Coté

If you’re wondering how cold fusion produces pollution, let alone a lot of it, don’t worry, this is explained in a chapter by one teenaged prodigy tennis player to another, wherein the latter is wearing a blindfold to improve his other senses but can’t find a bathroom, so he asks the other player for help, but instead, the other player explains cold fusion in exhaustive detail over such a long period of time that the blindfolded player is nearly peeing in his pants, and it all turns out to be a ploy by the explainer to pressure the blindfolded player (who is a Muslim and drug-free) to give away his urine so the other player and his friends can pass a drug test. Stuff like this happens a lot in IJ. Infinite Jest Extraction

Using AI to help with SRE, ops, etc.:

The problem, he said, is that Claude “will get wrong correlation versus causation.” It’s like a new joiner on the team, they will think “oh, it’s a capacity problem, when actually you lost your cache.” “This is why we can’t trust LLMs for incident response,” said Palcuie. The problem is its inability to “step back and start discerning between causation and correlation… For us humans, it is hard as well.”

And:

The Jevons Paradox, said Palcuie, is “the favorite paradox in the AI industry. It’s when technological improvements increase the efficiency of our resources used, but the resulting lower cost causes consumption to rise rather than fall.”

In the case of software, “it’s easier to write software, so we write much more of it, so the complexity goes up and not down, which means things break in more interesting ways, which means more incidents, more on call… all the improvements in the tooling will be cancelled by this ever-growing complexity.”

From: Fixing Claude with Claude: Anthropic reports on AI site reliability engineering

Using AI for security log analysis and how to fix it suggestions:

Building on that foundation, leading the list of announcements is a strategy described as an “agentic security operations center” powered by its latest Gemini AI models. Google is introducing adaptive AI agents that can investigate alerts, synthesize intelligence and assist in remediation workflows in real time, which replace the need to rely on static playbooks.

The new Triage and Investigation agent is designed to autonomously analyze alerts, gather supporting evidence and deliver reasoned verdicts to help security teams reduce response times and cut through growing volumes of false positives. The new agent is now available in preview within Google Security Operations.

Google is also extending its agentic approach by allowing customers to build their own enterprise-ready security agents through support for Model Context Protocol servers. The capability removes the need for organizations to host their own MCP client infrastructure to deliver unified governance and control over custom agents, with general availability expected in early April.

From: Google Cloud unveils agentic AI security strategy with Wiz integration and threat intelligence upgrades