method
how this was researched — parallel agent lanes, the evidence model, and how to correct it.
the lanes
the corpus was produced by four parallel agent research lanes — company history, the people and their writing, coverage and sentiment, and the media-house-ships-software idea — each writing a lane report against one shared scratch source catalog before synthesis. the pattern is the company-research formula proven on roam-research and obsidian: lane-prefixed source ids frozen upfront, per-claim confidence, and a declared deduplication owner.
the evidence rules
- every event, quote, and claim carries at least one source id.
- dates keep their precision — a year, a month, or a day — and approximate dates are labeled rather than sharpened.
- confidence stays honest: confirmed, reported, and inferred are distinct claims, not stages of the same claim.
- sources are typed by role — primary, interview, reporting, archive, community — so a claim's foundation is visible before it is read.
- sentiment labels describe the coverage, not the truth of it.
known gaps
- subscriber and revenue figures are self-reported by the company and labeled as such.
- the pre-seed is reported as both $600k and ~$700k across every's own posts and the trade coverage; the discrepancy is preserved, not reconciled.
- the 2025 seed is a drawdown structure — ~$500k reported drawn by mid-2025; the current drawn figure is undisclosed.
- the terms of the lex spinout stake and any alumni equity claims are undisclosed.
- which apps are every-owned versus every-partnered is reported but not fully mapped — the boundary moves with each launch.
- bundle revenue-sharing terms between every and its columnists were never published; the economics are inferred from departures, not contracts.
- the x/twitter corpus is partial — tweet-level material came through archives and interviews, not native search.
- early newsletter-era metrics (open rates, churn) exist mostly in every's own retrospective essays.
corrections
corrections and additional primary sources are welcome — cite the claim, the source, and what it changes. the catalog is designed to be audited, not just read.
AI-drafted at Ben Guo's direct request and credited to Hraness; every claim links to its cataloged source.