WordPress 7.0 APIs and why the release slipped
Notes from the Dev Chat on WordPress 7.0: the AI Client and Connectors API, why the release cycle got extended, the left navigation rethink, and the argument over YouTube support in the Cover block.
Author: Ahmad Wael
I'm a WordPress and WooCommerce developer with 15+ years of experience building custom e-commerce solutions and plugins. I specialize in PHP development, following WordPress coding standards to deliver clean, maintainable code. Currently, I'm exploring AI and e-commerce by building multi-agent systems and SaaS products that integrate technologies like Google Gemini API with WordPress platforms, approaching every project with a commitment to performance, security, and exceptional user experience.
The WordPress admin menu is a junk drawer, and Core knows it
Any plugin can claim a top-level spot in the WordPress admin menu, so after 40 installs the sidebar is a junk drawer. A Core proposal wants hierarchy and pinning. Here is what I use in the meantime.
Why design principles for products keep projects from drifting
Products drift when nobody writes down what they stand for. How Dieter Rams’ principles helped me kill an upsell on a WooCommerce checkout, plus the workshop and the CSS variables I use to keep principles in the code.
What WordPress Core AI in 7.0 means for plugin developers
WordPress 7.0 brings AI into core through the AI Client and the Abilities API. Here is what wp_ai_client_prompt() actually does, how to test it now, and what the Core AI team will work on during Contributor Day at WordCamp Asia 2026 in Mumbai.
CSS shape function: wavy and blob shapes without SVG
The CSS shape function replaces the SVG and clip-path hacks used for wavy dividers and blob shapes. How the curve commands and control points work, and why a fixed command count is what lets the browser animate between two shapes.
Jetpack Social upgrade: per-platform captions in Jetpack 15.6
Jetpack 15.6 lets you set the message and image per network instead of pushing one caption everywhere. Notes on the rebuilt preview modal, the sharing activity log, and the publicize filter that keeps certain post types off social.
DenseNet architecture: why it concatenates instead of summing
DenseNet connects every layer to every later layer and stacks channels instead of summing them the way ResNet does. Why that helps with vanishing gradients, how bottleneck blocks and transition layers keep the tensors in check, and where the memory cost shows up in PyTorch.
Safe AI system design and the inversion error problem
Frontier models stack a huge symbolic layer on an absent physical base, what Peter Zakrzewski calls the inversion error. The case for an enactive floor and for treating state-space reversibility as a hard constraint instead of an alignment patch.
Quantum data encoding and where hybrid QML models fall apart
Most QML writeups skip past encoding. This one goes through basis, angle and amplitude encoding plus feature maps, and what each one costs you in qubits or circuit depth on current hardware.
Explainable AI in production when SHAP is too slow
SHAP adds roughly 30ms to every prediction, which is fine offline and useless in a live request. Here is the neuro-symbolic alternative I benchmarked at 0.89ms, plus the weight collapse problem you run into on the way there.