The era of pure opinions may be coming to an end.

Author: David, Deep Tide TechFlow

In mid-January, X announced a $1 million reward for the best long-form article on the platform.

Elon Musk personally retweeted to confirm. The rules are simple: US users only, original English articles over 1,000 words, mainly ranked by exposure among US paying users.

You may recall that a few days before this content incentive campaign launched, personal growth blogger Dan Koe posted an article titled “How to fix your entire life in 1 day,” which received 170 million exposures, becoming the most successful article in X history.

Clearly, X saw the traffic potential of long-form content and quickly responded; lowering the threshold for Articles, adjusting algorithm weights to prioritize long-form content over short posts, and announcing a $1 million writing contest.

Over a two-week competition period, tens of thousands of participants entered.

On February 4, the results were announced, with a total prize pool of over $2.15 million—more than double the promised amount. The champion received $1 million, second place $500,000, plus a $250,000 “Creator Choice” award and four $100,000 honorable mentions.

The winners roughly are as follows:

You can see that Dan Koe made the list again. However, his previous article “How to fix your entire life in 1 day” had 170 million exposures, but the winning article in this contest only had 45 million.

Viral hits are still rare, but some winning articles are worth analyzing.

🏆 Champion: A 90,000-follower “small account” takes $1 million with a self-built database

Champion @beaverd’s article title translates to “Deloitte, a $74 billion toxic tumor spreading across the US.” It’s about the well-known consulting firm Deloitte.

This account currently has only 90,000 followers, considered small compared to others who won, and has no media backing or verified blue check outside of the platform.

His title doesn’t rely on trending keywords, but the content is quite provocative—exposing how Deloitte secured $74 billion in contracts from federal and state governments and then botched the projects.

Click here to view

Once you click in, you’ll see this person put in serious effort.

He built a website called somaliscan.com, scraping millions of government invoice data points, cross-referencing audit reports and system failure records.

Using this firsthand data, he told a series of shocking stories: California’s unemployment system was defrauded of $32 billion, Tennessee’s Medicaid system collapsed, leaving 250,000 children without coverage, and court system upgrades cost $1.9 billion and remain unfinished… covering 25 states in total.

He also uncovered the revolving door between Deloitte executives and government officials, detailing who moved from Deloitte to which department, which contracts they approved, with names and amounts clearly listed.

One person built a database himself and earned $1 million through independent research.

🥈 Second place: A finance giant with 700,000 followers teaches you how to profit amid tariff panic

Second place @KobeissiLetter is a familiar face in the macro finance circle, with 700,000 followers, focusing on US economic policies and market fluctuations.

His article is straightforward, breaking down Trump’s tariff strategies into a repeatable trading framework, titled “Trump’s Tariff Playbook: A How-To Guide.”

Since Trump often acts unpredictably, issuing bold policies and threats to other countries, but not always following through, Wall Street summarized this pattern as TACO—short for Trump Always Chickens Out.

TACO describes a recurring pattern:

Trump announces heavy tariffs → markets plummet → a few days later, he eases or delays → markets rebound.

Click here to view

KobeissiLetter’s article turns TACO from a joke into a timed operational manual. Using tariff events from the past 12 months as samples, he distills a complete cycle template for trading based on timing.

For example, weekend rumors from the White House cause panic, midweek buy-in from traders, the following weekend signals easing, and within 2 to 4 weeks, some agreement is reached. He also updates each step with ongoing commentary, making it feel like a continuous pre-research story.

He offers practical advice: monitor the US 10-year Treasury yield. If it breaks above 4.60%, Trump is likely to concede.

For paid users interested in macro and trading, this is highly appealing.

It doesn’t debate whether tariffs are good or bad, nor moral judgments; it simply tells you what actions to take and when to profit next time.

🥉 Third place: Most liked DAN KOE, familiar methodology for life mastery

Dan Koe’s entry, “How to enter a state of extreme focus anytime,” received 42,000 likes and 8,681 shares—top engagement metrics among all entries. But its exposure was only 11.04 million, less than a quarter of the champion’s.

X’s official “Creator Choice” award, worth $250,000, was given separately, so technically it’s not a third place.

It’s understandable—Dan Koe is “the person who inspired this contest.” His early January viral post with 170 million exposures directly showed how high the traffic ceiling for long-form content can be.

Click here to view

The article itself isn’t worth over-explaining; it’s about a personal growth methodology. It discusses how to achieve focus, citing neuroscience and flow state concepts for support and depth.

Ironically, this article had the best engagement data, but based on the core contest rule of “exposure among US paid users,” it didn’t rank at the top.

We’ll discuss why the most interacted article didn’t have the highest exposure later.

Honorable Mentions: 4 × $100,000

Nick Shirley, Josh Wolfe, Kaizen Asiedu, Ryan Hall each received $100,000. Their accounts cover public policy, geopolitics, history, and public safety.

Among them, Josh Wolfe is a co-founder of Lux Capital, a well-known venture capital firm, and announced that he would donate his prize money equally to four charities.

Since the original posts didn’t specify their articles, and due to time and resource constraints, we haven’t further investigated. Contributions and additional info are welcome.

Deeper observations

From the contest results, some patterns emerge:

• The most liked article only has a quarter of the exposure of the champion

This counterintuitive data point is definitely Dan Koe’s.

42,000 likes, 8,681 shares, 4,627 comments—top engagement across all entries. But exposure was only 11.04 million, less than a quarter of @beaverd’s. Interestingly, @beaverd’s likes are only 30,000, fewer than Dan Koe’s.

If you’ve managed social media, this feels odd. Usually, higher engagement means more algorithmic promotion and exposure.

But X’s contest measured not total exposure, but “exposure on the US paid user homepage timeline.” This metric excludes non-US users, non-paying users, search, and profile visits.

Dan Koe’s content is about personal growth, which naturally appeals globally, with many non-US followers. @beaverd’s content is about how Deloitte wastes US taxpayers’ money, so his audience is primarily US-based. Under the same algorithmic recommendation system, the “regional concentration” of content influences this metric.

• 9,000 followers beat 900,000 followers—content scarcity > follower count

Champion @beaverd had 90,000 followers before the contest. Second place @KobeissiLetter had 700,000. Dan Koe had 900,000.

If follower count directly determined exposure, rankings should be reversed. But the actual results show that, in X’s Articles recommendation logic, follower size isn’t as influential as expected.

@beaverd’s victory hinges on having unique content that others don’t, meaning content scarcity played a key role.

This is very different from traditional traffic logic. Big accounts rely on follower volume and posting frequency, but in an algorithm-driven environment, “having exclusive content” is more important than “how many followers you have.”

• Build your own content “hardware”

Looking at the three winning articles, their topics are completely different: one exposes government contracts, another teaches trading around tariffs, and the third discusses focus techniques.

In any platform’s classification system, they wouldn’t appear on the same list. But they share a common trait: each has its own “hardware,” in other words, a narrative framework.

@beaverd’s hardware is a self-built database scraping government data; KobeissiLetter’s is a tested trading framework over 12 months; Dan Koe’s is a six-chapter methodology blending neuroscience and psychology—seemingly complex but based on well-known principles.

None of the winners are purely opinion articles. All require long-form content to carry substantial information, which is precisely why X Articles exists.

Another notable fact: none of the eight winners are from traditional media.

All are independent creators. It’s not that traditional media didn’t participate; rather, in this contest format, individual accounts have an advantage.

Institutional media usually publish content on their own websites, sharing only links and summaries on social media. But Articles requires full content to be posted directly on X, which is awkward for media accustomed to external traffic.

What is X paying $2.15 million for?

Back to the platform itself.

X initially promised $1 million in incentives but ended up paying $2.15 million. During the contest, they also rolled out several supporting measures: expanding Articles from creator accounts to all paid users, adjusting algorithms to boost long-form content, and changing scoring to “exposure on the US paid user homepage.”

Such a large investment clearly indicates X’s goal: to acquire original long-form content on the platform.

Historically, long content on X mainly came from external links—Substack, Medium, personal blogs. Users click away immediately, leaving reading time and engagement data elsewhere. The goal of Articles is to keep these contents on X, so users can read from start to finish without leaving.

On a deeper level, X has Grok. Training large language models requires high-quality long-text data, but most content on X is 280-character tweets. If Articles can continuously attract creators to produce in-depth long articles, these become training material for Grok.

Finally, the value for paid users.

The contest rules focus on “exposure on the US paid user homepage,” directly telling creators that their content should serve paying users.

This supports the paid ecosystem with creator content, making paying users feel “my money is worth it because I see in-depth content on the homepage that I can’t find elsewhere.”

From a content creator’s perspective, we believe the era of pure opinions may be ending.

This trend also applies to crypto creators. The crypto industry isn’t short of opinions—every day, countless people call trades, predict prices, comment on regulation on X.

But few can build on-chain data analysis tools like @beaverd or break market cycles into repeatable trading scripts like KobeissiLetter.

Maintaining scarcity and independence, producing continuously—this is a highly professional activity, rewarding and fulfilling.

We also hope to see more content from the Chinese community, and that it will appear on the leaderboard in the future.