The US ordered civilian agencies to remove DeepSeek — including apps built on it

A first-time iOS developer wanted a simple thing: a private place on an iPhone for photos and files that nobody else could open. Not Apple, not a cloud provider, not him. He built it in about three weeks, mostly by directing AI coding agents, and launched with no audience, no ad budget and no marketing plan.

The first month, the app made $66.

Six months later it made $41,000 in a single month, and it is now averaging roughly $2,000 to $3,000 a day, as the founder says in a Starter Story interview published on 18 October 2026. The app has passed 60,000 downloads. He says he has not written a single line of code or a single line of the website copy himself.

The interesting part is how he got there, because it was not a viral video and it was not paid acquisition.

The product is almost boringly simple

The app stores photos, videos and files in an encrypted vault on the phone. You unlock it with a pattern, keep a recovery phrase, and there is no account and no sign-up. Because the keys never leave the device, the company cannot read the contents and cannot recover them either.

That simplicity is the point. The category is crowded with apps that are 15 years old and have millions of users, which means they rank well and get taken for granted. He could not outspend them, and he could not outrank them inside the App Store.

So he attacked the part they ignore: the open web.

The growth engine: one guide a day

He started with a normal marketing site: pages outlining each feature, then a series of guides aimed at the questions people actually type, such as how to store photos privately on an iPhone. Every one of those pages was written by a coding agent, not by him.

The loop is mechanical. Each morning, a small command-line tool he built queries Google Keyword Planner, looking for keywords where his site already appears in search results but gets almost no clicks. That gap is the opportunity: search engines have decided the page is relevant, but the title and the content are not earning the visit.

A guide is generated for that gap. He publishes about one a day. Google typically indexes a new page in three to four days. Internal links from pages that already receive traffic push the new one up, and the library compounds.

He says roughly 99% of the remaining daily work is a Claude agent waking up and running the loop.

Where the money actually comes from

The site is now the majority of his traffic, and he says about 10% of web visitors download the app.

The conversion curve is the unusual part. Only 5.47% of people who download on day one end up paying, and day one is the worst day, not the best. Conversion climbs for about two months and peaks around day 60. That is the opposite of the standard consumer-app playbook, where a user who does not pay immediately usually never does.

Lifetime purchases do most of the work: roughly 60% of purchases and more than 80% of revenue, as he describes it. The product earns trust slowly, and the pricing reflects that.

How to copy the method

Pick a need people already search for, not a clever idea nobody is looking up. He did not invent demand for private photo storage; he found a crowded category with old incumbents and went after the questions they never bothered to answer.

Build the smallest honest version of the product. Three weeks and coding agents were enough because the feature set was narrow and the promise was clear. A vague product cannot be explained by a guide.

Find the queries where you already appear without clicks. If you have no site yet, start with the plain questions your buyers ask before they know your product exists. Write the answer better than the first page of results, not longer.

Publish on a schedule you can keep, and link every new page from pages that already get traffic. One good page a day beats ten rushed pages once. Then measure the two numbers that matter: search impressions and the share of visitors who take the next step.

Finally, fix the conversion path before you scale the traffic. His call to action sits where readers naturally stop, and his paid tier is a one-time upgrade rather than a subscription that expires. Traffic into a broken funnel is just expensive noise.

What to watch out for

Every figure here is self-reported in a promotional case-study interview and has not been independently audited. Revenue is not profit: AI coding tools, hosting and payment fees all cost money, and the interview does not break out margins.

He also had unusual advantages. He is a repeat founder with a technical and security background, and the app was built on a privacy promise that is hard to copy without real care. A security product that leaks once is finished.

The daily publishing loop is also a real commitment, and search results are not guaranteed. Google can change how it indexes, the keyword gap can close, and a competitor can copy the same pages. The method lowers the cost of distribution; it does not remove the risk.

And the honest framing matters: this is a report of what one person did, not a promise that the same app or the same numbers will happen to anyone else. The repeatable part is the loop, not the outcome.

A self-taught filmmaker spent six years directing, editing and building 3D scenes for clients abroad. When generative AI turned that craft into something anyone could buy in seconds, his own creative work dried up. Instead of fighting the change, he built a tool around it.

The product is an all-in-one AI creative workspace: one place to write, generate images, turn them into video, add music and voice, and keep projects, consistent characters and team credits together. He built it alone, with no programming background, no outside funding and no paid ads. He says it brings in about $60,000 a month, roughly ten months after launch.

The interesting part is not the product. It is how he got customers, because his first viral success made almost no money.

59 million views, almost no revenue

He made a series of short AI videos styled as phone footage of famous scenes, the kind of thing a bystander might have filmed. In 30 days the series did 59 million views on Instagram and added more than 200,000 followers across his account and the product's account.

That is the number most people would stop at. He says it barely moved revenue. Views are attention, not intent: someone who watches a spectacular clip has no reason to open a tool, let alone pay for one.

The post that changed it

What worked was a tutorial published after the series. In it, he showed exactly how one of the videos was made and opened the entire project for anyone to copy: every prompt, every generated image, every video take. Nothing was hidden behind a paywall or a course.

The effect was immediate. On the day the tutorial went live, signups from outside his home market jumped 6.5 times. Over the next three weeks, 3,285 people signed up, about 78% of all new signups in that period.

He calls the loop "show, then teach": make something people actually want to watch using your own product; post only the result, with no pitch and no feature list; then immediately teach exactly how you made it, with the files open.

The logic is simple. The result earns attention. The tutorial converts it, because the viewer has just seen proof that the thing is possible and is now given the recipe. Giving the recipe away also builds more trust than claiming the tool is clever.

The second channel: affiliates

Customers who run the same loop on their own audiences earn a share of what they bring in. He says one affiliate brought in more than $30,000 on his own. That is a distribution channel built from people who already use the product, not from an ad budget.

How to copy the method

Start with a result, not a product page. Pick something your tool can make that is visually obvious in a few seconds: a transformation, a before-and-after, a scene that should be impossible. Make it with the tool yourself, because the demonstration has to be real.

Post the result by itself. No introduction, no list of features, no link. If the result needs an explanation to be interesting, it is not the right result yet.

Then post the recipe. Show the screen, the prompts, the settings and the mistakes. Open the project if the platform allows it. The tutorial should let a motivated viewer reproduce the result without guessing.

Repeat the pair. The result finds new people; the tutorial turns some of them into users. Over time the tutorials become a searchable library that keeps working after the views fade.

Finally, let your best users teach it too. An affiliate or referral deal gives them a reason to run the same loop for their audience, and it costs nothing until a sale happens.

What to watch out for

Every number here is self-reported in a promotional case-study interview and has not been independently audited. The $60,000 is revenue, not profit; AI image, video and audio generation costs money on every run, and the interview does not break out margins.

He also had advantages that are hard to copy: six years of professional visual skill, an existing audience, and a product built specifically around his own workflow. The method is teachable; the timing and the craft are not guaranteed.

And the central warning is his own: he says his biggest mistake was thinking virality is a business. Millions of views felt like success, but they barely moved revenue until he gave people a reason to act.

The takeaway for anyone selling an AI service or tool is uncomfortable but useful. A demo can get you seen. Only a clear, copyable path from the demo to the result gets you paid.