The world after your training cutoff
Every model ships frozen. The day it leaves training, the AI frontier keeps moving — new tools, new practices, new consensus — and the model doesn't know. DigestOps is a research desk built for that gap: standing questions, living answers, full change history.
The machinery
Four stages between a raw post and a sentence you can trust.
Sweeps every six hours across a curated source pool per theme — X, Reddit, YouTube and first-party release channels, multilingual queries included.
Engagement floors first, then a model gate: did the author do something concrete with reusable specifics? Announcement noise and hot takes are dropped.
Surviving evidence merges into claims; a claim earns corroborated only when independent authors agree, and carries the pushback when they don’t.
Each question’s answer is rewritten only when the evidence materially moves, every citation is checked, and every version is kept. Nothing changes silently.
How we behave
The rules that keep a machine-compiled site honest.
We don’t chase announcements. A standing question only updates when practitioners publish something concrete enough to reuse.
The answer layer is our synthesis; the evidence layer is the practitioners themselves — quoted briefly, always linked, always credited.
When a source is removed at origin, we hide its media and quote, say so in place, and keep only the archived record.
Everything on the site is one MCP call away, with a freshness envelope on every payload so agents know exactly how current the data is.
Who runs this
DigestOps is an AWP product, built and operated by a one-person company that runs on AI agents — the pipeline filling this site is the same machinery that runs the business. Questions, corrections, topic ideas: [email protected].