Overnight batch syncs stop working the moment an AI feature depends on the data. Five steps toward a real-time data pipeline: pick the high-impact flows first, read the binlog with change data capture, and keep the old job running until the numbers agree.
Hiring for hyper-depth became the default advice for WordPress teams, and it makes messy stacks harder to fix. My case for range, what generalists catch that specialists walk past, and how much of the specialist layer AI already covers.
Notes from the latest WordPress AI contributor meeting: the MCP client is becoming a normal plugin instead of a Composer package, the Abilities API is getting real exception handling, and AI agents are getting a proper block dictionary.
In a 200-task benchmark, nearly 91% of ReAct agent retries were spent on errors that could never succeed. The three fixes I use: an error taxonomy, per-tool circuit breakers, and tool routing that stays in code.
Churn is not a yes or no question, it is a question of when. This covers censored data, Kaplan-Meier curves, and Cox hazard ratios in Python with the lifelines library.
Claude Code is not only for refactoring PHP. Three things I run through it that never touch a codebase: LaTeX decks kept in Git, cross-app search over Slack and Notion, and prospect research.
Woo ran a Bug Blitz: support engineers with Claude Code and Copilot shipped over 170 fixes across 20 products, every line reviewed by quality engineers. Why it worked and what to copy.
LLMs forget your stack the moment you close the tab. Here is what actually sticks: a project rules file in the repo, global rules for your own preferences, and MCP when the assistant needs data from outside the codebase.
Most Pandas code I inherit is a trail of df_filtered, df_2 and final_df_v2. Method chaining with assign() and pipe() turns that into one pipeline you can read from top to bottom.
A GPU at 10% while every CPU core is pinned at 100% is a data loading problem, not a hardware problem. What I change first in a PyTorch pipeline: DataLoader workers, pin_memory, mixed precision and torch.compile.