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O'Reilly Radar — AI/ML

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When Context Collapses: Teaching Agents to Detect and Recover from Lost Memory

When Context Collapses: Teaching Agents to Detect and Recover from Lost Memory

This is the eighth article in a series on agentic engineering and AI-driven development. Read part one here, part two here, part three here, part four here, part five here, part six here, and part seven here. “640K ought to be enough for anybody.”—Bill Gates (allegedly) If you’re building AI agents that do complex, multistep work, you’re going to run into context […]

O'Reilly Radar — AI/ML
The PM’s Playbook for Shipping AI Features That Actually Work in Production

The PM’s Playbook for Shipping AI Features That Actually Work in Production

The demo to production Death Valley If you’ve worked on an AI feature, you know the feeling. You start building something that you are excited about, set launch timelines. The model spits out a perfect response, the prototype works magically, and everybody in the room is mentally calculating how big this product will be when […]

O'Reilly Radar — AI/ML
Long-Running Agents

Long-Running Agents

The following article originally appeared on Addy Osmani’s blog and is being reposted here with the author’s permission. A long-running AI agent can keep making progress over hours, days, or weeks. It can do this across many context windows and sandboxes, recover from failure, leave structured artifacts behind, and resume where it left off. For […]

O'Reilly Radar — AI/ML
The Tidy House

The Tidy House

DJ Patil has spent the past several months on a listening tour. Wherever he travels, he finds a local university, pings faculty and students and anyone else who wants to show up, and runs an AMA. He’s heard from grad students who can’t get callbacks, hospital administrators dealing with federal policy changes that land like […]

O'Reilly Radar — AI/ML
Predict, Don’t Enumerate

Predict, Don’t Enumerate

A third of the way into a security-operations guide that Anthropic published in April 2026, wedged between a recommendation to patch CISA’s Known Exploited Vulnerabilities list and a suggestion to automate your deployment pipeline is a small recommendation: “Use EPSS to prioritize the rest.” For anyone who has worked on a vulnerability backlog in the […]

O'Reilly Radar — AI/ML
Context as Code

Context as Code

As syntax becomes cheap and abundant, architectural control becomes the scarce resource. Effective governance starts upstream, where intent, constraints, and threat models shape the agent’s working context before generation begins. The goal isn’t better prompting but build-time boundaries that prevent structurally invalid code from entering the system. The Frankenstein factories The dark factories (as Dan […]

O'Reilly Radar — AI/ML
AI Sovereignty and the Architecture of Participation

AI Sovereignty and the Architecture of Participation

Adam Tooze recently shared a piece from The Economist about Brazil’s push for what it calls “medical sovereignty,” the determination to make its own vaccines and the active ingredients that go into its medicines rather than depend on supply chains it doesn’t control. Brazil already produces a large share of its own medicines through public […]

O'Reilly Radar — AI/ML
SaaS Is Not Dead Yet

SaaS Is Not Dead Yet

With the rise of agents, many people have been proclaiming that the age of software as a service (SaaS) is over. Who needs to subscribe to a service when you can create your own software with a few English-language prompts and a few dollars spent on tokens? Your own software, most likely a skill that […]

O'Reilly Radar — AI/ML
Open Source Ecosystems

Open Source Ecosystems

The following article originally appeared on the Asimov’s Addendum Substack and is being reposted here with the author’s permission. Bill Gurley has an excellent article on what he calls open source strategy, which we recommend reading. There is a lot to debate about his concluding argument in particular: that open-weight models are central to keeping the AI market […]

O'Reilly Radar — AI/ML
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