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Principal Drift in Practice

In 2026, the software engineering community is divided by a simple question: Should AI engineers still read the code generated by their agents? One camp argues that code has become virtually free to produce and discard, so humans should focus on systems and guardrails rather than implementation details. The other warns that blindly trusting AI […]
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When Your Buyer Is an AI Agent

In 2021, Maersk, the world’s largest container shipping company, deployed AI agents from a startup called Pactum to negotiate freight lane contracts with its carrier suppliers. The objective was for AI agents to handle negotiations autonomously rather than merely support human procurement staff. Operating entirely autonomously, the system manages the end-to-end agreement process, from reaching […]
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When Guardrails Go Wrong

The latest round of restrictions and safeguards for frontier models are overly fussy and limiting. A Claude skill that I created demonstrates what happens when guardrails go astray. My skill helps me to find articles and blog posts that go into O’Reilly Radar’s monthly Trends to Watch. It reads roughly a dozen well-known sites like […]
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Is Open-Source AI Really the Dangerous Path?

The following article originally appeared on the Tech Policy Press site and is being republished here with the author’s permission. In Washington, AI is increasingly being treated as something that needs to be controlled. The government believes that AI is, first and foremost, a national security asset, meaning that it must be sequestered to prevent […]
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What’s an Orchestrator—and Why Does Software Need One?

The following article originally appeared on Medium and is being republished here with the author’s permission. Everybody’s talking about the death of developers. I get it. The developer whose job was to write boilerplate or scaffold CRUD apps is done—a model can do that in seconds, and that developer is not coming back. But the […]
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When AI Writes the Code, Specifications Need an Exit Strategy

The following article has been extended and rewritten by Markus Eisele from The Main Thread and is being republished here with the author’s permission. Open a repository after six months of spec-driven agent work and you may find a second system sitting next to the code. Requirements, research notes, high-level designs, low-level designs, implementation plans, […]
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The Intent Debt

The following article originally appeared on Addy Osmani’s blog site and is being republished here with the author’s permission. Technical debt lives in your code. Cognitive debt lives in your head. Intent debt lives in the artifacts you may never have written: the goals, constraints, and rationale for why the system is the way it […]
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Prompt Debt and “Fighting the Weights”

Drew Breunig is one of the smartest voices writing about AI today. He’s the CEO and co-founder of cmpnd.ai, and a long-time hacker with a depth of experience from several eras, which is a surprisingly valuable asset these days. He’s also got a book on the way, The Context Engineering Handbook, already in early release […]
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The Two Pillars of Post-training: Reinforcement Learning and Supervised Fine-Tuning

This is the second article in Sharon Zhou’s post-training series. Read part 1 here. In the first post of this series, you learned how post-training closed the fundamental gap in usability of LLMs by making them behave in a certain way. In this post, you’ll explore specific techniques you can use to change a model’s […]
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A Home for Personal Context

Every agent I use is building a model of me. Claude has learned how I like my prose. ChatGPT remembers what I’m working on. I don’t mind this—every person I have a relationship with carries a model of me in their head, and every company I do business with keeps a profile. Other people’s understandings […]
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Why Open Source Matters for AI

In 1995, the question in the media was whether Netscape or Microsoft would control the web. The answer, it turned out, was neither. Both Netscape and Microsoft aimed to dominate the web server and browser market, reasoning that whoever controlled both ends of the connection would have an internet “platform” to rival the deathgrip that […]
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AI on the Pi: Build Your Own Local Voice Agent

As soon as I received my first Raspberry Pi, I knew that it would be a wonderful platform to bring AI into the physical world. Since the initial hardware didn’t have good CPU support for fast arithmetic, I ended up writing code that ran on the GPU so I could get the speed I needed […]
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Your AI Agent Isn’t a Static Artifact. It’s Growing Up.

In July 2025, an AI coding agent on Replit deleted a production database belonging to SaaStr founder Jason Lemkin. It did this during an explicit code freeze. Lemkin had told the agent, in capital letters, not to change anything. The agent ran destructive commands anyway, wiped records on more than a thousand executives and companies, […]
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Building Organizational Intelligence

Introduction Not long ago, one of my engineering directors came to me with a request: His team seemed overloaded, and he wanted to hire another engineer. I decided to test a research assistant I had been building—an AI agent connected to our internal systems via MCP—by asking it to analyze the team’s workload and write […]
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Introduction to Post-training

This is the first article in a series about post-training. Follow along on Radar. Before post-training, there was a major problem with LLMs: Almost nobody could use them. The story of post-training is also the story of how AI went from a research curiosity to a product used by about a billion people. Post-training is […]
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AI as an Enterprise Operating System

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. […]
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The Problem Is Prompt Debt

The following article was originally published on Drew Breunig’s blog and is being republished here with the author’s permission. Thanks to natural language interfaces, AI applications can be prototyped quickly. You write what you want in English, hand it to a frontier model, and a working prototype appears in an afternoon. This is extraordinarily powerful […]
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What the Hell Is a Loop, Anyway?

The following article originally appeared on LinkedIn and is being republished here with the author’s permission. We’re currently at the peak of the hype cycle. On June 7, Peter Steinberger posted that you shouldn’t be prompting coding agents anymore; you should be designing loops that prompt your agents. That same week, Boris Cherny of Anthropic […]
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