Prompting stops scaling after a few sessions. Here is how agent skills put your recurring logic into a SKILL.md file instead, with a weekly visualization example and the directory layout I use.
Cowork gets written off as Claude Code for people who don’t code. I use it for architecture work and multi-file debugging, and this is how I keep the context window lean, why I stay in plan mode, and which repeat jobs I turned into skills.
The 512-token split is the default in every RAG tutorial, and it quietly ruins answers on real documents. What I use instead: sentence windows, hierarchical chunking, layout-aware table parsing, and RAGAS to check whether any of it worked.
One working directory holds one state of the project, which is why you and your agent keep colliding. Git worktrees give each branch its own folder, and here is the script that pays the setup tax: env files, installs and a unique port offset.
Notes from WordCamp Asia 2026 in Mumbai, written for developers: the Interactivity API replacing fragile jQuery toggles, the Tag Processor in the HTML API, and what WordCamp India 2027 and the 7.0 roadmap mean for the code you ship.
A 2026 roadmap for learning Python for data science without the tutorial detours: which fundamentals actually matter, the three libraries you will live in, and how much time to give data structures before interviews.
A p-value is closer to a weirdness score than a probability that you are right. Here is how to read one, why the 0.05 threshold is arbitrary, and how to sanity-check sample size before you act on an A/B test.
MareNostrum V is 8,000 nodes sitting in a Barcelona chapel, and getting code to run on it means SLURM time slots, airgapped storage and Amdahl’s Law. Here is what that setup teaches about scaling anything smaller.
WooCommerce 10.7 drops HPOS order REST queries from 271 to 132, ships a beta Order Fulfillments API with typed methods, caches the Store API Last-Modified timestamp, and stops sanitization from eating % signs in gateway passwords.
Vector databases have become the default answer for AI agent memory, and for a project-scoped agent they are usually the wrong one. Plain Markdown files plus a local SQLite index give you grep, git diff and no server to babysit.