Scoring models that look great on one training set often break in production. These are the four filter rules I run across stratified folds so variable selection survives data the model has never seen.
Anthropic’s subscription ban pushed me off Claude for OpenClaw. Here is the OpenRouter setup I use with Kimi-K2.5, what it costs, where it runs slower, and the GDPR problem with hosted weights.
Automating every quick question makes tasks faster and teams weaker. What the research on informal communication and AI burnout shows, plus three ways to put useful friction back into the workflow.
Version 0.8.0 of the WordPress AI plugin moves image generation out of experiments, adds a Refine from Notes experiment that applies editorial notes for you, and ships the first AI dashboard widgets.
Part 2 on summarizing a 200,000-word handbook: validating K-means clusters with UMAP and silhouette scores, picking the chunk nearest each centroid, and where the final reduce step still drops topics.
Levenshtein and Soundex break the moment a query crosses script boundaries. Notes from a sanctions screening build on byte-level transformer embeddings, ANCE hard negative mining, and where CJK still causes trouble.
Regex and K-means both fall apart on short free-text data where the same idea gets phrased three different ways. Zero-shot classification with a local model like Gemma 2 handles the paraphrasing, and this is the Ollama pipeline I ran over several thousand security annotations.
Tabular RL breaks the moment the state space grows past a toy grid. Approximate Solution Methods swap the lookup table for a weight vector and semi-gradient updates, so one state teaches you about every state like it. Includes where linear models still beat a neural net.
Twenty-three pipeline failures in six weeks, none of them caused by my code. This is how I replaced GPT-4 with a seeded Qwen2.5 on Ollama, plus the GitHub Actions caching and Pydantic validation details that made it stick.
A logistics director with all-green KPIs and 18% late shipments does not have a data problem. Scoped AI agents watching the TMS can tell you which handoff actually broke, and tell you on the morning it happens.