O'Reilly Radar - AI as an Enterprise Operating System

O'Reilly Radar - 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. 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.

oreilly.com
u/OReilly_Learning — 17 days ago
▲ 4 r/YugabyteDB+1 crossposts

Free O'Reilly Report: Why Distributed SQL Is the Modern Foundation for AI

AI in pilot and AI in production are completely different. Traffic is unpredictable, data is scattered across separate systems, and things that worked fine in testing start to break under real concurrency and scale. 📉

Our new O'Reilly report, 'Why Distributed SQL Is the Modern Foundation for AI,' breaks down the architectural decisions required to keep AI systems consistent and scalable once they're live.

https://info.yugabyte.com/report-why-distributed-sql-is-the-modern-foundation-for-ai-oreilly

Walk away with an action plan for keeping transactional data, vector embeddings, and unstructured content working from one consistent, current source of truth.💡

Download your complimentary copy today! 🙌

u/OReilly_Learning — 23 days ago
▲ 44 r/OReilly_Learning+1 crossposts

Your MCP servers can reach every domain on the internet over 443. NetworkPolicy can't fix that. Wrote up why, and what can [O'Reilly]

I wrote a piece for O'Reilly Radar about the agent failure that never makes the post-mortem, because nothing visibly fails: https://www.oreilly.com/radar/prompt-injection-to-data-exfil-in-3-hops/

Disclosure up front: I work at Aviatrix, which sells one of the products in the category the article describes. The piece is deliberately layer-neutral: Cilium FQDN policy, service meshes, and cloud-native firewalls all enforce the same control, and the article covers this. The argument is about the category, not any product.

The chain is three hops of everything working as designed. Prompt injection hidden in a support ticket -> legitimate MCP tool call -> HTTPS egress to an attacker domain: no CVE, no stolen token, no compromised process. The agent did exactly what it was permitted to do.

Why NetworkPolicy doesn't help: it operates at L3/L4 and cannot tell api.github.com from attacker.example.com when both resolve into the same rotating CDN range. Allow 0.0.0.0/0 on 443, and the agent reaches everything. Deny it and the agent cannot reach its own model API.

The CIDR allowlist most teams settle on is the worst of both: it holds the legitimate API, plus every other tenant of that CDN, including the attacker. A firewall rule that permits both your API and your adversary is not a security boundary. It's a formality.

Guardrail models don't rescue this either. One that catches 95% of injections still loses, because the attacker controls the input, retries for free, and needs only one success against an action that cannot be undone. Answering a probabilistic attack with a probabilistic defense is like teaching a guard dog not to eat steak.

What works: deterministic egress containment. Per-pod identity, domain-aware policy read from SNI, default-deny on everything undeclared. What this does not close: exfil via permitted destinations, and DNS tunneling. What it does is shrink the reachable set to the handful of domains you declared, and force attackers onto slow, noisy channels you can actually watch.

The questions for you:
For every MCP server in your cluster, can you name the external domains it must reach and must never reach?
Has anyone shipped default-deny FQDN egress for agent workloads, and what broke first?

u/OReilly_Learning — 1 month ago

O'Reilly Radar - Ordinary Engineers, Not Heroic Inventors

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

oreilly.com
u/OReilly_Learning — 1 month ago

O'Reilly Radar - Guidelines for Respectful Use of AI

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.

oreilly.com
u/OReilly_Learning — 2 months ago

O'Reilly Radar - I Let an AI Agent Run 40 Experiments While I Slept

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

oreilly.com
u/OReilly_Learning — 2 months ago
▲ 372 r/OReilly_Learning+1 crossposts

Learning Go, 3rd Edition is in Early Release

I'm excited to announce that the 3rd edition of "Learning Go" is now available in Early Release!

The full book is scheduled for 2027. This edition is updated to cover the most recent Go releases. It also adds:

  • More code review advice
  • New exercises
  • A brand-new chapter on monitoring and observability

If you have an O'Reilly Online subscription, you can read the preface and the first two revised chapters now: https://learning.oreilly.com/library/view/learning-go-3rd/0642572348533/

#golang #programming #softwareengineering

u/JBodner — 3 months ago
▲ 970 r/OReilly_Learning+1 crossposts

what's a script you wrote once that's still saving you time years later

i wrote a powershell script like 3 years ago that checks AD for disabled accounts that still have active mailboxes and spits out a csv every monday morning. took me maybe an hour to write. it's caught orphaned mailboxes so many times since then that i stopped counting. the licensing cost it's saved us is probably more than my raise last year.

the other one is a bash script on our linux boxes that monitors disk usage and sends a slack alert when anything hits 85%. nothing fancy, just df piped through awk with a curl to the slack webhook. wrote it after we had a production outage because /var/log filled up and nobody noticed. that was a fun 2am call.

what's your version of this? the one script that keeps quietly doing its job in the background.

reddit.com
u/Less-Loss1605 — 3 months ago