TikTok News Network

TNN is a nightly satirical news broadcast about the Egyptian internet. I founded it, host it, and built the site it lives on. It runs on Wholana's data pipeline, and has grown to 12M+ views, 52K+ followers, and 260 stories covered across five recurring formats.

Views
12M+
Followers
52K+
Stories covered
260
Role
Founder, anchor and engineer
Period
2026 – Present
Stack
Node.js, Payload CMS, Postgres, Wholana API, TypeScript, Next.js, React, Tailwind, Figma
Site
tiktoknewsnetwork.com
  • The TNN home page: a red breaking-news bar reading “TNN is live on TikTok, new episode every night”, the headline “The Cure for Brain Rot” with “Brain Rot” struck through in yellow highlighter, and a row of stats for on-air date, stories covered, and straight faces broken
  • The “This week's briefings” row on the TNN home page: six episode cards numbered EP. 061 down to EP. 055, each with a dated header, a black-and-white still from the broadcast carrying a lower-third caption, and an episode title such as “TNN61: The Match In China”
  • The Bureaus section, “Five desks. One network.”: a flagship panel for The Nightly showing cadence, beat and an ON AIR status, above a four-column row for The Debates, Field Reports, TNN Stocks and On the Record, each with its own status chip
The front page, the week's briefings, and the five nightly desks.

Context#

TNN treats Egyptian TikTok culture with the deadpan gravitas of a broadcast news desk. The tagline is “Where high-stakes journalism meets low-stakes internet beef.” It airs nightly at 21:00 Cairo time, and I founded it, anchor it, and built the platform behind it.

It started in March 2026 with no studio and no crew. It has since grown into five recurring formats (The Nightly, The Debates, Field Reports, TNN Stocks, and On the Record) with a team of correspondents and co-anchors, 260 stories covered, 12M+ views, and 52K+ followers.

The “Engineering behind TNN: Wholana” section, pairing a research, signals and output summary with a screenshot of the Wholana explore feed: a sidebar of research and creator tools beside a grid of TikTok posts, each showing views, likes, comments, shares and an outlier multiplier
The site says the quiet part out loud: the show's rundown is a filtered feed, not a scroll.

The distribution problem, solved with software#

A nightly show is a nightly deadline. The hard constraint is not production, it is knowing what actually happened on the Egyptian internet that day before the rest of the internet does, every single day, without spending the whole day scrolling.

TNN runs on Wholana, the research platform I built. It aggregates posts from Egypt's 2,000 most popular TikTok creators and lets me filter by engagement and date window, so the show's rundown is a query rather than a scroll. Curation becomes a data problem with a repeatable answer, which is the only reason a nightly cadence is sustainable solo.

The TNN articles index: an ARCHIVE bar reading “full text articles for shipped broadcasts”, the heading “Article briefings”, and an archive-file panel headed “Every published briefing, latest first” with a count of 54 briefings on file
Every episode gets a written briefing, so the coverage stays searchable.

The website#

The site is the show's archive and its front door: every episode gets a written briefing, so the coverage is searchable and linkable long after the video scrolls past. It is built on Next.js with Payload as the CMS, which matters because the editorial workflow has to be fast enough to publish a recap right after air without a deploy.

The design carries the same joke as the show. Broadcast typography, a rigid grid, stat lines and desk names presented straight. The visual seriousness is what makes the subject matter funny, so the design had to commit fully rather than wink.

Why it matters as engineering work#

TNN is the proof that Wholana's pipeline works. Building a research tool and then betting a daily publishing obligation on it is a much harder test than a demo: if the ingestion, scoring, or filtering is wrong, the show is wrong that night and the audience notices.

Running both sides also feeds the product. Every friction point in the nightly rundown becomes a Wholana feature request from the most demanding possible user, which is a fast and honest loop.