Author: Frank, PANews
Recently, the hottest topic in the tech and startup circles isn’t a big company releasing a new model, but the nationwide craze of “raising lobsters.”
On one hand, the “raising lobsters” 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 users can actually gain from Openclaw remains a mystery. Although social media is filled with such myth stories, a closer look reveals most are virtual stories designed to attract traffic.
Can you really make money by raising lobsters? If so, who is actually earning it?
PANews has compiled data from TrustMRR, public social media cases, 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 unverified claims or lacking evidence.
According to TrustMRR’s classification page for OpenClaw, there are 153 recorded projects in this ecosystem, with a total income of approximately $358,600 over the past 30 days. The top 30 projects account for 97.3% of this total. Breaking down these projects and their underlying monetization logic by “industry value chain” reveals a harsh truth: The first to make money aren’t those using lobsters to create products, but those helping others raise lobsters or teaching others how to do it.
But this isn’t the most genuine answer we seek. How exactly are those using Openclaw making money? Based on PANews’ analysis, here are five monetization strategies for OpenClaw.
First: Selling “Shovels” and Proxy Services: Quick Money from “Cognitive Gap” Traffic
Whether overseas or domestically, the most discussed and profitable products related to OpenClaw are often not specific applications but tools and one-click hosting services.
OpenClaw functions more like infrastructure rather than ready-to-use consumer products. It presents a high barrier for non-technical users. Once complexity exists, services tend to grow.
In the approximately $35,800 of sample income from TrustMRR over 30 days, projects like “Hosting Deployment” and “One-Click Cloud Hosting” contributed about $12,010, 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. In the past 30 days, it earned about $8,782.
In the Chinese internet scene, this logic is implemented more simply: “Lobster proxy” on second-hand platforms like Xianyu.
Media reports indicate that recently, “OpenClaw proxy deployment” services on Xianyu and Xiaohongshu have exploded. Remote installation costs range from 100 to 300 RMB, while local on-site services cost between 400 and 1000 RMB. During a certain period, daily transaction volume for related services increased by 150% week-over-week.
The essence of this logic is “earning from information and cognitive gaps.” Users are willing to pay to save 30 minutes of hassle, but this is a “window period” business. As official one-click deployment tools mature, the profits from pure proxy services will quickly diminish.
Second Layer: Packaging AI Expert Personas: When “Stories” Become the Most Valuable Product
If we go one step higher, another more valuable layer in the OpenClaw ecosystem emerges: not just deploying for you, but training your Agent well. In the top 30 samples from TrustMRR, projects related to templates, skill packs, and configurations contributed 26.4% of income.
One of the most credible and well-documented business cases in this layer is FelixCraft.
In early 2026, overseas 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 in revenue via Stripe. Additionally, the crypto community issued related MEME tokens for this Agent, forwarding 60% of daily trading fees to it, allowing Felix to earn up to $100,000 worth of crypto tokens in a week.
As a case worth deep analysis, Felix’s example has several features. First, Nat Eliason granted the AI high permissions, allowing it to autonomously post on Twitter, retweet comments, and interact with the community. Before product launch, Eliason stated he had spent significant effort building the Agent’s framework, including memory modules, security settings, and workflow design.
He admits that the profitability was an unexpected outcome. Essentially, Felix’s main revenue still comes from packaging the training process and results as a product for sale. The MEME token gains are more about creating buzz and traffic through storytelling.
Notably, the top-earning project in TrustMRR’s OpenClaw category is Claw Mart (a marketplace for Agent Skills), created by Felix. Its current total earnings have reached $71,300. The reason for such high revenue is that Felix, as an autonomous Agent capable of creating projects and automating tasks, serves as the strongest endorsement for this product. 
Felix’s success reveals a high-level path for OpenClaw commercialization: endowing Agents with continuous identity. When OpenClaw is packaged as a specific name (Felix), a sellable guide, a set of reusable skill packs, and a compelling “AI entrepreneurship” narrative, it transforms into a powerful personal brand with explosive potential. However, the core barrier of this approach isn’t AI itself but the strong Agent training and branding skills of Nat Eliason behind it.
Third Layer: Selling Efficiency Myths: Using AI to Work, Monetizing Through “Storytelling”
Among all monetization paths, the most recognized is probably: replacing manual labor with OpenClaw, with the saved costs translating directly into profit.
In content operation, this has become a reality. Developer Oliver Henry named his Agent “Larry,” responsible for managing his TikTok account. Larry automatically uses 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, generating about $588 in revenue (from two apps he recommended in his videos). Additionally, Larry created $4,000 through MEME coin issuance. Interestingly, Henry’s tweet sharing this story has already reached 7.1 million views, similar to Felix, where the story itself seems more commercially valuable than the Agent.
In China, Cheetah Mobile founder Fu Sheng built a team of eight Agents called “30,000,” achieving daily updates from a few articles per year to over ten, setting a record of over 1 million views on the BoSheng account, attracting social attention. The viral post explaining how the Agent works still remains a story about the Agent’s earning potential.
In content creation, whether Agent-generated content can become a hit remains unproven. Most viral stories so far focus on how Agents make money or improve work efficiency. The biggest current topic in content creation is “the lobster story.”
Fourth Layer: Industry Deep Customization: Moving Beyond Tool Overlap, Earning “Service Premium”
If proxy services earn “entry-level” money, then packaging “lobsters” into personalized demand 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 MacBook Air equipped with OpenClaw system.” The business isn’t just pre-installing a lobster but encapsulating it within a MacBook, along with tailored services to train the lobster into a customized Agent.
This type of service may truly meet the future commercial needs of “lobsters.” Users don’t just want a ready-to-use lobster but a fully trained, customized one. Behind this demand is the need for deep service for Agents.
Simply put, we foresee many companies relying on Agents in the future, but how these Agents are trained or “taught” will become an unavoidable core requirement.
Fifth Layer: On-Chain Trading Legends: The Most Tempting Poisoned Apples and Traffic Baits
On social media, the most sensational stories about OpenClaw are always about getting rich quick.
Currently, the few cases verified on-chain involve the prediction market Polymarket account 0x8dxd, a high-frequency trading bot. Many posts speculate that this bot relies on OpenClaw for high-frequency trading, but PANews’ analysis shows the actual controller behind this address has never published such stories. The so-called “OpenClaw designed an automated trading system earning $100,000/month” stories are just clickbait, mostly aimed at attracting followers for their copy-trading bots.
The reason for highlighting this case is to serve 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 reflection: Those who teach you how to make money are the real winners with no risk
After reviewing the entire ecosystem, we notice a phenomenon more worth pondering than any single case: sharing “I made this much money with OpenClaw” on social media is itself a very stable business.
When a post like “I earn 50,000 a month with OpenClaw” goes viral, traffic becomes bait. The author naturally directs viewers to paid communities, consulting services, or product links. “Showing off income” is the top of the funnel; “making money myths” are the strongest marketing material. This creates a perfect self-reinforcing cycle: selling success stories — attracting traffic — monetizing traffic — sharing secret strategies as a mentor — leveraging bigger gains.
Fundamentally, this has spawned a new business chain: bottom layer is proxy and infrastructure, middle layer is skill packs and workflow replacements, top layer is industry solutions and consulting. If you understand business, marketing, and have traffic, OpenClaw can drastically reduce costs and amplify productivity.
Many are sharing how OpenClaw optimized workflows and brought convenience, 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.
(P.S.: This article was not created using “lobsters.”)
