A general guide to matching messy records into governed entities, with blocking, scoring, selective review, clustering, survivorship, and evidence-first reference tables.

Most teams already have the raw material for a context layer in Drive, Slack, and scattered transcripts; the hard part is turning that sprawl into a shared record that people and agents can use without rebuilding the history each time.

Google’s new TurboQuant method compresses key-value cache and search vectors more aggressively by cutting quantization overhead, which could make long-context inference and retrieval cheaper and faster.

Hardware, model compression, frontier benchmarks, and pricing all point to the same outcome: local AI becomes the default for ordinary work, while cloud models remain the escalation path for the hardest tasks.

A file-level benchmark comparing PDF and Markdown on storage, prep speed, and token estimates, including an image-bearing Grimm fairy tales PDF.

Turn a text PDF into lean Markdown that saves tokens and fits a personal context layer.

A practical framework for using folders, Markdown, per-project agent contracts, and Obsidian as a durable local context layer.

AI work is moving out of the chat box and back into project folders, because files are the simplest durable context layer for coworker-style tools.

Generate a kickoff prompt for a new Claude or Codex local context layer.