Everyday AI Podcast – An AI and ChatGPT Podcast - EP 448: How To Build an AI-First Company

Episode Date: January 27, 2025

One side of the coin — AI can make it VERY hard to compete when starting a new company. Other side of the coin — AI can make it MUCH easier to compete when starting a new company. Rajesh Kandaswamy knows the path. After spending a decade as a VP and researcher at Gartner, Rajesh learned a few things about building an AI-native company. He sharing the ins and outs of what it takes to build an AI-first company from the ground up. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan and Rajesh questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [e-mail] with Jordan on LinkedInTopics Covered in This Episode:1. AI First Approach2. Nourish: An AI-Driven Nutrition App3. Building with AI from Day One4. Overcoming AI Challenges5. Future of Organizations and AI AgentsTimestamps:00:00 Nourish: AI Diet Tracking App05:12 AI Transforms Multimodal Communication08:30 AI-First Organizational Revolution13:17 AI Partnership for Business Growth15:01 Future of Affordable and Fast Computing20:15 Adjusting to AI with Openness23:30 Embrace Change, Rethink GenAI Limits26:03 AI Agents Revolutionizing Business EfficiencyKeywords:AI first company, Gen AI, Large Language Models, technology trends, Gartner, AI agents, AI implementation, nutrition, Nourish, AI first app, tracking food intake, obesity, technological evolution, Value Prop Approach, Agentic AI, hallucination issue in AI, high school interns, digital technology, Commercial Agents, inevitability in technology, AI resources, automatization, organizational models, industrial revolution, AI reliability, investing in AI, machine's intelligence, AI and human processes, company growth, AI strategy.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

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How do I be AI first? How can our company be AI native? As, you know, let's be honest, companies have struggled a little bit over the last couple of years since the generative AI way of wave of 2022 to really integrate generative AI in large language models seamlessly into their day-to-day operations. And sometimes it can be easier to start over from scratch.

So we're going to learn today on how to build an AI-first company. And talking to the founder of Nourish and, hey, great timing because we can also talk a little bit about what Nourish is, what it does, and nutrition, right? It's that time of the year. We've got to watch what we can eat and we can do it with AI while also learning how to build an AI-first company. It's going to be a fun conversation. All right.

I'm excited for this one. I hope you are too. Welcome to Everyday AI. My name is Jordan Wilson. I'm the host and this thing. It's for you. It is your daily live stream podcast and free daily newsletter. Helping us all learn and leverage generative AI to grow our companies and our careers.

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debuting live. We'll still have in the newsletter. Don't worry. We got you. So make sure to go check that out. So let's get going. I am excited for today's conversation. I think it's going to be a fun one. It's on the top of everyone's mind. How can my company, you know, go from not just talking about AI to making it the first step, right, not an afterthought. All right. So help me. Welcome to the show. So there we go. We got him. Rajesh Kandeswami, the founder of Nourish. Rajas, thank you so much for joining the Everyday AI show. Thank you for having me, Jordan. I look forward to the conversation. All right. It's going to be a good one. So, Rajesh first, let's talk a little bit about Nourish. What is nourish and how did it come to be? So, Jordan, Nourish is an AI first app. Fundamentally, what Nourish does is help you track what you eat and get advice. You know, we track everything in our lives, money, steps, energy use, but what we put in our body, we don't really track very well.

And digital technology has helped us in many things, but somehow it has not made a mark in how we can track what we eat. Do you know that now hunger is a larger issue, obesity is a larger issue in the world than hunger? I never thought I would see the day. This includes India and China. So we believe there is a huge chance for us to improve how we track what we eat and previous technologies haven't really made such a mark, but we believe with AI, it's a step change, can help us solve this problem, can go beyond more, both in terms of user interface

and in terms of capabilities. And that's what NARIS does. It's an AI-first company to help you track what you eat and get instant advice and deeper insights. And yeah, what great timing, right? Because I think this is, you know, whether everyone's, you know, shove in their face during the holidays like me or, you know, looking at their New Year's resolutions to stop shoving food in their face. It's, it's, it's that time of year, right? So, so, you know, I'm curious, you know, how do you think, you know, nourish or, you know, even just using AI to be more mindful of what

you're eating? How can that be especially helpful during this time of year? So the thing is, like, you know, so one of the challenges, why this problem makes this. why we are not able to easily track what we eat is because food is a our relationship with food is very complex what we eat and it's a you know there are many apps today that can help you track what you eat uh but they're very cumbersome to use most people try them it works for a set of people but most people give up using technology to track what they eat but the interesting thing about AI and especially gen AI it's a step change in user interface now imagine like for instance i can easily tell you from breakers today i

I had a slice of sardo and a couple of scrambled eggs and a cup of coffee. Try putting it into one of these apps. It's super hard. What if you are just able to tell, like, you know, like how I just told you, I can just say, like, and I had like in a couple of scrambled eggs, and I had a slice of avocado and a slice of sardot and half a cup of coffee. So it's so easy to tell somebody. And AI can do that, right?

And also, like, imagine taking a picture or immediately getting instant feedback, you know, based on my goals, I happen to give. be a half marathon runner and then it happened to really, you know, prefer certain foods and get instant advice. So the interesting thing is why AI particularly is that like compared to other technologies, AI can mix multidimodalities in terms of exchanges, right? That's what. So whether it's speech, images, everything that we can do in the real world, that is a big step

change. And the second thing is, especially with nutrition, as I mentioned, nutrition is a very complex thing. You know, what we eat is it is a combination of chemistry, biology, culture, our individual preferences, behavioral science, all that goes in that determines like, you know, how well we keep on cap of a diet. I cannot think of any technology in the world, including all the digital technologies, that can look across domains and help you that way. And AI can. And similarly, there are opportunities in many other places. And I'm kind of building a nutrition company. But if you are in many other places outside in medicine, culture, finance,

are there things beyond what today's traditional deterministic computers can do? That's where the opportunity lies. And that makes it very interesting. That's what we are, that's what we are trying to do with nutrition. So, you know, you talked about building in there. And, you know, it's an interesting time right now to be building anything. But, you know, I want to talk a little bit about even your experience of building nourish, right? Because, well, first, and maybe this will help set the stage. Can you tell everyone first a little bit about your background at Gardner? Yes. So for, I mean, if you, Gartner is the world's leading technology research firm. And I was there for 10 years. I love the job. And I was fortunate to do many things.

And one of the things that it did was to Gartner makes you a fellow and was to think about the future of organizations. So I was trying to see like how organization models evolve over time. And one very interesting thing came up. Every large industrial revolution fundamentally changes the concept of what an organization is. When we were hunter gatherers and then we became farmers, the organization unit change. Then to small our artisans change. Steam power, organization model change. Metals and manufacturing cars, factory and offices came. But that had not occurred with the digital till a few years ago. If you look at the inside of like a large digital organization like Amazon,

what's not too different from a Ford Motor Company? You had like CEOs, marketing, sales, etc. So I was trying to see like, you know, why was that not the case? And at the time, like every time this change happens, it is for the underlying energy of the industrial revolution. So whether it is farming or steam power or metal making, electricity, but that are not occurred to digital. So then I was trying to look into that,

like, you know, I was trying to design something. But after that, Gen AI revolution came, then they realized the underlying energy of digital was not ready for the shift, and that's why the models had not changed. So now I believe that Gen.A. is the answer for a new type of organization that's well suited for the digital age,

so which I call as the AI-first organization. It's not just an organization in using AI, you know, in multiple products or something, if imagine if you're given a clean slate and you're going to start a company and you don't assume that it's driven by humans, human processes. If AI is your number one resource, that's what you're going to go to first and then use humans, how would you build that? That is AI first. And I believe the best way to do that is not trying to, like, you know, go and make little tweaks in existing organizations. And I believe that it'll grow organically through startups and I'm hoping to build that with me and my co-founder.

That's what we try to do in our company which we call it AI first. It is anything that we do, whether it is looking at our cap table, whether it is trying to come up with the marketing personas, whether it's trying to analyze competitor products, but design, like you know, testing out our strategies, developing code, testing code, putting data in all the way. We start with like, you know, first with AI. And if who we bring in, they have to start first with AI and Gen AI tools. Clearly, it won't work for everything. We will augment it, but we'll keep getting better over time.

That's what you're trying to do. Right. And, you know, you were in a fascinating position there at Gardner, I'm sure, right? Where it is your job to understand, you know, worldwide business trends and how these changes in technology are ultimately shifting. how we live, how we work, how we exist, right? But I'm wondering, was there any one trend? And obviously, I'm guessing it had something to do with the emergence of large language models, right? But what was it that you saw in your position as a fellow there and researching all of these technological trends?

What was it that really pushed you to say, okay, well, hey, I'm going to build this nourish thing. and we're going to put AI at the front and center? I think that part of that answer is personal, part of that is technology. The part of the personal answer is I had, like, you know, a long, long time ago when I was in India and just when Internet was taking off, I remember walking in early in the morning, and this is before the age of browser. And you could send these emails to list servers, and they will respond to you with output. I need to send something to universities, and I'm clearly dating myself.

And it was, you know, I was like, you know, fascinated that, you know, I wouldn't consider myself as a deep technology guy at all by any means. But that was fascinating that I could send these commands to Stanford University of Illinois, Urbana, Champaign. It will send you back without knowing me. It is just a mind boggling for me. And that feeling I got it again only when I started chat with chat GPT. So, and I felt that I needed to do more. with the new technology. Garten was wonderful, but I want to do something on my own. And second thing is, I realized with this future of organization fellows researches I did,

the best way to try to try that was to go and try to build something on my own. Large organizations do create a lot of value in the world. They will adopt AI. Absolutely fine. But for my area that I was thinking about, the best way to realize that was to start on. that's the second thing. And the third thing was nutrition. I want to do something that actually creates value to people. And clearly, as long as we have in my mind capitalism and as more and more food being sold and manufactured and obesity being a larger problem, this is a problem that exists. I have tried to do something in my own, in my own family, trying to start WhatsApp groups for people to better track what they eat, etc. That hasn't worked very well.

So I myself, I'm extremely habit-driven. You know, I track everything, how much I run, how many books I read everything. But ask me how well I eat and how do I track it? Really bad. So all of these things put together led me to wanting to start this. And I met a co-founder, Suresh, who's very interested in it, who's deeper in the technology, and we shared the same vision. We said, let's go do it.

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more to help bring your ideas to life. You can also get started with creative skills, a growing library of pre-built workflows for common creative tasks, like batch editing photos, creating mood boards, portrait retouching, and creating social variations. Every step the assistant takes is visible, so you can refine, redirect, or take over at any time. You stay in the driver's seat as the creative director. Adobe Firefly AI assistant now in public beta. See it today at Firefly. dot adobe.com. Looking back at it now, right? So you, you started nourish, what, just about a year and a half ago? Correct. What were some of the, maybe AI first decisions that you maybe made, you know, a year or a half and ago or more? What are some of those AI first decisions that you made

that maybe at the time felt a little uneasy, right? But looking back at it now, you're like, oh, okay, this was the right thing to put artificial intelligence or, you know, large language models at the center of this process, at the center of this ideation, right? What were some of those decisions that actually maybe felt weird but paid off? Yes, I think it's an important one to go into. So when we started this, right, just to give the other time, this is a year and a half ago. Yes, Chad GPDO is interesting, but actually using it in the product wasn't very sure. So, for instance, what I just said, like, you know, I had a couple of scrambled eggs with a slice of sourdough and, like, you know, half an avocado with a cup of coffee.

That giving something like that to an LLM and getting the response used to take 90 seconds, right? So at the time, we made this big bet that, you know, this technology, like, you know, I mean, you don't, we can't predict everything in the future. But one thing you can predict in the future in computing is computers will become cheaper, they will become faster, connectivity will be better. So based on that, as we said, like, you know, yes, today is going to be 90 seconds, but it's worth building it for that because technology will catch up. I mean, the closest analogy I can think of is when Amazon, Jeff Bezos tried to build an e-commerce marketplace for a 28.8 modem. Again, I'm dating myself. It is extremely slow, but they expected internet to become connectivity to become faster.

And then when it arrived. So that's a fundamental bet we took. So it took like around 90 seconds or so. And now the same thing takes 10 seconds. We have done some work to improve, but most of the work is done by the technology, underlying technology and the providers themselves. So we are writing on that, right? That is one big bet, I think, which worked quite well. The other thing we said was in terms of leading on to how we build this technology.

If it is AI first, AI is your first resource. then what you need is an aptitude to work on it and the willingness to, not necessarily your skills. So we started this interesting program, which is to use high school interns. So what we did was we created a mechanism in which a lot of high school kids want to learn computers, want to do AI, and they have the right aptitude. And these are students who are some who live close to us and some who are far away. I have high school interns in India, Dubai, China, UK. And what they do is when they start with us,

they could be, a lot of them are in software development. Since we are AI first, it's all generated code. And some of them are in marketing. Some of them do a marketing video. Some of them do content. So when they come, we kind of, we don't really train them, teach them everything. We tell them to go and use AI to get everything set up.

and they should use AI only for like, you know, over time to build it and learn from others. And so that's the second bet we made. And that beta has paid off. You know, we've learned. I wouldn't say it was completely smooth. But we have learned how to be an AI first company and then use humans and what the dynamic changes. That's a second key bet that we did. Does it help?

Yeah. And thanks for walking through that because now, now I'm, you know, my mind is racing in all kind of different directions because I, I think, right, one of the reasons why larger organizations are failing at implementing AI and truly becoming AI-first organizations, well, number one, they're too big, too slow, right? You can't do this over a one-year pilot. But I also think it's an older way of thinking. It's an older way of working if you're not AI first, right? Because you still think, oh, you know, our value prop is, you know, we solve X for Y by doing Z,

right, the very, you know, famous value prop approach there. But, you know, does AI, like, does being an AI first organization change what's possible? Do we still have to go do the old boring roadmap? Or, you know, there's all these, you know, conversations like, oh, AI is going to help, you know, a one-person company become a, you know, billion-dollar unicorn. Should we change our thinking and change what's possible if we can properly put AI at the center? Absolutely. In every aspect of you as a worker in a company or whether you're self-employed or, you know, in any aspect of what you do, starting to use AI. And these, most of these tools are available for anyone. And one of the things I see is the people who are willing to go and try with no preconceived notions. They do so much better because a lot of people, I mean, like, you know, I was spoken to many people over the last few years on technologies. And And there's not unique AI, but it's a larger problem in AI. Because people know what human intelligence is, they're trying to always compare AI and what it can do and a machine and machines intelligence, errors it can do in a particular way.

And I'm saying, don't. Just go play with it. It's interestingly, what happens is it's not only AI that will improve over time. We become better than working with imperfect intelligence. If you see over time in any technologies that we use, right, like, you know, say we see something on the screen, initially it used to be black and white, it's a flat screen. Clearly, it's not the real world. Clearly, it's not perfect like what's in front of you.

But over time, we adjust, our senses adjust. We can still, like, you know, a mode thinking it's like real people, though it's on a flat screen. Like that, how AI decisions, the content generates, we will learn to appreciate, we'll learn to work with its imperfections. while the technology is improving. And other thing which you realized is coming back to the points about using interns is people with the preconceived notions but wanting to get work quickly done, there are very few people in the world who really want to get stuff done quickly

and not waste time compared to high school kids. Sometimes procrastination, sometimes laziness is a good thing. So they are very, very open to saying, you know, why can't I make the computer do this? And I was born in a world and they gave me computers and then they connected the wire. to it. They were born in a world in the computers came with wires. They came with phones and their relationship to technology is so different. They're very comfortable. Interestingly, our observation is that a lot of these high school kids and thanks to their teachers, they are more open and thinking about use of technology compared to people who are already in colleges learning computer

science. They feel somewhat more threatened. Unfortunately, because of feeling threatened, they seem to avoid and putting themselves at more peril than the people who aren't. You know, I love that story, right, because it even resonates with me personally, right? Like, I love that you, you know, gave high school interns a shot to work on something that could be bigger than themselves. You know, I'm even thinking, you know, I got a job to, you know, work at a daily newspaper when I was, you know, in high school still. So, you know, I love that you were giving opportunities to the future generation. I want to shift gears here a little bit and talk a little bit more about this kind of trend spotting, right?

Because I know at Gardner, you know, that's what you were trying to do, right? Like, that's what big research organizations do, right? They see what trends have already happened, what's happening now, what's coming next, and how the business world can make use of that information. So, you know, if you combine, you know, your, you're decking. of doing that and now you're, you know, year and a half of trying to take that information and build something with it. What trends have you seen? So what maybe worked? And maybe do you see any disconnects, at least, you know, what the industry analysts are saying like, oh, here's

where AI is going versus you building with it day to day? Yes. There are two, three things I would say is one, let me get, how do I think about this? Let me just share it on it. I'll kind of go two or three ones. One is in terms of friends, like I mentioned earlier, there are some inevitable truths about how things evolve. Computers becoming cheaper, faster, AI getting better, connectivity getting better, more people getting computers, all of the inevitable truths. So if you can any technology, you don't need to try to think of everything technology does. Along these three or four vectors that will anyway occur, if that happens, how will the technology be? That's all we need to think about. that one we can be clear about the thing we need to be open about is at any point in time we have only one past but we are multiple futures because we don't know so being open and not necessarily tied on to one being willing to change is the second thing that is important to keep in mind now in terms of trends of one of the things which which is very important in my mind which is somewhat counterintuitive to how things are projected when people talk about gen ai they talk about hallucination

They talk about how it's not completely reliable, so because of which we can't use. Our take on this is completely different. When we started, we were initially thinking you're going to build our own database. And what we, and like, say for instance, a year ago, we were trying to build something with Gen AI, but we thought we'd have to build our own database

because for instance, if you say, I ate a slice of apple, he asked LLMs 10 times, they used to come up with like a few different answers. Today, ask the same LLMs, they come up with the same answer. And the speed has improved. So now we feel like we knew it is going to get better and it is getting better. What I want to go there is, well, people think about hallucination.

They're thinking about LLM purely as a technology. But the trend is, as technologies get bigger, they become brand. It's not LLM. GPT4O is a brand, right? A chat GPT is a brand. For the company with billions of dollars, for anybody to use them, they have to be able to offer the right answer because in some cases generation is okay calories in a slice of apple who's the seventh president of the u.s all of that you need absolute

truths and the users are not going to separate which question i want truth this question i want generation is the job of the company's job of the brand so what they will do the brand was chat gpt underneath it there might be an llm but there will be all the other scaffolding to make the thing work. So that's the trend as like, you know, these LLMs. You don't think only as LLMs. You think about them as brands and then working together a bet on. This is how it's been in the world in technology always. Even if you look at like, you know, a steam engine, you consider steam engine. Initially, when it came, it could explode. It could be dangerous. And over time, they put valves. It kept on improving for 200 years. It kept on improving. Now when you think about

steam engine, you think about the whole thing together. You don't think, about it separately. That's how these things will evolve as well. So we are confident, though hallucination is there, because of how these companies that invest in it will operate, they will push these things along to make them more useful. That is one large strand. The second one that is the share in stop us, it's especially with AI agents coming. It is, it is like in the future of organization research when I was writing about it. I wrote about this like, you know, six, seven years ago. I called them commercial. agents at the at the time it's a bad name so the the thing was it is predictable that as technologies

comes they will try to create things that do automatically seek opportunities and work so what we what i see out of that is because of AI agents while everybody's talking about new processes and things which will be there i think the larger opportunity will be using technologies to find inefficiencies and new opportunities that exist in the economy today and going and so solving them much cheaper and much quicker than ever done before. It's definitely possible, right? Yeah, when we talk about agentic AI, just how accessible the technology is, and yeah, just how much cheaper it's getting, you know, what we can accomplish by being

AI first is boundless, I'd say. But, you know, as we wrap, Rajas, we covered so many things. But what would you say is the one most important takeaway that you think, our audience should have from this conversation when it comes to being an AI-first company. There are very, very few moments in our lives when we will have something as big that occurs in front of us, right, whether it is in culture, politics, technology, economy. So few, so few generation, and so few times it will ever have that. We are at that stage. So as, you know, we are on the Thursday before the holidays.

Like, you know, as people spend time over the holidays and starting the new year, spend some time, whatever line of work you do, try to play with Gen AIT tools, they are free and sheep, with no preconceived notions, be open to it. Don't stop with the first question and say, it's not doing it right. Just keep working with it. Just keep trying it. If you don't want to do it for work, pick a hobby.

Try to do interesting things like that. Do it as a family. Do it with friends. to do coworkers, keep doing it and you will find how things you can do better in your personal life and in your work class. I would highly suggest that and watch for it. There will be more and more developments. What I'm suggesting is not just for only people at the front line or people at the, like, you know, doing the coding work. It is if you are a CEO or if you are a new founder or an investor, anybody.

It's not only for content generation, it's for anything that we do. You can help it for every aspect. Pick a task. One thing I'll give you is, if you have some project, something coming is, how can you be as an individual

be AI first for that one task? And do it for some time, maybe a week, and then see how it plays out, then you'll build more on it. And second, download Nourish. It's already available. Start 2025 on a good footing.

It's fast and easy to track much, much faster, less than 10 seconds to track what you eat. And it's free. We'll be going to subscription model soon until the time whoever gets in now. It's a lifetime subscription is free. Please leave to download. It's on the Apple App Store. All right. Well, thank you, Rajesh, for walking us through this.

I think even hearing your own personal journey of how you've done this and, you know, with your background, I think is going to be very helpful for all of our business leaders that are listening. and learning along with us. So thank you so much for joining the Everyday AI show. We really appreciate your time. Thank you for having me, Jordan. I enjoy the conversation. Have a wonderful holiday season.

All right. And hey, y'all, that was a lot of great information that Rajas just shared. If you missed anything, don't worry. We've got you. If this was helpful, please make sure to subscribe and leave us a rating on the podcast, whether you're listening on Spotify or Apple Podcasts, as well as sharing this. if you're listening, online LinkedIn, tag your friends. They need to know.

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