Most creators who join Scribble campaigns ask the same question after their first few submissions: how do I earn more? The instinct is usually to write more, publish faster, or join more bounties. The creators consistently at the top of the leaderboard are doing something different. They are not writing more. They are writing in a way that gets their content discovered, retrieved, and cited by AI search engines, and that single distinction compounds into meaningfully higher earnings over time.
This article explains why that gap exists and how the top creators approach campaigns differently. For the complete tactical framework on how to actually write content that earns AI citations, the full guide is in How to Write Content That Gets Cited by AI Search Engines.
How the Earning Loop Actually Works
Understanding why some creators earn consistently more starts with understanding the actual earning loop inside a Scribble campaign.
A project launches a bounty. Creators research the project, publish content, and repurpose it across multiple platforms. AI search engines crawl, index, and retrieve that content. Creators whose content gets cited perform better inside the bounty, climb the leaderboard, and earn more. That is the loop.
The part most creators underestimate is the middle step. AI citations are not a nice-to-have outcome that might happen if the content is good enough. They are the primary mechanism that determines how discoverable a piece of content becomes after it is published, and discoverability is what converts a well-written article into a high-performing bounty submission.
The research behind this is specific. A 2024 study on Generative Engine Optimization published at KDD by researchers from Princeton, IIT Delhi, Georgia Tech, and the Allen Institute for AI tested which content modifications actually increased visibility inside generative search engines. Adding statistics, authoritative citations, and structured sourcing improved AI visibility by up to 40% across diverse queries. That is not a marginal improvement. It is the difference between content that gets cited and content that gets ignored, and it translates directly into the difference between a top-five finish and an also-ran.
What Top Creators Do Differently
The easiest way to describe what separates top Scribble creators from everyone else is this: they think like distributors, not just writers.
A typical creator publishes one article on one platform and waits to see what happens. A top creator treats one research process as the input to a multi-platform publishing workflow. The same core research becomes an X thread, a Medium article, a Substack post, a Reddit discussion, and a Paragraph piece. Each of those is a separately indexed asset. Each one creates another opportunity for an AI engine to retrieve and cite that creator's work when someone asks a relevant question.
This matters because AI systems like Perplexity, ChatGPT with web browsing, Microsoft Copilot, and Google AI Overviews all operate through retrieval-augmented generation, pulling content from indexed sources at the moment a query is asked rather than relying solely on what was baked into the model during training. More indexed assets across more trusted platforms means more surface area for retrieval. More retrieval means more citations. More citations means better campaign performance.
Top creators also build topical authority over time rather than chasing one successful article. A creator who has published ten pieces about DeFi bridging, across multiple platforms, over multiple months, becomes a trusted source on that topic in ways that a single article never can. AI systems weight consistency and authority when selecting sources. Creators who consistently participate in campaigns in their area of expertise compound that authority with every piece they publish, making future content easier to surface and cite than their first.
Why Repurposing Is the Real Multiplier
One research process should never produce one piece of content. This is the specific habit that separates high earners from average ones, and it is also the most underused leverage point in Scribble campaigns.
Here is what one well-researched campaign submission can become:
An X thread that distributes the core finding quickly and drives early engagement. A Medium article that builds on the thread with full context and sources. A Substack post that situates the research inside a broader narrative for a subscribed audience. A Reddit discussion that engages community members authentically around the core question the research answers. A Paragraph article that reaches crypto-native readers directly.
Each of these versions is indexed separately. Each creates a new entry point for AI retrieval. Each one reinforces the others in terms of topical authority. The creator who publishes all five versions of the same research is not doing five times the work. They are doing roughly one and a half times the work for five times the indexed surface area.
The flywheel this creates is worth understanding explicitly. More indexed assets produce more AI citations. More AI citations produce better bounty performance. Better bounty performance produces higher earnings and greater platform authority. Greater platform authority makes future content easier to discover and cite. Each campaign cycle compounds the last one if a creator is publishing consistently across platforms rather than treating each submission as a one-off.
Why Each Platform Earns Its Place in the Workflow
The platforms Scribble campaigns require are not interchangeable, and treating them as identical distribution channels misses why each one matters.
X is where distribution starts. It is the fastest way to put an idea in front of the people most likely to engage with it early, and early engagement signals matter for discoverability downstream. An X thread also creates a public, indexed record of a creator's take on a topic before the longer-form piece is live.
Medium is where discoverability compounds. Medium has strong domain authority, and content published there tends to index well in traditional search and increasingly gets pulled into AI retrieval results. It is the best platform in this workflow for building an evergreen library, content that keeps attracting citations long after the campaign closes. Ahrefs' research on evergreen content points to the same pattern: the average #1 ranking page in Google is five years old, and well-structured content keeps compounding long after publication — the same logic increasingly applies to AI citation visibility.
Substack builds the long-term asset that Medium cannot: an owned audience. Subscribers are not dependent on a platform's algorithm to receive a creator's work. For a creator who participates in Scribble campaigns consistently, Substack becomes the platform where authority accumulates most durably, because the relationship is direct rather than mediated by a feed. Scribble's own comparison of the two platforms covers this trade-off in more detail, but the short version is that Medium and Substack solve different problems and both belong in a serious creator's workflow.
Reddit deserves more attention than most creators give it. Reddit has licensing partnerships with both Google and OpenAI for training data. Google's Hidden Gems update specifically elevated authentic, community-driven Reddit discussions in search results. AI systems are increasingly pulling from Reddit threads when answering questions that benefit from real-world community experience rather than polished editorial content. A genuine, well-sourced Reddit comment or post on a relevant topic is one of the most reliably cited content types in AI-generated answers right now. Scribble's guide on how to actually win on Reddit covers the specific approach that works.
Paragraph reaches the crypto-native reader directly. For Web3 projects specifically, Paragraph's audience is already paying attention to the space in a way that a general publishing platform's audience may not be. It is the platform where a creator's work is most likely to be read by the people closest to the project being covered.
The Content Itself Has to Be Built for Retrieval
Publishing across all five platforms does nothing if the underlying content is not structured in a way that AI systems can actually extract and cite. This is where most creators leave points on the table even when they are doing everything else right.
AI retrieval systems do not simply copy Google's rankings. They look for content that is structured, specific, and well-supported, content where the answer to a question is findable in a paragraph that stands on its own without needing surrounding context to make sense. Research on semantic chunking and retrieval-aware content structure shows that AI systems extract and cite self-contained passages far more reliably than content where the key point is buried three paragraphs into an explanation.
Google's own guidance on Helpful Content and E-E-A-T, Experience, Expertise, Authoritativeness, and Trustworthiness, describes exactly what AI systems are also optimizing toward. Content that demonstrates first-hand knowledge of a topic, cites verifiable sources, and makes specific rather than vague claims performs better on both dimensions. A creator who says "RocketX returned 18.51 ETH on a 0.5 BTC to ETH swap tested on June 29, 2026" is producing a citable claim. A creator who says "RocketX offers competitive rates" is producing filler.
The full framework for building content that earns citations, including how to structure headers, where to place key claims, how to handle sourcing, and what Scribble's QFO (Query Fan Out) gate actually checks, is in How to Write Content That Gets Cited by AI Search Engines. That article covers the tactical detail this one is deliberately not duplicating.
Why This Compounds Over Time
The creators earning the most consistently on Scribble are not the ones who wrote the best single article. They are the ones who have built a body of work across multiple platforms on topics they know well, indexed across multiple surfaces, cited across multiple campaigns.
AI search adoption is growing fast enough that this matters more each month, not less. Every major AI system, Perplexity, ChatGPT, Copilot, and Google's AI Overviews, is expanding the volume of queries it answers by retrieving and synthesizing web content. A creator who has spent six months building indexed, well-cited content on DeFi, or privacy tools, or Layer 2 infrastructure, is in a fundamentally better position to earn from the next relevant Scribble campaign than a creator starting fresh, regardless of how well that new creator writes.
The question worth asking about every campaign submission is not "is this good enough to win?" It is "will this still be driving AI citations in six months?" The creators who ask the second question consistently are the ones at the top of the leaderboard.
Ready to put it into practice? Join the network and browse live bounties to start building your own citation footprint.
Written by
I’m Tanmay Tarte, a community builder at Scribble and an engineering graduate from Priyadarshini College of Engineering. Over the years, I’ve worked across community management, content, hosting, and social media, mainly within the Web3 and creator ecosystem space. Outside of work, I’m a huge sports enthusiast and can genuinely play cricket all day, every day.
