- Social evidence ID
- SE-LINKEDIN-20260803-LI-POST-019
- Author
- Oli Nold — canonical person person-oliver-nold
- Original platform
- Historical account
- oli-nold
- Original publication date
- 2026-08-03
- Original platform status
- Publicly available at original URL
- Related venture
- vivameda
- Related career event
- event-vivameda-2025
- Content type
- Public post (live platform read)
- Original content
- Oli Nold reports a model test in which the top one percent of ranked companies entered hypergrowth at 27x the base rate, and states explicitly that this is not a unicorn prediction machine.
- Original source URL
- https://www.linkedin.com/feed/update/urn:li:activity:7489930872947802112/
- Source package
- LI-POSTS-20260818 — official platform account export. The raw archive is held privately; no storage location or file identifier is published.S-031
- Archive part
- LI-POST-019
- Path inside the export
- Not recorded
- Raw text integrity hash (SHA-256)
- Not recorded
- Record kind
- public_post
- Source independence
- First-party public post — evidence that the statement was published on that date, never independent corroboration of the statement itself
- Evidence relevance
- Evidence that the pre-scaling / workforce-structure research line was publicly communicated on this date, together with its stated limitation.
- Evidence classification
- CONTEMPORANEOUS FIRST-PARTY RESEARCH COMMUNICATION
- Evidence confidence
- MEDIUM
- Archive source
- SURVIVING ORIGINAL PUBLIC URL
- Professional relevance
- MEDIUM PROFESSIONAL CONTEXT (score 70/100)
- Themes
- None recorded
Claims in the main register supported by this record
C-VIVAMEDA-013 Public LinkedIn posts of 15 April, 22 April, 3 August, 5 August, 7 August, 10 August and 13 August 2026 record Oliver Nold publicly communicating Vivameda research and positioning: historical workforce comparison across the dot-com and COVID periods, the longitudinal dataset as an AI training substrate, pre-scaling and unicorn-pattern model results, a ten-year study of 225 major retailers reporting a 5.5x higher failure rate where capabilities were more digitally replicable, a six-company AI-cohort observation, and an M&A longitudinal-diligence use case. The posts establish that the results and positioning were publicly communicated on those dates. They are not independent validation, and the limitations stated in the posts are preserved: the pre-scaling result is explicitly not a unicorn prediction machine, and the six-company AI cohort is explicitly too small a sample to constitute a predictive model. The underlying studies and methodology remain the stronger sources.
Post existence: verified from the official first-party account export. Independent verification of the statement inside the record: not established by this source.
Independent material referencing the same event:S-027