Breaking down OpenClaw's Wealth Trap: Everyone is "Farming Lobsters" — How Do Others Make Money?

Author: Frank, PANews

In recent times, the hottest topic in the tech and startup circles isn’t a major company releasing a new model, but the nationwide craze of “Lobster Farming.”
On one hand, the “Lobster Farming” boom has driven growth in related industries, with large model companies and cloud server providers making huge profits. On the other hand, how much real benefit Openclaw can bring to users remains a mystery. Although social media is filled with myth-like stories, a closer look reveals most are virtual stories designed to attract traffic.
Is lobster farming truly profitable? If so, who is actually making the money?
PANews has compiled data from TrustMRR, public cases on social media, project official websites, and cross-verified reports from multiple sources. To distinguish “verified real income” from online myths, we excluded many rumors based solely on one-sided claims or unverified reports.
TrustMRR’s new startup data platform shows that the OpenClaw category has 153 recorded projects, with total income in the past 30 days of approximately $358,600. Analyzing the top 30 samples, their combined income accounts for 97.3% of the total.
If we break down these projects and their underlying monetization logic by “industry value chain,” a stark truth emerges: The first to make money aren’t those using lobsters as products, but those helping others farm lobsters, teaching others how to do it, and those riding the hype with MEME tokens.
However, this isn’t the most genuine answer we’re seeking. How exactly are those truly using Openclaw making money? To answer this, PANews has summarized five monetization strategies of OpenClaw.

First: Selling “Shovels” and services — quick cash from exploiting “knowledge gaps”
The most discussed and financially impressive products in OpenClaw are often not specific applications but tools and one-click hosting services.
OpenClaw functions more like an infrastructure layer rather than a ready-to-use consumer product, creating high barriers for non-technical users. Once complexity exists, services will emerge.
Among the approximately $350,000 in the past 30 days, “hosting deployment” and “one-click cloud hosting” projects alone contributed about $120,100, accounting for 34.5% of the sample income.

A typical example is QuickClaw, which packages underlying capabilities into a mobile app priced at $3.99/week or $49.99/year, generating about $8,782 in the past 30 days.
In Chinese communities, this logic manifests more simply: “Lobster farming” services on Xianyu (second-hand marketplace).
According to media reports, recently, “OpenClaw deployment services” on Xianyu and Xiaohongshu have exploded in growth. Remote installation costs range from 100-300 RMB, while on-site services cost 400-1000 RMB. During certain periods, daily transaction volume of related services increased by 150% compared to the previous quarter.
This logic essentially exploits “information and perception gaps.” Users are willing to pay to save 30 minutes of effort, but this is a “window period” business. As official one-click deployment tools mature, the red ocean of pure deployment services will quickly fade.

Second: Packaging AI expert personas — when “storytelling” becomes the most expensive product
Moving up the chain, another more valuable layer appears in the OpenClaw ecosystem: not just deployment, but training the agent.
In the top 30 TrustMRR samples, projects related to templates, skill packs, and configurations contribute 26.4% of revenue.
One of the most credible and complete business cases at present is FelixCraft.
In early 2026, creator Nat Eliason launched an experiment. He named his OpenClaw robot “Felix,” invested $1,000 as startup capital, and let it build its own business. Within a week, Felix generated about $3,500 via Stripe.
Additionally, the crypto community issued related MEME tokens on-chain, sharing 60% of daily transaction fees, allowing Felix to earn tokens worth up to $100,000 in a week.

As a case worth deep analysis, Felix has several features. First, Nat Eliason granted the AI high permissions, allowing it to autonomously post on Twitter and interact in communities. Before launch, Eliason spent significant effort building the framework, including memory modules, security settings, and workflows.
He admits in a podcast interview that the profit was an unexpected outcome. Essentially, Felix’s main revenue still comes from packaging his training process and results as a product. The MEME token gains are largely driven by the story and hype it creates.
Notably, the top-earning project in TrustMRR’s OpenClaw category, Claw Mart (an agent skill marketplace), was created by Felix. Its current total revenue has reached $71,300. The story of Felix as an autonomous agent creating projects and automating work is the strongest endorsement for this product.
Felix’s success reveals a high-level monetization path: giving agents continuous identity. When OpenClaw is branded as a specific name (Felix), a sellable guide, a set of reusable skill packs, and a compelling “AI entrepreneurship” story, it transforms into a powerful personal brand with viral potential.
However, the core obstacle isn’t AI itself but the strong agent training and branding skills of Nat Eliason behind it.

Third: Selling efficiency myths — using AI to work, monetizing through storytelling
Among all monetization paths, the most recognized is: replacing manual work with OpenClaw, and profiting from the cost savings.
In content operations, this has become a reality. Developer Oliver Henry named his agent “Larry,” responsible for his TikTok account. Larry automatically calls large models to generate images, write titles, and upload drafts. Henry only spends 60 seconds daily choosing background music and clicking publish.
Henry states that within five days, Larry’s videos surpassed 500,000 views, bringing in about $588 in revenue (from paid app recommendations in his videos). Additionally, Larry generated $4,000 through MEME tokens.
Interestingly, Henry’s tweet sharing this story has already reached 7.1 million views. Like Felix, the story itself seems more commercially valuable than the agent.

Fusheng, founder of Cheetah Mobile, built a team of eight agents called “30,000,” achieving daily updates from a few articles per year, with the Bosheng account hitting a record 1 million+ views and attracting social attention. The viral post explaining how the agent works is still the most popular.

This suggests that in content creation, whether agent-generated content can go viral remains unproven. Most viral stories are about agents making money or improving efficiency.
The biggest current topic in content creation is the “little lobster” story.

Fourth: Deep industry customization — moving beyond tool competition to earn “service premiums”
If deploying is about earning “entry barriers,” then packaging “lobsters” into personalized products is another level.
RoofClaw exemplifies this. TrustMRR shows it earned about $49,800 in the past 30 days, with total revenue reaching $1.8 million. It offers “personalized customization and delivery of a MacBook Air equipped with OpenClaw.”
This means they don’t just pre-install a lobster; they embed it into a MacBook, providing customized services to tune the lobster to meet specific needs.

This type of service likely taps into the future commercial demand for “lobsters.” Users don’t just want a ready-to-use lobster but a fully trained, tailored one. Behind this demand is a need for deep, customized agent services.
Frankly, we foresee many companies relying on agents in the future, but how they train or “cultivate” these agents will become an unavoidable necessity.

Fifth: On-chain trading legends — the most tempting poisoned apple and traffic bait
On social media, the most viral stories about OpenClaw are always about getting rich quickly.
Currently, one verifiable on-chain account is 0x8dxd on Polymarket, a high-frequency trading bot. Many social media posts speculate that this bot relies on OpenClaw for high-frequency trading, but PANews’s analysis shows the actual controller behind this address has never published such claims.
Stories claiming “OpenClaw designed an automated trading system that earns $10,000 a month” are just soft ads, mostly promoting their automated trading programs.
This example serves as a warning: as previous PANews research confirms, agents and high-frequency trading bots are not the same. People are often misled and fantasize about their mystery.

Final thoughts: Teaching others how to make money is the real winning strategy
After analyzing the entire ecosystem, we notice a phenomenon more worth pondering than any single case: sharing “I made X amount with OpenClaw” on social media is itself a very stable business.

When a post like “I earn $50,000/month with OpenClaw” goes viral, traffic becomes the bait. The author naturally directs viewers to paid communities, consulting, or product links.
“Showing off income” is the top of the funnel for acquiring customers, and “making money myths” are the strongest marketing material. This creates a perfect self-reinforcing cycle: selling stories of earning money — attracting traffic — monetizing traffic — then sharing “secrets” as a mentor — gaining even greater leverage.
Essentially, this has spawned a new business chain: bottom layer is deployment and infrastructure; middle layer is skill packs and workflow replacements; top layer is industry solutions and consulting.
If you understand sales, marketing, and have traffic, OpenClaw can drastically reduce costs and amplify productivity.
Many are sharing how OpenClaw optimized workflows and enabled many conveniences, but it’s far from a secret to wealth. The “herd effect” it triggers is the core of this traffic story: when you desperately push through the crowd to the front, you find nothing there — and you are the one waiting.
(PS: This article was not created using “little lobster”)