Agentic AI for Entrepreneurs: Build, Launch & Monetize From One Prompt with Ethan Ouyang of Atoms
Ethan Ouyang of Atoms explains how AI agents research, build, launch and monetize products from one prompt — and why judgment is now your edge.
- Atoms runs a full decision loop autonomously — research, planning, execution and iteration — rather than just speeding up code writing.
- Start with a rough idea or sketch; the deep research agent explores the market and returns data and recommendations before anything is built, so you can decide what's actually worth making.
- 'Grace mode' generates a first MVP using several different foundation models so you can pick the version you like and continue from it.
- Because execution is near-instant, your real edge as a founder is judgment and taste — not technical skill or capital.
- The platform ships full-stack: front end, databases, APIs, webhooks, logging in and out, recommendations, Stripe payments and one-click cloud deployment.
- Cost efficiency comes from being model-agnostic — open-source models get used where they can deliver the same result as expensive closed-source ones.
- Mobile app store publishing isn't live yet; it's on the roadmap, so builds are currently web-based.
- Non-technical users should expect bugs and use the docs, blogs and Q&As rather than quitting — patience and the right prompting approach get you through.
But now the execution is near instant. The judgment, the taste become more important. That really changes who gets to build a company or who gets to build a product.
We used to live in a world where the how really mattered because to get it done, you needed to know how. Now, it's more what do you want in a lot of ways.
Staying the same and hoping AI doesn't happen is a loser's mentality.
code faster. We help them make decisions, execute, and monetize more on the end-to-end side. You can imagine in a single prompt, ATEMS can research market, design a product, then build a system, launch it, and they can even optimize revenue for you. We have SEO agents as well. With all these kinds of multi-agents, they coordinate, we orchestrate, and they run very good efficiency, and they deliver end-to-end.
You don't win by following the playbook. You win by rewriting it. 700 episodes deep with the people who actually built something real. No theory. No fluff. No shortcuts. This is Right About Now with Ryan Alford. What's up, guys? Welcome to Write About Now. We're always talking about what's here, what's now, and what's more now than AI. Two letters that you shouldn't be scared of, but you should be maximizing to get the most out of your business, out of your life. It isn't going away. That genie isn't going back in the bottle. But that's why we bring the best, the brightest, the coolest companies doing all kinds of innovative things today. We're talking about splitting things. We're not splitting atoms. We're talking about how you split up and do a million different things with one tool.
I'm gonna tell you more. His name is Ethan Ouyang. He is the head of US Department of Atoms. It's the Deep Wisdom. It's the parent company. What's up, Ethan? Hi, Ryan, how are you? I'm great, man. Thanks for coming on. I always like talking AI. I like demystifying it a little bit. I think we're getting past it. A lot of people are using it. I don't even think we've scratched the surface of how capable it truly can be. I know that's a lot of what you guys are working on. What says you about the landscape of AI in business right now, Ethan? I can give you a brief introduction about our product, Atoms first, and then we can talk more about, in general, about the AI and all these related businesses.
But first, Atoms is a multi-agent system for building revenue-ready products with our autonomous AI team. Instead of helping people write code faster, we help them make decisions, execute, and monetize more on the end-to-end side. You can imagine in a single prompt, ATEMS can research market, design a product, then build a system, launch it, and they can even optimize revenue for you. We have SEO agents as well. With all these kinds of multi-agents, they coordinate, we orchestrate, and they run very good efficiency, and they deliver end-to-end. Really fascinating. Essentially, I'd call it a business in a box, like it's turnkey, all done by AI in a way. Am I describing that right, Ethan? Is that essentially what this is? Exactly. Yes. We have an affluent audience.
They understand business. They understand AI at a high level. I think agentic AI, though, is a little bit misunderstood and not completely leveraged the way it can be. Talk to me about the way Deep Wisdom and Adams leverages these agents within the platform. Most AI tools today are still systems. They wait for instructions and optimize isolated tasks, coding or copywriting. I think ATEMS is fundamentally different. This is not just code or just implementations. It's decisions. ATEMS run the full decision loop autonomously. Research, planning, execution and iteration. We don't help people just build or work faster. They tend to work on their behalf or with prompts. And on the technical level, it isn't a single model or just prompt. It's a system problem, right? What's priority for us is how agents coordinate, plan over no horizons, and actually execute in real environments, not just reason in isolation.
On the other hand, our company and our team have spent years publishing and open sourcing the foundations. We have a website called Foundation Agents.org actually published. A lot of top researchers all over the world, our team, try to gather everybody together and try to focus on the same thing. It's called foundation agents. And our system is built on top of that research and on top of those theories. Ethan, so if I need to train an agent, I need to build an agent, I need to call Ethan. Is that what you're telling me? Yeah. You can always call me. Yeah. Or you can use ATEMS to build your own agents on SaaS platform as well. I'm going to ask for some specifics, Ethan, not like proprietary specifics, but just specifics of capability, because I think people hear these things about agents and decision making, and I don't think they quite understand the level to what you're talking about, because you said most of it to now you can have these agents, but you're kind of still always prompting them.
It's like prompt and prompt and prompt. versus truly training and then real business decisions take place based on that training. Give some examples of how deep that can go with the decision-making of an agent and activities they can actually do based on their own reasoning. We have already seen a lot of use cases or a lot of products built from ATEMS. One example could be like a DTC brand, direct-to-consumer brand. So maybe you are a designer, you have your own taste of designs, and you only have a rough idea and a few sketches. And then you probably upload to ATEMS, and you ask ATEMS, hey, according to what I have, how to build a product I can sell. And then ATEMS will download. multi-agent system just ramp up, right?
They start and then the first start building first because they don't even know what to build with this like limited information. Our deep research agent will start to do a deep research first and try to explore the market and see what's actually the opportunities here in the market and then they will give you some recommendations and solid data for you and you can actually that's the phase that actually you can learn you better understand what you actually want to do because most of the time when you prompt maybe you don't even have the full picture of what the product will look like maybe you haven't saw through yet but this will help you think through and then you approve or say hey this is not what I want you want to do more then you can
iterate you can keep prompting and after you made the decisions you align with agents and they will start building and when you build there's a cool feature called grace mode you can use the system can use different models or foundation models to actually give you the first mvp version of the product and you can choose the one you like most and then you can continue with that version we start the model national language model and then it starts with the execution phase in the execution phase we keep human in the loop human can make the creative decisions like most of time agents will just run and implement and testing for you. And then eventually you can publish and then our SEO agents can also help with optimizing the revenues.
This is an example that we build things and we communicate with people and everything's delivered end to end. People don't have to have a very clear idea. They don't have to control everything. They just need to make key decisions. Yeah, so they become the manager, but not necessarily at a level where they know everything that how it's getting done. They're just controlling what gets done. We used to live in a world where the how really mattered because to get it done, you needed to know how. Now, it's more what do you want in a lot of ways. Yeah, or you can find some people, you can hire some people, they know how, but I think that's way more expensive or takes more time and then it comes to time and capital.
Are we replacing ourselves, Ethan? Is that what's happening? No, no. It's just the focus is different now because originally when you have idea, you don't even know if it's a good idea or not. You don't even know if it's going to make revenues or not. You have to get some resources first. You don't need to have people to actually implement for you. Then you go to the testing phase. But now the execution is near instant. The judgment, the taste become more important. That really changes who gets to build a company or who gets to build a product. You have your own resources, you have your own judgment, your own taste, your own preference. You can go ahead and try and test, and then you'll probably find something that's better.
You are also growing. People are also growing from this iteration. Yeah, you get knowledge. I came up in a time working with brands and doing marketing, spent hundreds of thousands of dollars and months and months. I mean, big brands had that, but now it's more accessible for this research and knowledge that used to be only attainable by large corporations. It's now attainable to guide small business decisions. And that's where the power of this comes from for the entrepreneurs that are willing to sort put their, oh, I got an idea to the side and go, oh, I got an idea and it can actually generate revenue. Talk to me, Ethan, about what we ultimately output here. Because I go to a lot of different places. Ecom and D2C makes a lot of sense.
Are you familiar with like base 44? Yeah, I've heard that. App building. It's prompt to app. Is all of that capability sort of built into Atoms as well, that it can literally give you from prompt to visualization? I know that your tool does more than that, but does it have that capability if you want to do a SaaS-based or develop a tool that's used internally in a company or something? Is all of that here as well? Yes. Actually, that's one of the reasons we call our product ATEMS. Our product is built on top of a lot of unit features or functions. There's so many features or functions living in the software world, right? About database, about storage, about payments. You need to be able to receive money and pay money to buy stuff.
Also about recommendations, about deployments. After the code is built, you need to have a container or deploy your web or your application to the cloud. Everything end to end. And those are the core features we support. You can preview your product. You can basically store your data. We can support like logging and logout. And there's a chemistry fact. If we use one ID for users, we can also implement, we can also support the recommendations feature, right? If you build an e-commerce website, We have a building recommendation engine for user logging and they can see, hey, this product looks fine. I probably want to buy that. But actually, that's because we have some building features inside. We have all these features. That's the very core capabilities for our product.
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I'm very familiar with Base44. I've used it to develop several apps. It's visualizing the app on the screen to the right. You got to write a left prompt, give me a database and log in for admin and users on app platform that looks like this example that does these things. Building it in web app environment that is usable right then. Exactly. That's our core capability. That's only part of the end-to-end flow. It's more on the execution phase. That's also very important. Execution is very important. Ethan, I know that the tool, 80% less cost than a lot of other tools. So Ethan, talk to me about cost here. What can people expect? We have our own foundation agents department, or this group. We have spent years publishing, and that really gives us the cost efficiency from our algorithms and how we orchestrate our multi-agents and how we design our system.
Everything is more on the technical side. Those researchers really help a lot. And also, on the other hand, we model agnostic on the backhand. So basically, we use different foundation models. Sometimes we use open source foundation models, which is way cheaper than those closed source models. So it depends on the task, right? We have a good way to try to deliver the same impact, deliver the same performance with low cost. That's our advantage. And that's pure technology. It's a little meta, to be honest. You're using AI, I bet, to pick what AI you use, model LLM. In a way, that's what it sounds like. Am I hearing correct? Yeah, we are an AI native company. Everybody in the company uses AI, not just like engineers.
In the classic software company, you may see like designers and test engineers, back and front engineers. Now we go into AI native and our designers can also use AI to create the prototypes or docs and our engineers are more. more end-to-end, they use AI to write better performance code, and they use AI's help to actually co-design the system. I'll just say, from personal experience, back to sort of this change of how to do it versus what you get, I find you have to be really good at debugging. That's a skill set when I've been doing apps that's getting underneath the right questions to ask, not how it gets done, but asking in a way that you sort of sort out the things that inevitably come up.
I'm just speaking from experience with Base44, developing tools and apps and things. Inevitably, you run into these mishmash of code that an activity you expect to happen does not happen. And they have self-correction in a way, but it's not always perfect. Help me understand how Adams works through those types of challenges and things when sort of building out tools. Yeah, there are two aspects. One is from our product side, we keep polishing and improving our product. From internal, we've been like killing bugs in our system. And that will help the system to create less bugs or create more reliable or more higher performed outputs. And that's the thing that we are iterating quickly. We're also having a lot of talents joining our company and try to optimize those, upgrade and optimize our product.
That's one thing. And on the other hand, for the user experience, we are posting blogs. We are posting documents and Q&As to the majority of our users, because most of the time our users don't know how to co-work. They don't have an engineering background, but that's fine. Actually, they are our title. audiences. And so we just try to help them on board and we'll try to help them feel more better when they see, but they should know it's not the end of the world. You have a way to make it work, but just need to be patient and they just need to probably use the correct way. We try to give them support, as many supports as possible. Two aspects. How sophisticated can Atoms go and who is the ideal customer for Atoms?
Our product is a global product. We call it Atoms. We launched in the U.S., but actually it's launched worldwide. It's talking on solo funders, indie hackers, or small business or small teams who doesn't have that many resources or domain knowledge, which means most of the time you need a big team to have all this knowledge in the house, in the room. That's our targeting audience system. And in terms of what we can build, I can give you some examples. I already gave you a DTC consumer brand example, and we have seen more reuse cases we collected from our existing users, like a businessman who runs window cleaning business and they used to rely on multiple apps to get things done. And now they build a single application that brings together, Booting.
estimate, scheduling, and the customer documents in one place. And they can also, that app can also handle payments. Everything you can, so that's why we call ATEM. So the business depends on what kind of features or what the actual requirements you need. And then we just provide those features. And our AI agents try to select and try to query, to select and to base on your requirement or your request. And we can build, with this combination, you can build whatever you want to build almost, right? Because both We are not saying we're supporting all these kind of features you can imagine, but we are iterating, right? We keep adding the recommendation feature maybe in the future. So it's not currently not now because it's more on the data side.
We probably need more data when it's actually getting top priority. That's one example. Also, we've seen the Florida-based insurance company use AT&T to build their landing pages and also all these queries on their features inside their company to brand their products. So the tool then can do web hooks and API calls and it can link anything as long as these softwares have an API or talk to one another. They can or use Zapier or that type of thing. It has all of that sort of functionality in it. Yeah, exactly. First thing is the system is a full stack. It has its own front end, which is an ending page and then all these merchandise pages and also the back end, which is databases. APIs and the web groups, et cetera.
And also we have some external integration. For instance, we integrate, you can integrate with Stripe to manage your payments, to accept money, receive money. And also we have the deployment feature. Basically you can iterate on your product and you click on publish, you can see a new version deployed on the cloud and you don't need to worry about too many, anything about any details about the technology. And you just see your product has been refreshed and it's serving new logic, it's serving new requirements. and you asked. What about publishing to app stores? Is this all web-based or can we build sellable iOS or Android, the Google Play Store? How far can we go with this? It's in our roadmap. Everything is depending on the priorities.
I do think there's a little bit of trepidation and fear out there that all of these tools are going to take all of the jobs. And we talked a little bit about that, that these are just tools that we can use. They make us more efficient. I believe the future is bright, but it's for people that adapt. Staying the same and hoping AI doesn't happen is a loser's mentality. It's just my opinion. Not putting those words in your mouth, Ethan, but that's my opinion. I'm direct with my audience. But I don't think it's coming for everyone's jobs. As the saying goes, head in the sand. You need to leverage these tools to make the future that you want. What says you to those that fear these things?
Don't think too much about this. The most important thing is just take the first step and try. It's not that hard. Whenever you try AI products or this new concept, you'll find it actually is not rocket science. It's easy to onboard. It's not that hard. AI creators or build AI products. We're trying our best to make people onboard easily or to use our product. Whenever you get to a point that you can actually achieve something, it can be anything. You can build your own thing without thinking. spending too much money or start hiring someone, or you can really accomplish something with less time and you really gain efficiency, you really find advantages and you really find the value of that, you will get addicted to it.
You will no longer fear. You will just embrace that and you will keep evolving and keep growing. Just relax. Relax and try. I would say relax and try. Yeah, relax and try. Why it takes everyone's jobs. I'm kidding. I'm kidding. Yeah, very well stated. Well stated. Well stated. Don't let the fear overcome you. Just like anything else, you got to get out there and you got to try these tools. And once you use them, you get addicted to the efficiency. We all feel good when you get productive. That's the word I was looking for. Exactly. These tools make you more productive. They get things done faster that took you hours or even just couldn't do yourself. So that once you tap into that, you do get an energy about you for how to leverage them.
Exactly. When you actually achieve something or you really learn something, you feel good, you feel happy, and that overcomes fear. You just keep going and it becomes natural. That's what we do on this show. We go deep. Deep wisdom. Yeah. Ethan, where can everyone learn more about the software, website details, social media? Give any of those details for our audience? We have ATEMS.dev. That's our official website. And you can just visit that website and, you know, you can sign up or you can try free and try to build your own stuff. We have all the social media live. We post on X. It's also called ATEMS.dev. And we have LinkedIn for the reason. Talk with me. Just feel free to go to LinkedIn and X and all the social media.
Try to search for ATEMS. Thank you for coming on the show, Ethan. Appreciate you having me. Thank you, Ryan. Thank you for having me. Hey, guys, you're going to find us. Ryanisright.com. You'll find the full episode here with Ethan and Adams and Deep Wisdom. They're doing some cool stuff. We'll have links to all of the stuff that Ethan talked about and ways to get in touch with them on social media and learn more. Look, it's not time to fear. Time to get your... ass on it. It's time to do it. That's why we're bringing these guests. We're trying to give you the knowledge to put you ahead right now. We'll see you next time. All right. About now. Here's the truth. Information doesn't change your life.
Execution does. So don't just listen to this episode and move on. Take the idea. Make the call. Launch the thing. Fix the problem. Build what you keep talking about building. For more, follow Ryan Alford on Instagram, at Ryan Alford. And watch or listen to every episode at ryanisright.com. This is Right About Now. Now quit waiting. Go win.
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