Storyline · entertainment · 2 reports from 2 newsrooms
Nathan Fielder’s “You Can See Everything” and the Elizabeth Holmes Buzz
First reported Oct 15, 4:08 PM ET · Latest Oct 16, 6:00 AM ET · Explainer updated Oct 16, 7:02 AM ET
Where things stand
As of Oct 16, 2026 WIRED ran a fan‑guide piece linking the current hype around a documentary on Theranos founder Elizabeth Holmes to experimental comedian Nathan Fielder. The day before, Variety reported that a trailer for the project, titled “You Can See Everything,” had been released and noted that viewers were anticipating further fallout for Holmes.
What changed
The WIRED article adds a fan‑guide perspective and stresses that the Holmes hype is tied to Fielder’s involvement, expanding on Variety’s earlier focus on the trailer and audience reaction.
Background
Nathan Fielder is known for his experimental comedy style, while Elizabeth Holmes is the former Theranos CEO convicted of fraud. “You Can See Everything” appears to be a documentary or film that brings the two together, generating interest both for its subject matter (Holmes) and for Fielder’s unconventional approach. The Variety piece mentions “schadenfreude,” meaning pleasure taken from another’s misfortune, reflecting some viewers’ attitude toward Holmes.
What we don’t know yet
The reports do not clarify whether the film centers on Holmes, on Fielder, or on both, nor do they reveal the exact release date, distribution plan, or the specific content that will be shown.
Timeline of reporting
- The New Fan’s Guide to the Unreal World of Nathan Fielder — WIRED
Surprised by the hype around yet another documentary on Theranos fraudster Elizabeth Holmes? It has everything to do with this experimental comedian.
- The Most Shocking Thing About ‘You Can See Everything’: Nathan Fielder’s Sympathy for the Devil — Variety
Ever since the first trailer went up for “You Can See Everything,” if not since word of the movie got up, schadenfreude lovers have been rubbing their hands with glee at the prospect of Elizabeth Holmes getting more of what’s coming to her. Especially knowing
How this works: stories from different newsrooms are grouped by topic, then AI writes the explainer using only those reports. It may miss context the reports don't include.