Critical Apache HTTP/2 flaw under WordPress sites

Google's new model (Gemini Decision 1) doesn't write text; it gives probabilities for predefined questions: yes/no, multiple choice (2–255 options) or rubric scoring. In one request it evaluates up to 1,000 questions on the same multimodal input (text, image, PDF, audio, video), in 150–250 ms. Every answer comes with a confidence score, so uncertain cases can be passed to a stronger model. ❓ The sources conflict on price: Google's blog says $0.10 per 1M input tokens, while TLDR wrote "$0.10 per 2M tokens". Output is free. The page says nothing about EU availability.

OpenRouter measured that the same GitHub task on Sonnet 5.5 cost 1,421 tokens with the gh command-line tool (CLI), 3,315 with a skill, and 59,417 with the GitHub MCP server's 46 default tools. The reason: every tool's description is sent to the model again with every request. Tool Search (deferred loading of tools) roughly halved the cost on Claude, with mixed results on other models. Their recommendation: use a CLI where one exists; with MCP, load only the tools you need, and trim large tool responses (requesting only the needed fields).

AI often answers a slightly different question than the one asked: it calculates net instead of gross, or counts only active employees instead of all of them. The Neuron's method: (1) have the AI list every definition and assumption it used; (2) compare that with the wording of the request; (3) in a new chat, give only the request and this list, with this prompt: "Below are my original request and the definitions and assumptions an assistant used. List where a definition is narrower, broader or different from my wording, and for each, describe how the result would change with my original wording."

A list of typical LLM phrasings is going around. Examples: openings of the "not X, but Y" kind, announcing "this is crucial" instead of showing what the thing does, punchy closing lines, lists of three out of habit, and "happy to elaborate" at the end. The list comes from the "declauding" skill in oaustegard/claude-skills: the skill rewrites the draft, and in a separate mode marks in HTML what it changed and why. In Claude.ai it can be uploaded as a ZIP under Settings / Skills.

Scammers use social media posts to write personalized phishing emails (spear phishing). In one case, a deepfake "CEO" and "lawyer" were used to extract $129M. Even small organizations should give staff a short warning: always verify urgent payment requests through a second, known channel. (Superhuman)

A free, open-source (Apache 2.0) research preview for Mac, Windows and servers. It tracks invoices, drafts replies, watches pages, and asks for approval before sending. It also works with local models (Ollama), but those need tool calling and a 64K context. The question: how far can you trust an experimental tool with access to your email and calendar? It could run on an always-on home machine. (Superhuman, The Neuron · nod.n8n.io/)

Intruders at the Railway cloud host stole environment variables, mainly AI provider keys, and used them to run up charges. Grok Build's 35,000 public apps also exposed confidential data. Lesson: put a monthly spending cap on AI provider keys, and keep them out of public repositories and code. (TLDR InfoSec)

Microsoft researchers showed that by rewriting a few rarely used neurons in an open-weight model, a hidden command can be planted that activates on a trigger phrase. When running a model locally, download it only from official sources. (TLDR InfoSec, TLDR IT)