AI Launches a Business in 40 Minutes with Samruddhi Mokal of Pace Labz

Speaker A: Do you believe in this idea that one day we're going to have a single person billion dollar company?

Speaker B: Yes, I believe that. I strongly believe that like AI is going to make one person billionaires and gen con companies imagine creating an entire edit and automation with just one prompt. So that is going to be a lot of work reduced and the execution speed is going to be at least 10x than what it is right now.

Speaker A: Samruti, welcome. So what are we going to learn today?

Speaker B: Today we are going to see how to launch your business in next 40 minutes. I'm going to show you exactly how to create a video ad that looks like we spend six figures on production and a working voice agent that handles your customer calls and closes sales. And this is going to be like without even having to go to WAPI and create your voice agent. I'm going to show you how to use WAPI MCP and you just one prompt in CLAUDE and your entire voice agent is built on that.

Speaker A: Oh my God. This is very exciting, very exciting. So we're gonna build a business in 40 minutes. This is, this is a very special episode. Build a business in 40 minutes and this business is gonna have customer agents that are gonna talk and then we're gonna just create like beautiful ads. Right? And so I think this episode is gonna be an example of what AI can do and also this whole idea that there can be. And maybe I'll get your take on this which is do you believe in this idea that one day we're going to have a single person billion dollar company?

Speaker B: Yes, I believe that. I strongly believe that like AI is going to make one person billionaires and genuine companies.

Speaker A: So this is this episode everyone so uh, very excited to dig in. Why don't we just get right into it actually. So what is, so uh, what are we going to see first? If you want to share your screen and walk everyone through it.

Speaker B: So what I'm going to walk you through is we are going to use Google's AI Studio, uh VO 3.1 to create the ad. And um, we are going to use a specific prompt framework and a structure that creates these production level like six figure production level ads. I'm going to use Claude desktop which is, this is my browser. So you're not able to see the Claude desktop but we are going to connect MCP of WAPI using Smithery and we are going to create the voice agent on wapi. So uh, giving a background about.

Speaker A: Okay, so just take a step back. So just to take a quick step back to make sure, everyone understood. So the way that the voice agent we're going to use is using a product called vapi, that's vapi, which is just Voice API. And so that's going to be the voice agent. And then we're also going to use a tool called Smithery. And what does Smithery do?

Speaker B: So Wapi, you can think of it like any 10 for voice agents or a platform builder for voice agents. And um, Smithery is a tool or uh, Smithery is not exactly a tool. Smithery is a marketplace where you can find all these mcps. So I'm going to use um, npx command to install WP's MCP server on Claude desktop and we are going to uh, run the uh, prompt on Claude to create our voice agent on mobi.

Speaker A: Okay, I see. So Smithery just uh, make sure for the non technical audience to get them there. So Smithery is just this platform that gives you access to a whole bunch of MCP servers. And what that means is say that you have Airtable or you have Linear or you have Google Analytics, all these things. If you want to use AI agents to talk to them, you need a protocol called MCP. So it's kind of like an API, except your agents like Claude or ChatGPT can use MCP to talk to these external services. And so all of these things are listed on this site called Smithery. And we want to build something with vapi. But in order to do that what you're saying is we're going to get the MCP from within Smithery Smith so that then we can talk to vapi which is going to build our voice agent.

Speaker B: Yes, exactly. Uh, yes. So we were on Wapi's uh, MCP server and we are talking about how MCP Server is used. So to give a brief understanding, like I went on WAPI's MCP server and these are all the tools that this MCP server provides in the backend what these tools are. These are each separate uh, APIs that are going to be called when we are going to give our prompt. For example, if I'm going to ask what are the voice agents that I've built on my wapi, it is going to use this API call and it is going to list out to me so you can think of MCP as a combination or a club version of all the API calls and the MCP decides which API to call when based on what the user request is. So first um, starting with the add part I'm going to go to Google's AI Studio. I'm going to go to Playground Video Generation. I'm going to select this VO 3.1, okay.

Speaker A: And Google, uh, AI studio. So for most people who have a business Google plan, you're going to have access to this. You can just get to it by going to aistudio.google.com and the model we're using right now is VO 3.1, right? That's one we were using.

Speaker B: Yes.

Speaker A: Or is it just VO3?

Speaker B: Yes. And yeah, I guess.

Speaker A: Uh, so that's the link is like Rocky going, okay, amazing. So yeah, okay, so we're in VO3. What do we, what, what do we do next?

Speaker B: So every business needs marketing. And a, uh, video ad like what I'm about to show you would cost you like tens of thousands of dollars at a traditional agency like production, creo, locations, editing, revisions, weeks of work. If you're going to do it using just one prompt, you can use this prompt structure for any type of ads that you want to create. So I'm going to copy this prompt and I'm going to explain in depth what this prompt actually is. So there is a prompting framework called as JSON prompting. So this is going to be our prompt. It consists of, um, description, style, camera, lighting, environment, elements, motion, ending, and text. So going in depth of what this is, most of you might be aware of JSON if you're not aware of JSON. JSON is a format in which we can store data. It is stored in key value pairs. For example, description, here is the key. And then we are going to use colon to separate what is the value. This is the value. This right here is the value. This is the structure that is used for very specific type of image generation or video generation models. You can use this exact framework in your prompting, which is going to be description, which is going to tell the story, what happens scene by scene. Like, this is your script, beginning, middle and end. The AI needs a narrative arc, not just a concept. Second is the style, the visual feel. This tells the AI what world we are in. Same story short and horror. Lighting versus golden hour looks completely different. The third part is the camera. The specific movements of the camera. Like this is your cinematographer. Where's the camera? How does it move? And like amateurs, forget this. Professionals are obsessed over it. Next is the lighting, how light behaves and changes. Think of lighting as emotion. We start soft, then brighten as the food arrives. The AI needs to know all those shifts. Next is the environment, the setting and the details. This is your production design. Like what's in the frame, like wood, textures, plants, sunlight, details that are going to make it feel real. The next is the elements, specific objects and actions listed out. This is your short list. Every item the AI needs to include, explicitly stated, no assumptions. The second last part is the motion. How things move and transform. Like what happens in what order. The swipe, the explosion, the reassembly, frame by frame. And then the last is the ending. The final frame. Like this is your.

Speaker A: So, uh, so I have a qu. A question. Yeah, so just a question on this. So we're, we're doing this right? We have all of the different, you know, elements in the script. Now did you, did you actually type this out or was the script AI generated too?

Speaker B: Uh, so I had these parts that I mentioned. For example, uh, what is supposed to be the key and the rest of the part is AI generated. Because this is a very comprehensive part, it will take me a lot of time, plus a lot of knowledge about the production and all those things to get these details. For example, if we go to the, um, camera here, like starts low at this, then ik So I think the

Speaker A: conclusion here, so we have a script so we can press run to build it. And so, but, but I think like the conclusion is that, um, you know, these days you shouldn't be writing your own prompts. You shouldn't be writing your own scripts. You can obviously guide these things and provide the, you know, the guardrail is the beginning, middle and end. But you, you want to let AI fill in the details and then you can obviously, you know, prompt back and forth to make it what you want. But if you want to make a really good video, actually like an AI can prompt it better than you can.

Speaker B: Yes, definitely. So usually what I personally do is I have created my own cloud projects, whether it's for like, uh, sales proposal generation, my personal strategic advisor or prompting, they have all these knowledge bases. So for image and video generation, I have a separate, um, project which helps me draft all these prompts in the right format. This is going to take some time, roughly a minute to generate this video. If you want to change the resolution and all those things, you can change it from here. We're going to make it a, uh, second video ad. Also, if you're going to create this video, you'll have to add your API key that is going to be a prerequisite to generate these videos. You can get your API key from here. This is the ad that our, uh, A.I. has generated. Let's check it out. Usually doesn't take this long. But right now probably it's back. So this is the added generator, including the voice and the textures, the movements, the camera angles, everything.

Speaker A: I mean uh, this is incredible. It's crazy. And I mean again it looks super uh, realistic. Maybe the part where the food is going into the air and falling on the floor, maybe not as much. Uh, that part, that part does look a little bit AI generated. But again this is a first prompt. So what I would then do is take the script and then talk to AI and say, hey, you generated this thing. But the last part looks AI generated. So how might we change that so it seems more realistic and then take the new script and this is how you can edit back and forth.

Speaker B: Yes. So ah, usually uh, by creating videos in the first prompt, it is going to give you this. If you are going for lift, sync and a few more features, you might have to take two or uh, three shots at the prompting and you'll get a better ad once you keep adding. For example, let's try another prompt which

Speaker A: is, I'm thinking in the interest of time, uh, maybe we go to the next thing.

Speaker B: So we created our ad. The second part that we are going to create is we are going to create a voice agent using WAPI's MCP server. So let's say we have our ad running, we are getting our leads and they are calling us and this voice agent is going to convert those leads. What you are going to do is we are going to connect our WAPI's MCP server which I have already installed. But to give you an idea how to install it, you have to go to go to your terminal and use the command that is given in your Smitheries MCP server which is going to be NPX command. Also this is how to install WAPI's MCP server is go to your terminal, copy this command that is going to be seen here. I'm going to choose Claude Desktop where I'm going to install copy it and run this command and it is automatically going to install the entire MCP server. Once you install that, you'll have to go to Wapi and get your API key. From here, just paste the API key and press Enter. It will do the entire installation for you. Once the installation is complete, go back to your CLAUDE desktop and you should be able to see WAPI MCP Server in your Tools section of claude. And this is going to be specifically on Claude Desktop. You won't be able to see this on Claude's web version. So if I click on this plus button and I go to connectors. I'm able to see this WAPI MCP server here. So I'm going to give it a prompt of creating our voice agent. So I'm going to name our company Fresh Pause for the time being. So this is our prompt. Create a voice agent on WAPI for Fresh Positive, a premium fresh dog food subscription company. These are the company context agent role, primary tasks that it has to handle. New customer inquiries, existing subscription support, common questions to handle, and um, call flow for new customers, Call flow for existing subscribers, and tool guidelines. I'm just going to press enter.

Speaker C: Hey everyone. Just a quick pause on today's episode to tell you about my daily day job. In addition to this new way, I'm the CEO of a company called Fellow AI and Fellow is an AI meeting assistant. It joins all your meetings, it summarizes them, tracks the actions and the decision, and does that better than any other

Speaker A: tool that you've seen.

Speaker C: We've spent a ton of time making sure that the meeting notes and summaries and action items that come out of Fellow are the most accurate, the most precise. Precise. It beats any human. You have to try it. But in addition to that, what makes Fellow different is that it is the first AI note taker built from the ground up with security and privacy in mind. This means that you can use it for all your meetings. Not just the customer facing ones, but also the sensitive ones. Things like one on ones and executive team meetings and those QBRs and everything in between. It's got really good judgment. So for example, if you see start a meeting and you're talking about some social stuff that you don't really want on the record, that's gonna get emailed to everyone afterwards. Velo just knows it just doesn't include those things. Or say you have something that you talked about and later on you realize oh man, that shouldn't have been there. Makes it really easy. You can go back to the meeting, select that part, delete it, and then it's gone from the record. It connects to all of the other tools you use in the organization, whether that's Slack or Asana or HubSpot or Salesforce or Linear or Jira or Confluence. Whatever it is, Fellow integrates with all those things. I think the best part is that Fellow also acts as an AI Chief of staff because it sits on all the meetings and the conversations that you have access to. You can ask it really cool questions such as what are the biggest opportunities in my company? What are the bottlenecks in engineering and Fellow Just pieces together information, sees trends and it can answer those sorts of questions. It can even do things like hey, based on all of the one on ones that I've had with this particular person, can you create them? A performance review and it can do things like that too. And the sky's really the limit. What I really wanted you to do is have the opportunity to try out

Speaker A: Fellow Check it out.

Speaker C: And we're making a special offer available to all our listeners. So just go to Fellow AI this new way to try Fellow. There's a discount code in there for you if you decide to continue with it. Either way, I would love for you to try it and let me know what you think. And with that said, let's go back to the episode.

Speaker A: So that's pretty cool. So this, these are the instructions for the, for the voice agent. And it's as if like you hired someone who's going to answer the phones and you want to give them some instruction. And so this is the, the idea behind that.

Speaker B: Oh yes. So every time I um. It is getting that API, it is asking me for permissions. This is how MCP server is going to work in the backend and it's going to create an entire voice agent for us which is just a few minutes, roughly two or three minutes max. That's created a voice agent for us and it is. All right, so it has given us what are the details. That is agent, name, voice. It has assigned automatically LLM M. Also it has assigned transcriber and the numbers that I already had. That is wired video and this is the test number. It is giving us instructions. Go to your WAPI dashboard phone numbers and. Okay, perfect. I'm going to switch back to my VAPI and let's see what it has created. So I'm able to see this voice agent that it has created.

Speaker A: Okay, so that was pretty easy. I mean it was literally one prompt and so now it creates this voice agent. So now we're back to the VAPI interface. And so how do we test it?

Speaker B: So I'm going to click on this talk to assistant button and it's going to start the call automatically. Hi, thanks for calling freshpaws. I'm Luna. Are you looking or are you an existing member? I'm looking to get started. Wonderful, I'd love to help. Tell me a little about your dope. The name is Lily. I think it's catching up my microphones from both the sides which giving some error. I'll test again.

Speaker A: But no, no, this is really, really cool. I think uh, I think this is good. I mean it's amazing. So maybe the sound doesn't come through as well, but it's basically like a full on voice agent and it's going back and forth and, and it sounds very natural. Uh, so the question is, so now that you have this, so say that someone went through the steps through Claude, was able to use the MCP to connect to VAPI to build the voice agent. Now that the voice agent is there, how do you deploy it? How do you actually make a phone number that you have connect to this agent?

Speaker B: So I already had two numbers. If I would have given my Claude a prompt that I have to connect this number. You can get the test numbers from here. You can click on create phone number and Wapi gives you free phone numbers. So they have limit ah per account. So you can just use a phone number from here.

Speaker A: Oh wow. This is like um, again so easy to do. So you literally, you go to vapi, you get a phone number and then you just assign an agent that you created to that phone number. It just makes it so easy to do. This is incredible.

Speaker B: MCPs are like just change the speed of all the things like especially connecting them to Claude or like some other AI tools or white coding.

Speaker A: Yeah, it's super interesting. And you know the conclusion that I'm drawing here is that more and more people are not going to want to learn your interfaces. Like it's just so much work to learn where a specific thing is in an interface and you just want to describe the action that you want to take and you want your main AI agent, in this case claude, to just go and do the work and just set it up in the way that you want. And you know like you can always go to the interface and check on things, but really the interface is starting to become less relevant. And it almost seems like we're entering a world where software is now being designed for agents themselves and not as much for humans. Humans will use the agents, the agents will use the software.

Speaker B: Yes. And like lot of automation tools are also launching there MCP servers which is going to be more crazy. Like this was just voice agent, but imagine creating an entire edit and automation with just one prompt. So that is going to be a lot of work reduced and the execution speed is going to be at least 10x than what it is right now.

Speaker A: This is uh, this is incredible. So that makes sense. And so far we've seen how to create a video using VO3, we've learned how to create a voice agent I know that you were going to talk to us about the idea of memory. I think you were using something called MEM0. What is that?

Speaker B: So MEM0, you can think of it like a memory layer for your apps or agents. For example, let's say you're using ChatGPT for some of your chats and then you feel that Claude is a better model later on. But you need that context. So MEM0 or super memory is going to store that context for you and you can very easily switch between different apps. And this is also if you are using memory layers or your phone or like emails or telegram, WhatsApp etc. It is going to have a context of what you had talked with that person. Let's say I'm talking with same person on WhatsApp and on email. I don't know what I talk exactly on which communication channel. I'm m just going to say that I want this specific detail and just based on this detail, these are the next steps that you want to take. And MEM0 is going to be extracting the exact that specific moment from any app that is there and it is going to take the next, help me take the next actions.

Speaker A: So give me another example of this. So in a case where MEM0 became very, very useful, like what's a recent example of how you ended up using it?

Speaker B: So I sent a uh, invoice on email and I, I use two channels. Once I convert the list we usually use uh, WhatsApp because a lot of people prefer WhatsApp. And this uh, was the second invoice and I didn't uh, exactly remember whether I sent it on email or whether I send it on WhatsApp. So I just wanted to make sure I had sent that invoice to do a call up and I just asked it like can you give me that invoice for the specific mind? And then it extracted that specific invoice and gave it to me.

Speaker A: That's awesome. So is it like a memory layer or how is that different from say Claude that might have access to through MCP through both WhatsApp and through email?

Speaker B: Uh, so it is like a memory layer. But if you go to Claude's or NCP servers, Claude is, if you're using, let's say if you're using Claude in Claude, we'll have to stack those NCT servers. For example, I'll have to say every time in my prompt that check these channels first, only then it will be able to answer that. Whereas in memory layers it is going to have memory of everything. I do not have to specify that. Check this, this, this. And uh, if I'm using MCPS on Claude, there is a limitation to the number of MCPs you can use. Not exactly a limitation per se, but then after a point it starts to slow down and it, uh, starts hallucinating. So it is better to have less MCP servers. So that is where the memory comes into the picture.

Speaker A: Okay, so how does it put it in the memory? Like, is this just like search or is it that every time you interact with an AI tool, it remembers something from it? Because in this case you sent something via email, so that feels more like a search activity. So how is it memory in the that case?

Speaker B: Uh, so uh, it connects different tools and it creates its own memory, um, knowledge graph in the background. So it is a search semantic search. I'll say from where it extracts things from its memory using the knowledge graph that it has created.

Speaker A: Hey everyone. Hope you're enjoying the episode.

Speaker C: One of the common things that we hear is, hey, you all talk about all these different tools, you walk through these demos. Sometimes it's hard for me to follow along. We decided to do recently was take all the things that we talk about, put them in a weekly newsletter, we literally list all the tools we link to them. And any demo that we walk through, we break it down step by step, put it in this newsletter, so it's super easy for you to follow along. And the other nice thing is that if there's someone on your team that you think could benefit, they're working on that subject area. They could use a little bit of AI injection into their workflow, send them the newsletter, send them that particular episode. We make it super easy to do that. It's free to sign up. All you have to do is go to this new way dot com, enter your email address, and you'll get this weekly email from us. Hope you enjoy it. With that said, let's go back to the episode.

Speaker A: Okay, so as activities are happening in these other tools, uh, so is MEM0 more like, would you say it's a competitor to Glean? I don't know if you've heard of Glean before.

Speaker B: Ugly. Not exactly. I have copy and I've heard of

Speaker A: memory, so that's great. So, uh, that's another cool tool, uh, to use. So now I have a few other questions that I thought would be good to get your take on. Uh, so you showed these things, I mean, other things that we could have done. We know, for example, if you are creating a business, you might want to create a uh, business plan, you might want to create a slide deck. And so now through the Gamma mcp for example you can create a slide deck just through Claude. So this idea of MCPS is very interesting and as we showed today through Smitheries uh, you can actually go and you know get the list of MCPs. So that's a really great place to look. Maybe. Let me ask you this question. So in the world where it's becoming easier than ever to vibe code, you know to use MCPS in this way, is there really like what, what do you think will be the future of products like N8N and some of the, the workflow tools? If it's just as easy to describe to Claude to go build a program that will you know use MCPS and connect to various things. What do you see happens like fast forward you know two years. Where do you think companies uh, like N8N end up? Do you think they're more valuable or less valuable? How do you think so I think

Speaker B: companies like any 10 uh will still exist because uh Anything is mostly like workflow automations. You can use, definitely use Claude Desktop and other things and NCP servers to create these tools. But automation specific platform, they have their own strengths and moving forward it is going to be pretty simple creating the automations as well. Right now we have to create separate modes and connect. But Anyton recently launched Anything's beta version where you just describe on a prompt M and it creates the automation for you that is still the beta stage but uh, it is out there. So it is also going to be like describing and the workflow is getting ready so the execution is going to be way faster. But I believe a lot of people are going to get stuck in technical side of it because whether it's automation or whether you're using MCP servers or anything technicalities will still be there. For example uh, how to use API keys if you're just giving a prompt and a non technical person is trying to implement that prompt. The example that I showed in Today's MCP server, WAPI's MCP server I had to give it API key. If people do not get those concepts they won't be able to um, use these tools at the full capacity. And since automations are white coding it is a connection of multiple tools and the only way to connect these tools is going to be APIs or ah, webhooks. So understanding how the technology works is going to play a very important role in this.

Speaker A: It's super interesting. So your view is that there still is value because you're going to have a non technical audience. And these workflow tools still make it easier because the nodes are there. You know, you drag a box and that box, you know, abstracts a bunch of other functionality. And so that's why, you know, just push back a little bit. It's interesting. I don't know if you've been following openclaw and you know what you can, what you can do there. It's crazy because, you know, you kind of talk to OpenClaw about the thing that you want it to do and then if it needs an API key, it'll open up your browser, go to the website. Heck, it can, you know, go to the right page, create an API key and bring it back. Right. And so I think the world is changing. It's kind of hard to predict. I do agree with you. It is hard to predict. One, one thing that is interesting about what I like about NAN and other workflow tools, Zapier, is that you can almost like in one view see how the system works and get like a visual understanding of what's there. Potentially makes it easier to troubleshoot. And then again, if I were to take the devil's advocate view of what I just said, I could say like, well, yeah, but you could take any program and then get Claude to generate a visual, you know, view of it and you can do the same thing. So it's going to be really hard to tell. It feels like there's going to be a convergence between the workflow tools, the, you know, the programming tools, uh, even design tools like figma. All these things are, I think, starting to. And we didn't even mention the tools like Airtable, uh, which are arguably like application builders too.

Speaker C: Right.

Speaker A: So it feels like there's going to be a convergence all across all of these platforms.

Speaker B: Yes, definitely. Like there are lots of tools coming out and the specific point of openclaw, openclaw is like, we can call it like um, a wrapper of mcps. Last year we are getting a lot of AI wrappers and now since mcps are out there, we are getting a lot of MCP rappers out there.

Speaker A: Yeah, this is super interesting. So lots of cool things that we talked about here. One other question maybe that I will ask you is you have a super interesting background. I know you started out, uh, building trading algorithms for Kalshi and polymarket, which sounds super interesting. And today you do a lot of AI consulting. Right. So you go into companies and you do an AI audit, you talk to them and figure out what things can be automated. You maybe act a little bit like a forward deployed engineer. You kind of observe, audit, uh, and then come up with a plan to help automate and do more, uh, with AI within those companies. So I want to ask you questions about all of these, but just my curiosity takes me to the, to the Kalshi and Polymarket things that you were doing. These are kind of like betting platforms but for real world things. Right. You can say things as, you know, meaningful as who's going to win an election or things as meaningless as how many times is the CEO of Coinbase going to use a particular word during the earnings call. Right. So lots of stuff there. So how did you, for people to understand, like when you did trading on, on these platforms, what specifically? Like what's an example of uh, a trading algorithm that, you know, people build.

Speaker B: So we specifically targeted, uh, two things. Uh, first is the crypto and second of the sports. Reason being, um, back then the APIs. This was like three to four years back when I built this. The APIs that were available for this were better as compared to others. And there was a, um, way to predict or algorithms to predict in the background what is going to happen next. Because let's see, if you're taking sports, we have all the data. For example, this player is going to play at this specific region. This is going to be the opposing team, this is going to be the um, time and date and we have the rest of the history data based on which we can analyze and predict. So the entire history was a part of the next prediction in that.

Speaker A: Okay, interesting. So you basically look at all this data, uh, and then you calculate your own odds and then if those odds are different enough than whatever the market says, then then you would take a bet. Uh, so super interesting. So people wondering, well, Aidan, why are you asking that? This has nothing to do with AI. No, but there's a method to this. How does AI now impact these things? Because, you know, you can use, I assume, you know, cloud code to build a, uh, model. We uh, now have Claude in Excel which can, you know, allow you to build really comprehensive models of almost anything.

Speaker C: So what do you think the impact

Speaker A: of this stuff is going to be? Because arguably an agent is going to be a lot better at getting all this data, understanding it, figuring out the next algorithm, um, and self training and getting better. So what do you think the impact of this is going to be on platforms like Kalshi and Polymarket?

Speaker B: All these are like Very data comprehensive tasks that are to be done. And if you're just a human mind is analyzing all these things, it is very tough to get the right, tough to make the right decision and analyze everything and do it fast because every minute is going to cost you. Here for example, something like a match is going on right now, some sports match is going on. Even if you delay by a few seconds, you lost it. So the speed is very important and AI is going to analyze all this data very fast. And if you're using agent AI, it is going to take actions on behalf of us in the right way.

Speaker A: That makes a lot of sense. So uh, this is a great conversation. So before I ask my final and favorite question, if people want to reach out uh, to you, how can they? What are the best ways to find you?

Speaker B: The best ways to find Me, uh, is LinkedIn and my Twitter or X. So I'm pretty active on both of these platforms.

Speaker A: Okay, great. And you know my final question to you today Sam Rudy is over the next 12 months, what are you most looking forward to in the world of AI? Like what is it that maybe you can't quite do today that you want to do? Or what is a trend that you're very excited about? What are you looking forward to in the next 12 months?

Speaker B: I'm um, personally looking forward to like help organizations 10x their execution speed with AI right now. We are a lot there but specifically people, uh, non technical folks in the age group of like let's say 40 plus because they have this knowledge of their industries that younger people do not have. And if they just add AI to it and if they know where to add AI and how to add it, the impact is going to be way higher and the execution speed is going to be at least 10x if we do that. So I believe that is going to be where the future is going to be in the next 12 months.

Speaker A: Amazing. Great place to end it. Uh, thank you so much for doing this.

Speaker B: Thank you.

Speaker A: And that's it for today.

Speaker C: Thank you so much for tuning into

Speaker A: this episode of this new wave.

Speaker C: If you like the content bedroom, be

Speaker A: sure to rate, review and subscribe so you can get notified when we post the next episode. See you next time.