Dumping PDFs into a vector store is why RAG systems hallucinate and cost too much. This covers curating the source data, chunking by meaning, quantizing vectors, mixing BM25 with vector search through RRF, and testing retrieval with DeepEval.
Timer-XL makes the case that decoder-only Transformers beat encoders at forecasting. This looks at how TimeAttention keeps temporal order intact, why patch tokens cut the compute, and what the zero-shot numbers mean for real pipelines.
WooCommerce added a Subscriptions Health Check tool under Status. It finds subscriptions stuck on manual renewal after the HPOS cache bug, plus active subs with missing or overdue payment dates. Here is what caused it, and what the changelog left out.
MARL for logistics: RL picks the routing strategy, Linear Programming handles packing, and ratio-based observations let one agent run at a rural hub or a metro sorting center. Includes the sequential training loop that keeps agents stable.
WooCommerce for Claude came out of Automattic’s Radical Speed Month. It uses MCP to give the model analytics lookup tables, a store knowledge layer and an AI-readiness score, all on one endpoint. Plus the provider pattern and how to run it locally.
A “5x improvement” on its own tells you nothing. Three questions pull it apart: which dimension moved, from what baseline, and against which period. Examples from Core Web Vitals, model accuracy, and a transient cache bug that faked a 10x speed boost.
Claude Code gets more reliable when it can run its own output: unit tests through WP-CLI, parallel prompts compared against the goal, and Chrome screenshots over MCP for front-end work. Also why an agent looping with no check-in is worse than no loop.
WordCamp US 2026 runs August 16 to 19 in Phoenix, and the calls for speakers, sponsors, and volunteers are open. Speaker applications close May 29, 2026, and volunteer applications close June 15.
Google’s Prompt API is Chrome-only, downloads a 4GB Gemini Nano model without asking, and requires developers to acknowledge Google’s Generative AI Prohibited Uses Policy. My case against calling that a web standard.
AI coding tools copy whatever patterns already exist in a repo and know nothing about battery budgets or packet sizes. In IoT that combination turns into technical debt faster than a team can refactor it away.