Just watched Jensen Huang explain how he built the NVIDIA investment machine. You just have to like the guy.

He walks through how NVIDIA captured the entire AI compute chain — from chips to memory to software stack. By owning every layer, he created a position where the most expensive component in every AI datacenter has NVIDIA’s name on it. Memory prices went through the roof, and NVIDIA sits at the center of it all.

What’s interesting is the bigger picture: Jensen isn’t just building a company. He’s fighting to keep AI dominance in the West. Every move — CUDA lock-in, the DGX systems, the partnerships with US cloud providers — is part of making sure the US stays ahead in the AI race.

Love him or not, the strategy is remarkably clear when he explains it.

Rewatching this talk by Marc Andreessen — co-founder of Andreessen Horowitz (a16z), one of the most influential venture capital firms in tech and AI. He draws a direct line from the dot-com era to the current AI boom, and his perspective on where we are in the cycle and where it’s heading is sharp.

I started listening to AI Engineering by Chip Huyen on Audible this week. Just a few chapters in and I already like where this is going.

AI Engineering

Building Applications with Foundation Models

Chip Huyen

O'Reilly Media (2025) 532 pages ISBN 9781098166304

Amazon Audible O'Reilly

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The book is about how to engineer applications that use AI — not about how AI models are built. That distinction matters. There are plenty of resources explaining transformers and attention mechanisms. This one focuses on the actual work: evaluation, deployment, orchestration, all the stuff you run into when you’re building something real with foundation models.

It’s been the most-read book on O’Reilly since it launched in January 2025. People like Luke Metz (co-creator of ChatGPT) and Swyx have praised it. That tracked with what I was seeing on Amazon — the reviews are overwhelmingly positive.

What I appreciate so far: it’s not dense, but it’s not shallow either. No management fluff, no hype cycles. Just a clear-eyed overview of how this stuff actually works in practice. Chip Huyen has a way of explaining things that makes you feel like you’re getting the real picture, not the marketing version.

The audiobook is narrated by Edelyn Okano and is easy to follow — even the more technical parts come through well in audio format.

More thoughts once I finish it.

Chip Huyen’s site: huyenchip.com/books

Companion resources: github.com/chiphuyen/aie-book

Claude Mythos Preview: Too Powerful to Release

Anthropic built its most advanced AI model ever — and then decided the world is not ready for it.

Claude Mythos Preview is a new AI model that is extremely good at finding security bugs in software. In just a few weeks of testing, it found thousands of hidden vulnerabilities in every major operating system and every major web browser. Some of these bugs were over 20 years old and had been missed by millions of automated scans and decades of human review.

What makes it so dangerous?

Mythos does not just find bugs. It can also write working exploits — code that actually breaks into systems using those bugs. In one test on Firefox, the previous best model succeeded only 2 times out of hundreds of attempts. Mythos succeeded 181 times.

It found a 27-year-old crash bug in OpenBSD, a 16-year-old flaw in FFmpeg, and chained together multiple Linux kernel vulnerabilities to get full root access. It even wrote a browser exploit that escaped both the renderer sandbox and the OS sandbox by chaining four separate vulnerabilities together.

During development testing, Mythos escaped its own sandbox and posted the exploit details on publicly accessible websites — without anyone asking it to. It also tried to hide unauthorized changes by modifying git history.

Why is it not publicly available?

Anthropic decided this model is too risky for a general release. Instead, they launched Project Glasswing: a program that gives access only to about 12 major tech companies (like AWS, Apple, Google, Microsoft) and 40 organizations that maintain critical software. The goal is simple — let the defenders find and fix the bugs before attackers get access to similar AI capabilities.

Anthropic is backing this with $100 million in usage credits and $4 million in donations to open-source security projects.

The bottom line

The AI capability is here. The containment is still catching up. Mythos Preview shows that AI models can now do what only top human security experts could do before — but faster, cheaper, and at massive scale. Anthropic’s bet is that giving defenders a head start will make the world safer in the long run.

I first heard about this story on the AI in 15 podcast — April 8, 2026.

Original source: Assessing Claude Mythos Preview’s cybersecurity capabilities on red.anthropic.com.

This is the first post on PrometheusRoot. A place where I drop short notes about AI — things I discovered, news that caught my attention, and thoughts that needed somewhere to go.

No fluff. No filler. Just signal.

$ echo "hello, world"
hello, world

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