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A fractional AI executive service that helps traditional businesses build AI workflows with their own teams.
average retainer above ₩20M per month
Sell the business outcome and teach the client’s team to build; do not inherit an unmaintainable software agency.
Fewer bars = easier, cheaper, or faster for an AI-assisted solo builder. Editorial judgments based on the case details.
John Cheney’s earlier startup journey involved raising investment to hire developers, then losing money on an NFT pivot that produced less than $100,000 in sales despite an expectation of at least $1 million. In 2024 he began using Replit to build software himself. A four-day AI proficiency-test site attracted more than 100 visitors but no payments because checkout was broken. Cheney then messaged CEO acquaintances on LinkedIn and sold a $15,000 employee AI-training engagement. A client asked him to stay on, and he proposed a $15,000 monthly fractional AI executive role. Gen AI PI now helps companies without a CTO define AI strategy, redesign work, and train employees to build AI-native systems. The creator reports ₩3 billion in annual recurring revenue within a little over a year, with a few employees. The model sells judgment and coaching, not outsourced code alone.
Cheney’s first customer came through direct outreach to CEOs he already knew on LinkedIn. The test site had drawn more than 100 visitors without a payment because checkout did not work, so he shifted from waiting for product traffic to booking a conversation.
The quick-reference card — acquisition channels, replication playbook, risks & traps, and our verdict — is members-only.
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Two production-grade prompts per idea — a full build spec and an SEO growth plan — plus 10 tailored build specs a week. Members only.
Join the Unicorn Club — $5/moCancel anytime, in one clickEvery claim traces back to a listed source — open any of them and check the number yourself. The exact words are quoted below, with a timestamp that jumps to the second each figure is said.
“And now, his company, restarted with AI and without a single developer, is generating 3 billion won in annual recurring revenue.”
0:12 · hear it in the video“By the time the call ended, he had a contract for $ 15,000. That’s 20 million won in our currency.”
4:23 · hear it in the videoData credibility: The video narrator reports ₩3 billion in ARR and describes contracts and pricing attributed to John Cheney. No financial statements, contract records, customer count, or independent revenue audit are shown, so the headline figure is creator-reported.
The first contract was a $15,000 engagement to observe and teach a company’s employees AI skills. The prospect had first arrived through a CEO call, but Cheney sold a service rather than the AI test site; the site itself had attracted visitors without producing payments because its checkout was broken.
The flywheel began when a client asked Cheney to stay after the initial training. He created a recurring offer on the spot: act as a part-time AI executive for $15,000 per month.
The broken checkout and the 100-plus unpaid visits could have looked like market rejection. Cheney found the issue, then changed the route to revenue by contacting CEOs directly and selling a service he could deliver without a functioning payment page.
Gen AI PI is a fractional AI executive and enablement service. Cheney maps an organization’s AI strategy, changes how work gets done, and trains employees to build AI-native systems themselves. The initial customer base included established companies in fields such as painting, pool service, construction, and masonry that lacked a CTO. The service is meant to bridge the gap between business operations and technical execution without staffing a traditional development team. Its distinctive delivery choice is to coach client employees with vibe-coding tools rather than take ownership of every software system. That choice makes the service more like a combination of executive advisory, process design, and hands-on training. A useful engagement starts with the client’s workflows, sets standards, and makes verification part of the build process.
The reported model combines a $15,000 initial training contract with a later $15,000 monthly retainer offer for fractional AI executive work. The creator says Cheney receives an average of more than ₩20 million per month from clients and reports ₩3 billion in ARR for the company. Those are service contracts, so revenue depends on maintaining executive-level access and producing useful change. Price around ongoing decisions, training, and oversight rather than hours of ad hoc coding. Define a renewal plan, decision rights, and escalation boundaries in the contract. Avoid promising unlimited software delivery inside a retainer. A package that teaches the client’s team can support repeat work without making the provider responsible for every feature request. The economics still depend on founder time and how much delivery the small team can standardize.
Cheney moved from a proposed $105,000 outsourced app build to prototyping with Replit. The AI-built test site took four days, although its payment system did not work. His current method includes writing a business plan in business-plan.md and instructing coding tools to refer to it, then checking that the output meets those standards. The video provides no operating-cost or gross-margin breakdown for Gen AI PI. The practical stack is therefore less important than the operating discipline: specify scope, validate each workflow, test client-facing output, and make a human owner responsible for acceptance. Keep client credentials and business data protected, and use a separate project environment for each account. The team should document reusable prompts and review steps without treating generated code as production-ready by default.
Copy the wedge: approach companies with real operations and no CTO, then sell a paid working session that combines workflow observation with employee training. Use a narrow trade vertical so you can recognize repeated processes and speak the buyer’s language. Convert the initial project into an ongoing fractional leadership relationship only after the client sees value. Change the delivery model by making verification explicit: define success criteria, assign client owners, and test outputs before employees rely on them. Keep the service focused on strategy and capability transfer instead of accepting every custom software request. Cheney’s earlier hiring-heavy and NFT chapters also show the cost of scaling a model before its economics are understood. This playbook best fits a confident seller who can understand operations and coach technical work, even if they are not a conventional software engineer.
Our read: demand for AI guidance is real, but a consulting retainer can become an unbounded development agency if scope is vague. A few clients may consume the founder’s calendar, and employees may lack time or authority to adopt new workflows. AI-generated systems can break existing features or expose sensitive data; the client should not discover defects first. Build written requirements, test cases, ownership rules, and maintenance boundaries into every engagement. The category is crowded, and a successful pitch today does not guarantee that the same offer will remain distinct as internal tools improve. Keep pricing linked to executive judgment, workflow adoption, and client capability rather than code volume. Reported ARR is substantial, but it remains creator-reported and does not show margins or customer concentration.
The four founder playbooks — first customers, first dollar, the flywheel, the silent stretch — are in the Unicorn Club, on this idea and on all 1,435 others. The story, the numbers, the sources and every later section stay open to everyone.
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