Prompt caching only pays off when the prefix stays byte-identical. I go through the mistakes that break it, a semantic cache layer for WordPress, loading tool definitions on demand, and what to keep or drop between turns.
Notes on serving high-resolution desktop wallpapers from WordPress without wrecking load times: what sub-size generation costs you, why lazy loading hurts a hero image, and where a CDN belongs.
Two graphs moving together is not proof one caused the other. A PHP helper for Pearson r, the nonlinear cases a correlation check misses, and the hidden variables that make a new theme look guilty.
set_detect_anomaly points at the wrong layer and costs you 10x on CPU. A forward hook adds roughly 3ms per pass, names the layer that produced the NaN, and pairs with a gradient norm check that fires a step earlier.
The ::nth-letter selector still is not in any browser, and hand-wrapping every character in a span wrecks the DOM. A shim that rewrites the raw CSS into :nth-child and lets SplitText handle the markup and the ARIA.
Calculation groups look tidy in the model, then rename every series in your legend to the same thing. Where explicit measures in tabular models hold up better, including the Excel PivotTable case that cost me three days.
justify-self aligns one element along the inline axis and overrides the justify-items value its parent set. This covers how it behaves in grid, in block layouts, and on absolutely positioned items, plus the inset rule that trips people up.
Analysts waiting three weeks on an engineer for one metric is a tooling problem. Here is the dlt, dbt and Trino setup we used to move pipeline building into YAML and SQL, what it cost, and where it still falls short.
Version 0.7.0 of the experimental AI plugin adds content classification, bulk alt text generation, and hooks for changing system instructions before results are saved. Here is what holds up, what to watch on a slow host, and what 0.8.0 has queued.
Row-wise iteration is what makes most Pandas code slow. This walks through profiling with %timeit and memory_usage, replacing iterrows with vectorized operations, cutting memory with category types, and when to move to Polars or DuckDB instead.