25:59Ritesh Verma · Interview
I Built a $11k/mo AI App
A 20-year-old UK founder turned a gaming hobby into a niche anti-cheat SaaS, then walked through every decision live.
May 19thThe argument in one line.
Once a company can copy an employee's institutional knowledge into a queryable AI system, the employee's physical presence becomes optional — the only safe position is to own the system rather than be the brain it ingests.
Read if. Skip if.
READ IF YOU ARE…
- You work in tech, product, or ops and have noticed your company pushing AI tools harder than you expected.
- You are a software engineer, business analyst, or product manager wondering whether your role survives the next two years.
- You have been thinking about building a side project or AI product but haven't committed yet.
- You want to understand what clients are actually paying for in the AI services market right now.
SKIP IF…
- You are already running a profitable AI product or services business — the case studies here are early-stage.
- You want a technical walkthrough of how to build a RAG or knowledge-base system; this is a business argument, not a build tutorial.
The full version, fast.
The presenter sold a $40,000 project to build an AI that digitizes a key employee's entire knowledge base — making it queryable by anyone at the company, and making the employee expendable. Three insider stories confirm the pattern is already running at scale: ex-big-tech managers expect Claude Code on every task, a major hedge fund tracks engineers by keystrokes (too many = not using AI), and a banking PM is unknowingly automating himself out of a job. The counter-move is to shift from being a knowledge donor to being a system architect — someone who builds the tools that act on the data, not someone whose data gets ingested.
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00:00 – 02:08
01 · 1/5 — The $40K Project
Hook with revenue dashboard. Explains the AI second brain concept: every process, decision, and piece of know-how from a key employee digitized into a custom queryable AI tool for a roofing/insurance client.
02:08 – 03:28
02 · 2/5 — All We Do Is Use Claude Code
Insider account from ex-big-tech coworkers: managers now mandate Claude Code for all tickets and projects — not using it is penalized. Title card on screen names the tool explicitly.
03:28 – 04:53
03 · 3/5 — Getting Graded on Your AI Use
Second insider story: a major hedge fund (~$1T AUM) tracks engineers and analysts by keystroke count. Excessive typing flags manual work. Connects to the second brain — companies compel knowledge dump, then fire the person.
04:53 – 06:32
04 · 4/5 — The Product Manager Replacing Himself
Third insider: a PM at the 5th-largest US bank builds AI automations, gets promoted as AI product manager, saves thousands of hours — but is unknowingly building the system that will eventually eliminate his own role.
06:32 – 11:03
05 · 5/5 — Where to Go From Here
Counter-move: become the system architect, not the brain being copied. Two mentee case studies (Totsy app, $11K/mo SaaS). CTA to AgentRise coaching program.
Lines worth screenshotting.
- A company that captures its employees' institutional knowledge in a queryable AI system no longer needs those employees — it just needs someone to run the queries.
- At certain companies, too many keystrokes is now a performance flag — it signals you're manually coding instead of delegating to AI.
- The second brain threat isn't future-tense: companies are already paying five and six figures to build them right now.
- An employee who voice-dumps their entire knowledge into a company Notion or Obsidian vault is building the exact system that will replace them.
- The safest position in an AI-automated company isn't the expert whose brain gets copied — it's the architect who decides what the brain does next.
- A food scanner app built by a first-time developer in one month can generate $5,000 in revenue and project a $180K–$600K acquisition path.
- Managers who build AI automations that eliminate their team's work eventually build automations that eliminate their own job — the logic doesn't stop.
- System-building will always be in demand because AI cannot yet build high-scale systems reliably on its own — that gap is the opening.
- Owning an asset that generates recurring revenue gives you a sellable exit; being an employee gives you a severance package.
- The difference between an employee and a founder isn't the tools they use — both may use the same AI — it's who owns what gets built.
Your knowledge is only yours until you document it for someone else.
WHAT TO LEARN
The same AI tools companies use to automate work can be turned against the employees whose knowledge powers them — the difference is who owns the system.
- Companies that pay engineers and analysts to voice-dump their expertise into AI-readable databases are not preserving institutional knowledge — they are making human experts redundant.
- AI adoption metrics like keystroke tracking are already in use at major financial firms; not using AI enough is now a performance failure, not a preference.
- The second brain trap: when you document your full knowledge inside an employer's system on their deadline, you accelerate the timeline of your own replacement.
- System architects — the people who design and connect AI automations — retain value even after the knowledge bases they manage become fully automated, because building new systems still requires human judgment.
- A recurring-revenue software product with $5K/mo in revenue can project a $180K–$600K acquisition value at standard SaaS multiples, making it a more transferable asset than any employment record.
Terms worth knowing.
- AI second brain
- A searchable AI system built on the documented knowledge, decisions, processes, and institutional memory of a specific employee — designed to persist and be queried even after that employee leaves.
- Context OS
- An alternative term for an AI second brain; positions the employee's knowledge as a queryable operating system for the company rather than a personal note-taking tool.
- Claude Code
- An AI coding assistant from Anthropic. In this video it is referenced as the tool big-tech engineering teams are mandated to use for tickets, projects, and assignments — with non-use being penalized.
- Keystroke tracking
- A method reportedly used by at least one large hedge fund to measure how much engineers and analysts are manually typing — high keystroke counts signal manual work rather than AI delegation.
- AgentRise
- The creator's coaching program, described as helping participants build AI service or product businesses to $5K–$50K/month within 60 days on a pay-only-if-you-earn basis.
Things they pointed at.
08:06productTotsy — Family Food Scanner
Lines you could clip.
00:16
“This means that we will need fewer and fewer humans every single year.”
03:17
“If you're not using AI to do the work for you, you're getting penalized.”
03:38
“They're getting tracked by how many keystrokes they're doing on the computer.”
07:04
“You can stop being an employee a company can replace and start being the person who builds everything.”
07:30
“System building will always, always, always be in demand. Because for AI to be able to build systems at a high scale, it needs to advance a lot more. It's just not there yet.”
Word for word.
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analogystory
00:00I closed a $40,000 client to build something that is absolutely terrifying, and I'm looking at it right now. See, it's an AI that copies the brain of a real human.
00:09Every process, every decision, every piece of know how locked inside someone's brain is all dumped into an AI tool that I'm custom building for a client.
00:19So if that employee ever were to leave, his brain stays. And here's a part that should make you sit up. This means that we will need fewer and fewer humans every single year.
00:28I'm a software engineer who quit a big tech job to build stuff like this for clients. And in this video, I'm gonna show you exactly what I built. The insider stories about old coworkers that telling me about what's really happening inside these big companies that are investing heavily into AI.
00:42And the one move that puts you on the right side of all this instead of getting replaced by AI and getting taken advantage of. So let me actually explain what I was paid for because once this company gets their hands on it, you'll see where the job market is heading. My client was a roofing and insurance company, very old school.
00:58In fact in fact, the entire business runs on a handful of experienced people who they pay a crazy sums of money to so they don't ever leave the company. And these people keep the business going.
01:09They know how the entire roofing industry works. They know how quoting for roof work looks like. They know how insurance angles work.
01:15Everything that is stored inside their brain is what makes them valuable. But that's where the founder of the company, I won't say his name or the company's name, he told me, what do I do when these people quit? If this person right here were to leave the company, my company would not function.
01:28And that is alarming for anyone who's running a company. If that employee were to leave, his brain were to go with him, and that company would be back at square one, and they would have to spend thousands, tens of thousands of dollars on training, hiring new talent, and seeing if they can be half of what that key person was.
01:44And this is where the idea of the second brain came about. What if when that employee leaves the company, you can take their brain.
01:52So even if their physical body is gone, all the information that was in their brain stays with company. I'm not talking about maybe some projects or SOPs they have written or built. I'm talking their entire brain, all the information they ever known or ever amassed, all the documents they ever created, absolutely everything end to end is stored within some sort of database that is queryable from other people in the company.
02:14So let's say, for example, you are a sales manager and you have years of sale experience, but you were to leave the company. If your brain stays, the next sales manager can just copy exactly what you know from your brain that's still with the company. And the opportunity of a second brain or some people might call a context OS is insane.
02:30I mean, I'm getting paid $40,000 to do this for a company that's medium to large size, but there are companies that are way bigger, enterprise level that are probably spending 6 figures for this. And you, you are someone who can build a second brain literally today if you wanted to. Now how can you do it?
02:44We'll cover that in a bit. Now the part that really alarms me about all this is that I used to work as a big tech software engineer at a very big company in New York City. Uh, you all know this.
02:54Guarantee you all have heard this company's name, but, again, I can't say it because they're gonna flag me or whatever. But my old coworkers from my this big tech company, they tell me all the time that all they do is use Cloud Code now for all their tickets, all their products, all their assignments. Their managers even expected to be using Cloud Code, and if they're not using Cloud Code, they're doing something wrong.
03:11Can you believe that? We're in a time where if you're not using AI to do the work for you, you're getting penalized. In fact, one of my coworkers who now went to another company that's probably the biggest actually is the biggest asset company in America.
03:26They own, I think, over $1,000,000,000,000 in assets. Huge hedge fund.
03:30And, again, you've all heard about this. They're actually global at this point. They are getting tracked on how many key strokes they put in to their computer.
03:38So basically, the amount of times you're typing on the keyboard, and if you're typing excessive amount, they're assuming that the engineer is manually coding and not using clawed code. So in fact, they're getting penalized for manually coding because in today's age, if you're manually coding, then that means you're not using AI efficiently.
03:55And this just doesn't apply to engineers. Obviously, was engineers, my coworkers are also engineers, but some of my friends who are business analysts, the same thing is applying to them. They're getting tracked by how many keystrokes they're doing on the computer.
04:05They're expected to be talking directly to the AI, for the AI to do all the heavy lifting, and if they are caught not using AI enough, they're replaced. So now when the manager tells you, hey, what I need you to do is I need to dump all your information using some sort of voice dictation tool to talk into this Notion database or inside this Obsidian vault, dump all your information, all you everything you know, all your emails, dump absolutely everything.
04:27If you don't do it, you're gonna get penalized. But if you do do it, then what's happening is all that information in your brain right here that makes you valuable, the company now has. So if they were to fire you tomorrow, it nothing really matters to them because they still have all the data and all the information you you have in your brain.
04:43So why do they need your physical body when they can just have AI operate on that data and do all the work that you were doing anyways? Now here's another insider story as you already heard one from my personal ex coworkers, and now you've heard one from a big hedge fund.
04:55There's a product manager that I know who's slowly replacing employees at his company at management a level, and eventually, he doesn't even know this yet, he's gonna replace himself. See, he's a product manager, meaning he's managing products at the what is the company?
05:09What what are definitions? He's a product manager, so he's managing products. No.
05:12What he's basically doing is he's in charge of the product's entire cycle from development to be pushed to production, to making sure customers are receiving it well, the entire cycle end to end. Now, a lot of the processes in between require AI automation or they require a lot of human effort, but he's slowly building out AI automations that replace the human effort that's needed for that process.
05:33This is extremely important because he is getting promoted very quickly inside this company, which is the fifth largest banking company in America, I believe, because of this success that he has as now what's called an AI product manager. And he's building AI solutions for his company internally. And he's seeing his company thousands of hours every single month, which is in insane, but because he's salary cap, he's not getting any financial bonus.
05:54But he's getting promoted, so I guess that's his pros and cons. But that's beside the point. The point is that he's replacing manual tasks that take human effort to do, which allows his team to do other things.
06:04But at a certain point, when you create enough automation inside of a company, what happens is that company no longer needs as many humans in that department to do the task. And for the humans that it plans on laying off, as long as that they're able to retain the data of a human, as long as they're able to retain the workflows of the human, how the human operates, why the human is able to produce the way he or she does, they can let go of that person at any time because they have all the data, they have all the information, they have the brain.
06:31And slowly but surely, my friend will eventually build a product for his company internally that replaces himself, and that's when he will also pop the lid off. So here's a part that nobody at these companies wants you to figure out out because you are you're slowly giving away all your information, all your knowledge to the company so they can replace you at any time.
06:48There's also a way where you can take advantage of this. See the exact same AI that's replacing employees, you can point to the other direction. Instead of being the brain that gets copy, you become the person building the systems that are using the brain to operate on x y z tasks.
07:04So you're the one delivering value instead of just giving value to the brain. And this is kind of what my friend is now doing as an AI product manager at his company where he's constantly building more and more systems where even if the second brain that this company is developing gets, you know, very smart and scaling up, it has a bunch of mini employee brains inside of it.
07:23He's built so many systems where they'll see him as a system architect who can use that information in second brain actually apply it for the company's use cases. Because there's no point of having all this information of all your employees and your ex employees when you can't really act on it. Right?
07:36That's where system building will always, always, always be in demand. Because for AI to be able to build systems at a high scale, it needs to advance a lot more. It's just not there yet.
07:45So you can stop being an employee a company can replace and start being the person who builds everything. Let me show you some examples. One of my mentees, Neymar, who I worked with one on one for the last three months, he graduated from MIT, one of the best universities, if not the best university in the entire world for tech and computer science.
07:59This means that he could easily land a multiple 6 figure job, probably $304,105 $100,000 a year job. But instead of working nine to five, he built an app called Totsie, which now has over 51,000 followers on Instagram.
08:10It's a food scanner for kids, and it allows parents to check which foods and which have switched nutrients, which toxins to accurately judge whether they should buy that food for their child. In the first month of his apps launched, he made over $5,000, and this was his first app he's ever built.
08:24Now follow the math because this is where it gets really fun. As a twelve month projection, if you're earning $5,000 a month, you're expected to make $60,000 a year. Now apps like this don't just generate revenue, they also sell for acquisition.
08:36For example, if you exit an app like that that's earning $5,000 a month, you're typically looking at a three to 10 x multiple on annual revenue. So multiply the annual revenue that you have, which is $60, by three to 10 x.
08:48You're looking at a 180 to $600,000 acquisition. In fact, one of my software's got a $200,000 acquisition following the exact same principle.
08:56And see how he's not waiting for a company to look at how many keystrokes he has to see his AI coding? He's building an asset that is sellable. And he's not the only one.
09:03Another client slash mentee that I work with, Ben, is running $11,000 a month SaaS. If you do the math on that, he's projected to make a $121,000 a year, which added three to 10 x multiple is over a million dollars on the high end.
09:16This means that he can literally walk out with a million dollar buyout potentially if he finds the right buyer. Now that's the difference. The employees whose brains I copied for $40,000 and built this system for my client, they don't own anything.
09:29They don't have any valuable assets. If the company would replace them, they're on their butt, and they can't do anything. Neymar and Ben, they own everything that they built.
09:37Yes. They may have used AI, and in fact, same the AI that I'm using to build a second brain, but they are the founders. They are the ones who are owning the asset, which is whatever product they built.
09:47When the company owns all your assets, you're just a cog in a wheel who's waiting to get brain dumped into a second brain then replaced very quickly. And I know it's because I'm literally bony right now. Now this is the entire reason I started my coaching program, AgentRise, where I've coached now 220 mentees across the entire world where I help them build their own assets, their own AI tools, their own apps, and scale them to multiple $5.06 figures in revenue.
10:11Neymar and Ben are just two examples. See, this is where you get to choose which side you're on, but you actually have to choose. You can't just wait until you get replaced by your company's second brain.
10:20You have to act on the current market that we're in and be ahead of the AI tools, be ahead of the AI opportunities, and take advantage of everything that is out there in front of you. Build your assets now. Because at the end of day, I'm gonna pay $40,000 to help a roofing insurance company become the best in their entire industry.
10:37And, of course, I took the project, and, of course, I will do it. And I will save them costs. I will help them fire some of their employees.
10:43Because at the end of the day, for any business, why would you spend more than you have to? It just doesn't make sense. So it's now up to you to decide whether you wanna give your brain to AI or use your brain to build valuable AI assets.
10:55If you wanna see exactly how to start building your own AI asset, your own AI app today, solo, no team, step by step, watch this video next.
The Hook
The bait, then the rug-pull.
The revenue dashboard was already on screen before he said a word — $46,980.99, glowing in the corner of the frame. Then: 'I closed a $40,000 client to build something that is absolutely terrifying.' Eleven minutes later, you understand exactly what terrified him — and why the thing he built is coming for the person watching.
Named ideas worth stealing.
03:42concept
The Second Brain Trap
- Company mandates knowledge dump into Notion/Obsidian
- Employee complies to avoid penalty
- Company retains the data
- Employee becomes expendable
The cycle by which companies extract institutional knowledge from employees under the guise of AI adoption, then no longer need those employees.
Steal forframing any conversation about the real cost of over-documenting your expertise inside an employer's systems
07:04concept
Brain Donor vs System Architect
- Brain Donor — provides knowledge that gets ingested and replaces them
- System Architect — builds the systems that act on ingested knowledge
The two sides of the AI replacement equation. The presenter argues only the architect role compounds in value over time.
Steal forany positioning argument about employees vs. builders
08:23model
SaaS Acquisition Math
- Monthly revenue x 12 = ARR
- ARR x 3-10 = acquisition multiple
- $5K/mo → $60K ARR → $180K–$600K exit
Simple back-of-napkin math showing how a small recurring-revenue app translates into a sellable asset.
Steal forany pitch about why building a product beats staying employed
How they asked for the click.
VERBAL ASK
10:00product
“Make an Extra $5k-$50k/mo With Your Own AI Business in 60 Days — or Pay Nothing”
Landing page shown full-screen for several seconds. Risk-reversal guarantee ('pay nothing') prominent. URL agentrise.io also in description alongside free training and indraos.ai for custom builds.
MENTIONED ON CAMERA
FROM THE DESCRIPTION
PRIMARY CTAWhere the creator wants you to go next.
OTHER LINKSAlso linked in the description.
Visual structure at a glance.
