The Core-AI team shipped v0.1.0 of the WordPress PHP AI Client SDK. It is a provider-agnostic Composer package you bundle into your own plugin, so swapping the LLM behind a feature stops being a refactor.
Cursor turns a four-hour refactor into a 20-minute one, but only with a plan. My four steps: spot the trigger, write a plan.md, let Claude execute with test scripts, then compare the output against the original.
Six months in, WordPress Core AI has a stable shape: the Abilities API lands in 6.9, WP Client AI abstracts the LLM providers, and the MCP adapter turns a site into a server that agents can call.
Notes on porting statistical models into WordPress: where research gets diluted instead of distilled, how real-time aggregates in user meta leak data through race conditions, the atomic SQL fix, and why a bigger LLM is the wrong answer to arithmetic.
Rolling-window forecasts treat every SKU as independent. This post models a WooCommerce catalog as a graph instead, with GraphSAGE over shared plants and attributes, the PHP that extracts SKU neighbors, and where heterogeneous transformers go further.
WordPress now has WP-Bench, a benchmark that tests AI models on Core APIs, security patterns and block development. It runs the generated code in a real WordPress runtime instead of grading answers on paper.
Hardcoded API keys hold up until the first model deprecation. Here is how I use AWS Bedrock as the gateway instead: Boto3 calls, inference profiles, IAM permissions, and a triage assistant that runs on Lambda rather than inside the WordPress request cycle.
Longer context windows cost server memory, not just compute. Infini-attention replaces the growing KV cache with a fixed-size compressive memory matrix updated by a Delta Rule, which cut memory use by 114x in Google’s tests.
Prompting stops scaling as soon as a task has real edge cases. Here is what the Stanford ACE research found about its generator, reflector and curator loop, where the gains show up, where they do not, and how to keep the same kind of playbook in WordPress.
Vanilla vector search breaks down as soon as your data is relational. Notes on GraphRAG, enforcing a data contract on LLM output in PHP, and the production RAG lessons worth stealing from the Towards Data Science write-ups.