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Right About Now - Legendary Business Advice
Agentic AI Is Here: How ATOMS Turns Ideas into Revenue with Ethan Ouyang
00:16:19
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- [00:00]
A
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, Atoms 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 kind of multi agents. They coordinate, we orchestrate and they run very good efficiency and they deliver end to end.
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B
This is Right about now with Ryan Alford a Radcast Network production. We are the number one business show on the planet with over 1 million downloads a month, taking the BS out of business for over 6 years in over 400 episodes. You ready to start snapping next and cashing checks? Well, it starts right about now.
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C
What's up guys? Welcome to Right about now. We're always talking about what's here, what's now, and what's more now than a I, 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 bright, the coolest. Company's 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. You tell you more. His name is Ethan Oyang. He is the head of U.S. department of Atoms. It's the deep wisdom is the parent company. What's up, Ethan?
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A
Hi Ryan. How are you?
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C
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?
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A
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. So 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 opt, optimize revenue for you. We have SEO agents As well. With all these kind of multi agents, they coordinate, we orchestrate and they run very good efficiency and they deliver end to end.
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C
Really fascinating. Essentially I'd call it a business in a box, like it's turnkey. All done by AI in a way.
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D
Am I describing that right, Ethan?
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C
Is that essentially what this is?
- [02:26]
A
Exactly, yes.
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C
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.
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A
Most AI tools today are still systems. They wait for instructions and optimize isolated tasks, coding or copywriting. I think ATEMS is fundamentally different. Business is not just code or just implementations, it's decisions. Atems run the full decision loop autonomy autonomously, research, planning, execution and iteration. We don't help people, just build or work faster. ATEMS 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 OG actively 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.
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C
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?
- [03:46]
A
Yeah, you can always call me.
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C
Yeah.
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A
Or you can use ATEMS to build your own Agents or own SaaS platform as well.
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D
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C
Up to real life.
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D
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C
That's where Poncho Outdoors has really impressed me.
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D
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C
Some exclusions to instant rewards apply. This is not investment advice and trading. Crypto involves risk.
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D
Check Gemini's website for more details on rates and fees.
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C
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.
- [06:53]
A
We have already seen a lot of use cases that 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 try to build a product I can sell and then atems will the 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 opportunity is 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 thought 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 race mode. You can use the system. 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 with that model, natural language model. And then it start with the execution phase. In the execution phase, we keep human in the loop. Your human can make the critical decisions. Like most of time the agents will just run and implement testing for you. And then eventually you can publish. And then our SEO agents can also help with, you know, like 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.
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C
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.
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A
Yeah, or you can find some people, you can hire some people. They know how. But I think that's more, way more expensive or takes more time and it helps turn time and capital right.
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C
Are we replacing ourselves, Ethan? Is that what's happening?
- [09:16]
A
No, no. It's just the focus is different now because originally when you have idea, you don't even know it's a good idea or not. You don't even know it's going to make revenues or not. You have to get some resources first. You don't need to hire 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 how who gets to build a company or who gets to the 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 probably find something that's better. You are also growing. People are also growing from this iteration.
- [09:52]
C
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 and 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 decision. And that's where the power of this comes from. For the entrepreneurs that are willing to sort of 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. EE comm and D2C makes a lot of sense. Are you familiar with like base 44?
- [10:32]
A
Yep.
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C
I've heard that app building, it's prompt to app. It is all of that capability sort of built into Adams as well that it can literally give you from prompt to visualization. I know that your tool is 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?
- [10:56]
A
Yes, actually that's one of the reason we call our product atems. Our product is built on top of a lot of unique features or like 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 deployment. 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 those like you can preview your product, you can basically store your data. We can support like login and logout and there's a chemistry effect. If we use one ID for users we can also like implement. We can also support the recommendations feature. Right. If you build an E commerce website, we have a building like recommendation engine for using login in and they can see, hey, this product looks like looks fine. I probably want to buy that. But actually that's because we have some building features inside. We have all these features and that's the very core capabilities for our product.
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C
I'm very familiar with base 44. 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 login 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.
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A
Exactly. That's our core capability. That's only part of the end to end flow is more on the execution phase. That's also very important. Execution is very important.
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C
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?
- [12:35]
A
We have our own foundation agents department or this group we have spent years publishing and that really give us the cost efficiency from our acronyms and how we orchestrate our multi agents and how we design our system. Everything is more on the technical side. The those researchers really help a lot. And also on the other hand we model agnostic on the backend. 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 lower cost. That's our advantage and that's pure technology.
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C
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?
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A
Yeah. A AI native company, everybody in the company uses AI. Not just like engineers. In a classic software company you may see like designers and test engineers, back end front engineers. Now we are going to AI native and our designers can also use AI to create the prototypes or docs. And our engineers are more end to end. They use AI to write better performance code and they use AI help to actually co design the system.
- [13:54]
C
I'd 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.
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A
Yeah, there are two aspects. One is from our product side we pay polishing and improving our product from internal. We've been like killing bugs your system. And that will help the system to create less bug or create more reliable or more higher performed output. 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 our 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 majority of users. Because most of the time our users don't know how code work. They don't have engineering background, but that's fine actually. They are our targeted audiences. And so we just try to help them on board and we try to help them feel more better when they see. But they should know it's not the end of the world. You have 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.
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C
How sophisticated can Adams go and who is the ideal customer for Adams?
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A
Our product is a global product and we call it Atoms. We launched in US but actually it's launched worldwide. It's talking on solo founders, indie hackers or small small business or small teams. Who who doesn't have that many res 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 audiences. And in terms of what we can build, I can give you some examples. I already give you a DTC consumer brand example. And there we have seen more real use 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, booking, estimates, scheduling and customer documents in one place. And they they can also. That app can also hand payments, everything you can. So that's why we call Atems. 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 based on your requirement or your request. And we can build with this combination. You can build whatever you want to build almost right? Because 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 like we've seen the Florida based insurance company use ATEMS to build their landing pages and also all these queries on their features inside their company to brand their products.
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C
Ethan, where can everyone learn more about the software? Website details, social media give any of those details for our audience?
- [17:24]
A
We have atems.dev that's our official website 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 deep reason. Talk with me. Just feel free to go to LinkedIn and X and all the social media try to search for us atems.
- [17:45]
C
Thank you for coming on the show, Ethan. Appreciate you having you.
- [17:47]
A
Thank you, Ryan. Thank you for having me.
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C
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. Yes. We're trying to give you the knowledge to put you ahead right now. We'll see you next time.
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D
All right.
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C
About now.
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B
This has been Right about now with Ryan Alford, a Radcast network production. Visit ryaniswrite.com for full audio and video versions of the show or to inquire about sponsorship opportunities. Thanks for listening.