hraness

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

  1. every event, quote, and claim carries at least one source id.
  2. dates keep their precision — a year, a month, or a day — and approximate dates are labeled rather than sharpened.
  3. confidence stays honest: confirmed, reported, and inferred are distinct claims, not stages of the same claim.
  4. sources are typed by role — primary, interview, reporting, archive, community — so a claim's foundation is visible before it is read.
  5. sentiment labels describe the coverage, not the truth of it.

known gaps

  1. subscriber and revenue figures are self-reported by the company and labeled as such.
  2. 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.
  3. the 2025 seed is a drawdown structure — ~$500k reported drawn by mid-2025; the current drawn figure is undisclosed.
  4. the terms of the lex spinout stake and any alumni equity claims are undisclosed.
  5. which apps are every-owned versus every-partnered is reported but not fully mapped — the boundary moves with each launch.
  6. bundle revenue-sharing terms between every and its columnists were never published; the economics are inferred from departures, not contracts.
  7. the x/twitter corpus is partial — tweet-level material came through archives and interviews, not native search.
  8. 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.