Gutenberg is experimenting with content guidelines: a machine-readable home in the admin for voice, tone and structural rules, so authors and AI assistants work from the same standards instead of a PDF nobody opens.
Most WooCommerce stores buy clicks and hope. Expected value modeling puts a number on it: profit per sale, cost per click and purchase probability decide whether a customer is worth targeting, plus a small PHP helper to run the check.
Mechanistic interpretability is the Xdebug of AI research: hook a forward pass, zero out a neuron, and see what the model was actually doing. A walk through the residual stream, TransformerLens, circuit tracing and steering vectors.
Agentic analytics moves the consultant’s job from writing queries to architecting the systems agents read from. What that looks like in practice, including a clean WordPress REST endpoint built for agent consumption.
How I set up Claude Code context: local docs and meeting transcripts in a /knowledge folder, a .claudignore that keeps the agent away from secrets, and a bash script that bundles only the files a given feature needs.
Voyager 1 still self-corrects on 69.63KB of memory. That comparison is the frame for quantization, knowledge distillation and TinyML, plus a small PHP example of how weight quantization actually works.
WordPress 7.0 makes the post editor always iframed, which breaks editor JavaScript that reaches for the global document. Also here: native viewport-based block visibility, per-instance custom CSS, and the Studio 1.7.0 CLI updates.
The giant catch-all prompt is fine in a prototype and falls apart in production. The Google Interactions API keeps state on Google’s side, which is what lets you poll a long research job from WP-Cron instead of hanging the page.
Andrew Adetitun had more than 160,000 followers and no platform of his own. He is a former WordPress developer, and he still used the AI website builder to get The King’s Monologue online fast, then pointed it at his Kickstarter book.
A look at what the YOLOv2 paper actually changed from v1: batch normalization, high-resolution fine-tuning, K-means anchor boxes and the passthrough layer, with PyTorch code for the Darknet-19 blocks.