning path, however, face what I call […]| Radar
This is the first of a three-part series by Markus Eisele. Stay tuned for the follow-up posts. AI is everywhere right now. Every conference, keynote, and internal meeting has someone showing a prototype powered by a large language model. It looks impressive. You ask a question, and the system answers in natural language. But if […]| Radar
When I was eight years old, I watched a mountaineering documentary while waiting for the cricket match to start. I remember being incredibly frustrated watching these climbers inch their way up a massive rock face, stopping every few feet to hammer what looked like giant nails into the mountain. “Why don’t they just climb faster?” […]| Radar
The productivity gains from AI tools are undeniable. Development teams are shipping faster, marketing campaigns are launching quicker, and deliverables are more polished than ever. But if you’re a technology leader watching these efficiency improvements, you might want to ask yourself a harder question: Are we building a more capable organization, or are we unintentionally […]| Radar
Mapping Power, Concentration, and Usage in the Emerging AI Developer Ecosystem| O’Reilly Media
What the Computerization of Wall Street Can Teach Us About AI| O’Reilly Media
For most people, the face of AI is a chat window. You type a prompt, the AI responds, and the cycle repeats. This conversational model—popularized by tools| O’Reilly Media
Everyone’s talking about microservices. Who’s actually doing it?| O’Reilly Media
There’s a lot of chatter in the media that software developers will soon lose their jobs to AI. I don’t buy it.| O’Reilly Media
What O'Reilly Learning Platform Usage Tells Us About Where the Industry Is Headed| O’Reilly Media
Developments in Security, Programming, AI, and More| O’Reilly Media
To hear directly from the authors on this topic, sign up for the upcoming virtual event on June 20th, and learn more from the Generative AI Success Stories Superstream on June 12th.| O’Reilly Media
The Replacement of Organic Search with Advertising by Google and Amazon and What That Might Mean for the Future of AI| O’Reilly Media
Thoughts about the outcome of the NYT versus OpenAI copyright lawsuit| O’Reilly Media
Generative AI has been the biggest technology story of 2023. Almost everybody’s played with ChatGPT, Stable Diffusion, GitHub Copilot, or Midjourney. A few have even tried out Bard or Claude, or run LLaMA1 on their laptop. And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. In enterprises, we’ve seen everything from wholesale adoption to policies that se...| O’Reilly Media
In December 2021 and January 2022, we asked recipients of our Data and AI Newsletters to participate in our annual survey on AI adoption. We were particularly interested in what, if anything, has changed since last year. Are companies farther along in AI adoption? Do they have working applications in production? Are they using tools like AutoML to generate models, and other tools to streamline AI deployment? We also wanted to get a sense of where AI is headed. The hype has clearly moved o...| O’Reilly Media