Moving from a single AI agent to a multi-agent system pays off once workflows get complex. This covers the ReAct loop, specialized roles like retriever, writer, and verifier, and when to drop the monolithic prompt to cut hallucinations.
How I stopped re-explaining my projects to Claude every session. I keep a persistent knowledge base built from CLAUDE.md rules and a custom skill, and a nightly cron job keeps it current.
Manual performance tuning is mostly hypothesis and hope. Agentic loops like pi-autoresearch take a metric and a budget, run the experiments themselves, and keep only the versions that measure better.
Discover how to enhance your website’s search engine performance using the power of schema markup. This comprehensive guide covers everything from basic microdata to advanced JSON-LD implementations. Learn why search engines love structured data and how you can use it to gain a competitive edge in search results starting right now for your business.
RAG re-derives everything on every query, so nothing accumulates. This is the Raw and Wiki folder layout, the three control files, and the daily, weekly and monthly jobs I use to keep an AI context layer my agents can read.
WordPress.com opened the AI Assistant to every paid plan and shipped Studio Code, a beta CLI agent for local work. Notes on what the CLI does with block markup and what the plan change means day to day.
The WooCommerce REST API documentation left its 4.2MB single-page site for per-endpoint files on developer.woocommerce.com. What that changes for coding assistants, raw markdown fetches, and doc updates that ship inside the PR.
Vision models and language models look like separate brains, but as they scale their internal structures line up. A look at the Platonic Representation Hypothesis, the pressures behind convergence, and what it means for the data assets you build.
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.
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.