Podcast

This is the Everyday AI show, the Everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. I've been struggling with this one for years. There's so many instances when I want to personally use generative AI in large language models to maybe help me complete a certain task faster, maybe to go into more depth. But then I think, okay, yes, this is going to save me some time. It's going to make me more productive. But am I just going to get dumb over time? Right, the more I blindly hand off knowledge work to a large language model. Right. So it's something I'm excited to talk about today. Kind of this dichotomy of, okay, how can we, you know, still use the best technology that I think any of us have ever seen, maybe in our lifetime, yet still keep our brains sharp?

Right?

How can we find that balance of being productive but not just getting dumber at the same time? This is going to be a fun one. I can't wait. What's going on, y'? All? My name is Jordan Wilson and welcome to Everyday AI. This is your daily livestream podcast and free daily newsletter helping us all not just learn AI, but how we can leverage it to grow our companies in our careers. So it starts here with this very podcast. I'm excited for our guests for today, but it continues in our newsletter, so if you haven't already, please make sure to go to your everyday AI dot com. Sign up for the free daily newsletter. We're going to be recapping some of the most important points and takeaways from this very conversation and laying it all out for you, right? So you can actually take this info to grow your company and your career. All right, so before we get started, as a reminder, I just got back from the Nvidia Conference. We're going to have a ton more out of GTC over the next, like, week or two. I had so many amazing interviews. You know, I can't wait to, you know, release these over the next few days. So just make sure to keep an eye out for those. All right, before we get started, I first want to go over some of the AI news for March 21st. So first, OpenAI has launched its advanced AI models for voice. So OpenAI has introduced three new voice models which are called GPT4O, transcribed GPT4O mini transcribe, and GPT4O mini TTS, or text to speech. Yeah, gotta love the naming. All right, so these models are designed for transcription and text to speech applications and available through OpenAI's API for third party developers. So the models include some pretty nice groundbreaking features such as real time streaming speech to text and customizable voice presets so users can modify accents, pitch, tone and even emotional expressions through simple text prompts. So the new models significantly outperform OpenAI previous whisper model which was one of the best models in the world, achieving a 2.4 word error rate in English compared to Whispers higher error rates. They also perform well in noisy environments across 100 plus languages. All right, OpenAI also launched a pretty cool competition which is kind of rare for them. So we'll make sure to link to that in today's newsletter. All right, next Gmail and Google have introduced some actual AI powered features for Gmail now. So Google has rolled out a new AI powered search feature in Gmail to display more relevant email results based on factors like recency, frequent contacts and most clicked emails. Previously, Gmail search function only showed emails containing entered keywords in chronological order, often leading to overwhelming and irrelevant results. So users can now toggle between most relevant and most recent search results when using this new AI feature. Yeah, I'm excited to test this one out because yeah, the old kind of Gemini for AI, it was just kind of a bad search, right? So hopefully this one's better. You know, we'll find out and like speaking of something getting better in about time. My gosh, about time. Amazon's quad finally has real time access to the web. I don't know, this is like, to me this is like, you know, you've had an iPhone for 10 years and it just started text messaging like today. Anthropic. Super late on this, but they did announce a major update to Claude, enabling it to search and process information on the Internet in real time. So Claude's new web search feature is now available for paid users in the US allowing the AI assistant to access and synthesize up to date information instead of relying solely on training data. So the feature includes direct source citations, a move designed to address concerns about misinformation and AI hallucinations while boosting user trust. So yeah, I know I've been kind of hard on Anthropic for this very reason, but I think it, if I'm being honest, it was kind of getting almost like dangerous to use any large language model not connected to the Internet. Yes, you still have to do your due diligence to make sure these AI in large language models are just hallucinating information, but still. All right, yeah, we're gonna have a lot more on those stories, Anton, in our newsletter, so make sure you go to your everydayai dot com. All right, let's get to it. Good to be back live. Good to see y' all on the LinkedIn and YouTube machines. Big bogey Face and Brian and Jay, Zach, Michelle, Jessica, Everyone else, if you have any guests questions for our guests, make sure to get them in. Michelle, Sandra, uh, Cecilia, Gene, Everyone else, what's up? All right, uh, I'm excited for today's guest, so, uh, please help me welcome to the show. Bringing him on. There we go, we have Sumit Gupta, who is the lead BI engineer at Notion. Sumit, thank you so much for joining the Everyday AI show.

Yeah, no, thanks. Thanks a lot, Jordan, for the welcome and morning.

All right, I'm. I'm excited for this one. Let's. Before we get into this topic, which I'm gonna try hard to shut up and let you talk a lot because I've got a lot of feelings on this one, Sumit, but can you first tell us a little bit about, you know, you do in your role at Notion? I'm sure most people know Notion, but maybe just, you know, for those that don't as well. Maybe if you could describe that as well.

Yeah, sounds good. So I, I lead the BI engineering at Notion. I support sales and marketing team here. If you've never heard of Notion. So Forbes like to call Notion as AI everything app. You can think of Notion as a blank canvas and you can do pretty much everything. You can, you can do notes, you can do database automation. You can, you know, create your own gantt char and project management. Notion can pretty much do everything nowadays. Right. And I, I come from a place in India. I was born in Bombay. I've been in US for 10 years and, you know, and have been using AI like, in professional life for like a couple of years now. And I'm pretty excited to talk about the topic. I'm actually like, as much as I'm excited, I'm also like. It's. It's a topic which is very close to me and I think it's. It's the same with you also. So let's get going.

All right, let's get to it. Is using AI making us dumb? Yes.

The short answer is yes, but allow me a couple of minutes to explain that part right in my rule right at Notion, I day in, day out, my job is to write SQL Query. SQL Query. My job is to create dashboards and reports in Tableau and, you know, before AI, like let's say if I, if I wanted to create a tableau report, it would take me three to four weeks, right? Generally there's a lot of to and fro involved with stakeholders and I would go and write a lot of calculated feeds. I'll write, I'll do a lot of joins, I'll, I'll, I'll, I'll iterate over charts, right? But nowadays whenever I get a request from my stakeholders, I'm like, okay, I strategize of how the dashboard might look like, what do I need, what calculated field I need, and then I, I feed that data into AI, right? I even believe I have premium subscription of pretty much anything. Every AI that you can imagine, GPT, publicity cloud. Like, you know, all the AIs have their own strengths, right? So in my case, I would go to, let's say, Claude and be like, you know what, create a calculated field for financial, financial year, right? And comparing financial year metrics and Claude will Split out a 200 volt calculated fee, right? If I was to do that previously, right? If I was to do that, it would take me at least four to five hours to even get it right? With Claude, it does not even take four to five minutes. It probably takes less than a minute. So it makes me productive 100%. Instead of spending two days writing calculated field, I'm finalizing my calculated fields and my metrics in two hours. But the counter side counter of that is it's, it, it's, it's made me lazy, let's put it that way, right? And when you're lazy, you're not, you're not thinking really hard. I mean, when you're not thinking hard, you're dumber, right?

It's, it's so true, right? And you know, I'm curious, you know, Samit, through your personal experience, because I, you know, I remember the early days, you know, back in like 2020, right before ChatGPT came out. There's all these, you know, essentially writing tools, right? And I was a journalist and so I was using this technology early on and I'm like, okay, this is good. And then it started to get to a certain point for me, even before ChatGPT came out, that I'm like, wait, I'm starting to turn off my brain in some instances, right? And you know, you have to start keeping that in check. You know, I'm curious, what was the point for you, right, when, when maybe the, the, the power of certain LLMs started to, you know, really get really good and you're like, wait, do I have to like sit back and look at how I'm using these? Like, like, did you have a certain point where you were like, whoa, I like, I have to make sure I'm still using my brain.

Yeah, yeah, I remember the time that you're talking about because I think before GPT came out there were like article rewriter services, right? Like copy AI and those kind of AI, etc. And those were great. But GPT came along and then you're like, wait a minute, is, is this real? Right? And as far as like specific instance of when I felt this is like, you know, life changing, right? When I was at Snowflake, I was tasked to build like a streamlet report and then I'm not a Python wizard, right? So I started using GPT to like debug my code, part of my, part of my, like trying to debug my code. Because previously you would go on stack overflow, you would research, you would spend a couple of hours and you try multiple different coding solutions to see if it's what's working. And then with GPT, I was able to do that in less than 30 minutes. And this is like early to 2022, late 2022, right, where models were still not like great. It was great at the time. But now when you think about it, how Claude works, right, with the coding output, etc. And with cursory AI, etc. In 2022, the fact that I, I did not need a mentor or a coding buddy to actually review my code and get the code working, that was a mind boggling moment for me.

So what's, what's your advice? You know, maybe for people who are struggling and you know, I'll even say like one of my personal examples, right? I said I'm a journalist, you know, I, I, I do a lot of writing, I write a daily newsletter, right? And there's some instances where I use AI and then there's some instances, businesses where I don't. Because at least I feel if I start handing off one of my, you know, most polished skills that I've been getting paid for two decades to do, if I just keep handing that off, I'm gonna lose that, that, that skill, right? How can, how can, you know, business professionals out there sumit start to, how can they find that balance?

Yeah, I think in my case, I, I'm, I'm not to a point where I'm handing my life off to AI yet. And I don't think so I will ever do that because when you're in tech, if you, if you're not learning, if you're not critical thinking, you'll be out of job in less than six months. Right? And I'm, I'm completely aware of that. Right. And to be honest, I only use AI for things that I am already great at or you know, need some support. I wouldn't go about and be like, oh, I'm an AI researcher, writer technique, write a research paper of 30 pages, right? That's B.S. that's not the best use of my time. Right. Even if AI could write it, that's not who I am. That's not what I want to do. So in short, I want AI to do the repetitive task that I generally used to do previously and in the areas that I am already exporting. Right. I'm an expert in Google search. But nowadays with the cloud just launched web search, right. Little today itself. But before that complexity, I would ask publicity to be like, you know what, like literally early last week I, I've been looking to like do a lot more speaking speaking gigs. This year I went to publicity. I'm like, Perplexity is a prompt go about and search like data conferences or analytics conferences which are, which are still open for speaker there they have called for speakers, right. And perplexity gave me like 25 different links. If, if I was to do that, right. It would take me a couple of hours if not more to even, even do that. So things that I'm expert in and which has a repetitive element to it, that's where AI shines.

Yeah, that's a great point. Yeah. Anything. Yeah. With research, repetition, right. Things that don't, like, you know. Yeah. If I'm researching something manually and I have 30 tabs open, like I think maybe that process is making me dumber. Right? Not. But by skipping it, it's probably making me smarter, right. Not getting stuck down all these, all these rabbit holes. But Samit, I'm wondering is, is there any downside right, like, like specifically like cost. Right. Because sometimes, you know, as an example with, with vibe coding. Right. You know, because I think this is huge, right. When it comes to, you know, coding, software development, everyone's just, you know, sometimes maybe turning off their brain too soon. Is there a downside even to elements like that? Oh, I think I, I think, I think we lost your, your, your audio there.

Sweet.

There.

Yeah. Yeah. So, so I, I think the, the, the white coding moment is here. I think couple of weeks back, YC YC right. Y Combinator published a post where 90% of the YC back startups are, you are white coding like their apps completely based off AI coding, right? I mean that's great, but I think I have a couple of examples that I would want to talk about. One of them is like I read a post on X or Twitter as we used to call, someone wrote a code and you know, they used aws access key, etc. And then the backend wasn't very secure, right? And then hackers were able to access backend and the founder saw like a million dollar bill. Right? Because when you're wipe coding you're not thinking of backend, you're like, oh yeah, the website looks pretty, the website looks great. I'm ready to go, ready to get that funding. So that's one instance. Another instance is recently one of our non technical stakeholders wipe code and wrote a SQL query. The SQL query with the joins and everything else should have taken less than like $50 to execute on our platform, like on Snowflake, but it took over $10,000. Because when you're querying like trillions of rows, if you're not careful, if you're not efficient in writing your query, the select star statement can cost you thousands of dollars. And that's what happens. So that's the downside of using AI without really when I think of AI, I think of myself as a guardrail for AI. AI can do what I ask them to do, but it's my job to make sure there are guardrails around it and make sure that it's, it's working but it's not costing me dollars. Right, then, then it should, yeah, that's.

Yeah, that's a good point. Right. And so for those that aren't familiar, you know, vibe coding, you know, that's essentially when either non technical people or people who know how to code, right? Instead of just going in there and you know, writing it by hand, they're just kind of passing it off to, you know, maybe a tool like cursor or something like that. But if you're using the API, right, and you're paying the usage, yeah, those, those bills can, can SK rocket, Right? You know, I'm curious Samit, is there anything that you're, that you're doing, you know, actively, you know, to ensure that you're still staying sharp, right, that you're not getting dumber? Right? I, I think this is something I'm asking you, right, because I, I need to find these things myself because I sometimes find myself over reliant on large Language models, right. What are you doing in your day to day to make sure that you don't hand off too much and you know, finding that balance.

Yeah, I think my way of think as I alluded to it, right. My way of thinking of best use case of AI is a repetitive task. Anything, let's say. And as I mentioned, like especially in my case, right. When I'm SQL querying or when I'm writing or building tableau Dashboard, the first iteration is always mine, right? I'll go ahead and build the dashboards, right? Because I don't want to lose that touch. But once that first iteration is done, generally, you know, after a point of time you need. You are like the way you have created writer's block engineers and you know, data visualizer. Visualizers like me can have that block too. So I'm like, okay, what do I do next? What, how can I improve? That's why AI comes into picture. Because think of AI, what's LLM. LLMs are being fed like with a million visualization, right. And they know like you know, what to look, what's good, what's great, what's bad, right. So you can take their suggestion and that's what I do. I take the suggestion. I'm like okay, how do I improve this chart, right? How do I improve this query? Can I make this query more efficient? Right. And that, that I have that cut off, right. Without that cutoff, I would be even more dumber. I'm. I mean I know I keep using number as a very loosely, but not that I'm dumb like I work for notion, right. I mean obviously we are all smart here, but the fact that that cutoff is really important for me. I. I am hoping and hoping and praying that that cutoff does not get lower and lower and lower as. As the days fire. And it should ideally get higher and higher. And that is why I wanted to talk about this topic because it's an emotional topic for me itself where I'm like, it's an, it's an inflection point where I'm like, I don't want to get this cut off lower. I want to keep this keep, keep a high bar of you know, making sure that I stay on top of my feet. I critically think and you know, I be in the job. The market is already rough. You don't want to make it easy for folks to not hire you.

Yeah. And you know, now's a good time to point out, you know, live stream audience if you do have any questions for Samit make sure to get them in now. You know, there, there, there was a recent study. We covered this one in our newsletter. It was from Microsoft. It was a great, great study. It was called the impact of Generative AI on Critical Thinking. And it found that for knowledge recall, 72% of participants reported using much less effort or less effort compared to not using gen AI. So Samit, like I think, right, and you know, maybe this isn't a stretch, right, but I think of the brain as a muscle, right? The more you use it, the smarter you get. The less you use it, the more you turn it off, right? The dumber you get. And you know, we, we hear constantly about how, you know, these, these LLMs and the benchmarks and you know, these, these pseudo IQ tests and you know, like it's getting to the point where, you know, as we quote unquote approach AGI or ASI or whatever you want to say, right, that any large language model is going to know more than any human. So like, how should we be addressing this, right? Because part of me is like, okay, maybe it's good to just give more and more to these large language models because they're smarter and they know it and I don't, right? Versus okay, well I'm not then developing new skills. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on genai. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for chat GPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everyday AI.com partner to get in contact with our team or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on gen AI.

Yeah, so that's exactly where you should have your own own like, you know, cutoffs or you know, baseline of when you bring AI in your life. You cannot be bringing AI in your life for everything. I mean, you might be tempted to, right? But it's like the way I think of it as like you're getting short term results for long term losses. Right? That's how, that's how I view AI. If I start using AI for everything in my life, let's say if you're a student, right. I think I saw a post like last week from a Berkeley professor and he's been teaching like database database for like 10 years. And he noticed that people have stopped asking a lot of questions in the classes now, like students. But then he also realized that he's like, oh, maybe I'm, I, I've just become so great that students don't have any questions. But then during tests, right, midterms area, their average score was the lowest it has been in last 10 years because students actually, without even trying to understand or learn, they're using AI to, you know, write assignments, you know, but then when you're, when you have a midterms, right, in the class, you don't have access to, let's say GPT, you are not going to recall what was thought because you just weren't focusing or you just did not, you did not stretch your muscle enough to like in your assignments to retain that or retain or recall that information. So that's a very good use case of where AI is actually impacting, you know, even younger generation. Because at least for us, like we come from place where we still have built that muscle, right. Like, you know, when we were growing up, right, we had to do it because GPT did not exist. Like I wrote a book, right, the tableau workshop. It took me a year and a half to write that book. Nowadays, if I was to do the same thing again, it would take me less than three months because I know for a fact a lot of things would be GPT driven, right? So the fact that, you know, having that guardrail, having that cut off for when to use AI and when not to use AI is going to be as critical as the fact that your prompts are supposed to be great.

Yeah, I think, I think you bring up, yeah, a lot of, a lot of good points there. And I'm sure there's going to be, you know, many more of some of those types of stats, right, that just show, hey, you know, scores across the board on, on certain standardized testing are probably going to continue to go down, especially when you can't use AI, Right. Because I think that people are maybe leaning a little too heavily on it. So even, even for myself, right. I think the productivity piece Maybe has that downside, right? Because I've never felt, felt so productive in my life. I've never felt that I've learned so much in my life, right. Since AI came out. You know, you mentioned you know, being able to use something like a, you know, quick search tool, Perplexity, Deep Research, Grok Deep Research, Open AI Deep Research. So I feel I'm able to bring in all this knowledge but then I just feel I forget it, right? Like, like do you ever find yourself. Yes, now I'm more productive and more knowledgeable, but I'm still not retaining anything. Like do you ever feel that way?

Yeah, I, I can give again I, I, I specific example. I think one of the, one of the, everyone who's listening in will understand. So when you type something in Google, let's say, right? And if you make a mistake, right, then Google says did you mean let's say a word xyz, right? And you don't, you don't, you do not even try to make correct it. You just click on that like the correct spelling right of that word and you know, Google searches for you Imagine like your ability to recall like you, when you're typing, you almost know that the spelling is going to be wrong, but you hope that Google's going to correct you, right? That happens far too often, right? And then to your question again like right, So I have started noticing that when I used to write SQL query myself, I would know how to write case when statement. I would know how to write let's say, specific function in SQL. But now if I don't have GPT, I have to like okay, how do I write even case statement, right? Because case statement can be complicated. So when that inflection point comes in, I'm like, I don't think so. This is working for me, right? AI is making productive. But then if the fact that I can't retain information anymore, I am becoming more of an AI than a human.

Yeah, right, that's a good point. You know, as, as weird as this sounds, I like, I find in, and this is for me why this topic really does hit home. Like I'm not exaggerating, I'll look up things on, you know, chat, GPT search, perplexity, you know, Google search, whatever on a certain topic that I'm trying to learn. And in so many cases, and I, I kid you not, in so many cases, a lot of the, the first sources are myself, right? And that, and like in that, you know, because I covered something six months ago or I had a guest on or I did a tutorial, right? And for me that's that it almost hurts because I'm like, wait, I'm learning from myself and I forgot this. And this was three months ago, six months ago. How did I forget this, right? Is, is like, is that going to become, do you think, more and more common? Just our ability to retain information for a longer period, right? Like I find myself struggling with this often.

Yeah, that's gonna happen if we, if we don't see as I mentioned with our like you know, pre, let's say 90s born folks, right? Or pre 80s or 90s born, at least in our case we grew up with that critical thinking ability, right? We were supposed to do our own job, right? So that's why like we both, like, we both are able to talk about AI and how it's making us number, right? Talking about cutoffs and guardrails for folks younger than us. Like if you have 15 or 16 right now, you have like the whole computer in your palms, right? And you are like using AI for everything in your life, right? So the fact that you did not go through that muscle building exercise for like a decade or two, right, you, you don't have that retain ability to recall or retain that much. Your muscles not built, right? Your brain muscles just not built. But I hope that as much as AI is a boon, right, it's, it's helping folks. It does not turn into a curse in five to 10 years where you know, there's like, let's say now like there's 10% of world population who can get, let's say job in it because of, you know, their critical thinking ability. But in 10 years, I hope there's not a, that number still stays at 10 or above, not goes down to let's say 1 or 2 percentage. Because the top 1 or 2 percentage who, who know how to use AI in the job are going to be millionaires, right? Are going to be in the market, in the, in the demand for like years to come. But that top one to two person are not gonna run the world. You need more people, right? You need critical thinking ability. You need people who can retain and recall and you know, use AI to like as an assistant, not replace a real human with the AI. AI is your assistant, not, not like your personal full fledged human who can do everything that you can imagine. It should be complementary, it should be complimentary. AI should always be complementary to you, not the other way around.

Yeah. So you know, anyone that's listening to the show, like you all know I, I hate when you know people come on here and pitch their products. But you know, Michelle is asking and I like I feel Samit, you have to take this one because you know, asking. Tell us more about Notion. Can it help with this retention? Like I got to give you that one because it's a softball because it's great for that.

No, 100%. So if you've never heard of Notion, I highly recommend you we have a free trial. I don't like, I, I'm not represent representing Notion here, right. It's, it's all personal opinion but go ahead, go to notion.com sign up for a free trial. You would be surprised with what Notion can do for you, right? Obviously it's a note taking app but Notion now also has like assistant AI which basically if you connect your let's say Slack you connect your other tools, right? And if you ask question it's like a Knowledge AI now where it will search through your post messages on Slack. It will, if you, if you were to use Notion in your professional setting it will search through your docs and give you like relevant information. Right? GPT works great, but it does not have access to your personal information, right. Or you know, your company information or knowledge base in the company. And that's where Notion AI shines. The fact that you can. I have had so many instances with Notion AI where I'm like did someone talk about let's say a metric, right? Because I've been at Notion for less than a year. So there have been metrics that have been the company has been using for multiple years, right? Okay. When was the first time someone mentioned let's say month over month retention for product users. So Notion AI actually goes through the whole Slack history that we have and gives me like exact link and conversation context of. Okay, this is when let's say Director of Demand Gen was talking about this, right? So the fact that Notion AI does that for you is amazing, right? Obviously that's one of the, one of the features of Notion AI. There's the fact that you can create notes, you can create automations, you can I. If you are new to Notion AI I would highly recommend you just Google Notion templates. People have the whole brain on Notion. There's the whole concept Jordan, you would know like there's a whole concept of like second brain on Notion. Just Google that term second brain on Notion and you would be amazed with what people can create.

Yeah, yeah, I, I do agree. And I was like hey perfect, perfect chance there to answer a question. Super Directly, but you know, this one might be controversial. So Sandra, thanks for this. You know, she's asking could, could this be the, the end of the knowledge worker? Right. You know, for decades we've gotten, you know, we've gotten jobs, we've gotten promoted, right? Companies have, have grown into unicorns, trillion dollar companies based on what its people know. Samit, could, could this, could we be. Not now, right, but could we be seeing the end of the knowledge worker anytime soon?

I, so I know folks talk about, talk a lot about, oh, is AI going to take my job or you know, is AI going to replace me? I think that's partially true for jobs, which has a lot of repetitive aspect to it. Right. And I believe knowledge workers fall in that category. But the counter argument to that is so if you're a knowledge worker and if it, if it, let's say you were doing let's say 10 tasks a week, right? With AI, if you upgrade yourself, if you know how to use AI to complement your job instead of doing 10 jobs, if you're doing 40 jobs now, because AI, right, AI can hallucinate, we all know that, right? AI is not perfect. Anytime I see an AI output for a metric or something, I generally go about and verify that myself. And as a knowledge worker, if your job wouldn't be now to research a lot, but to find, but to validate what the research is saying. So Instead of doing 10 tasks, if you upgrade yourself to do let's say 30 tasks, 40 tasks, you're always going to be in the demand. But if you are one of those lazy workers where you know, you're still stuck at 10 and you ask AI to do 90% of your job and you know, let's say you, you do a report for CD of your company and you know that the CPU uses that number in, in a board deck and that number is absolutely weird and it does not make sense. You're not going to be in your job because your job is to validate and verify and obviously get that info. But if you don't validate and verify, you're going to be out of job. And that's, that's not a good thing.

I think. I think that's a, that's a great, a great take there. Yeah, yeah, I'll, I'll have to save my, my hot takes on that one for another day. But Samit, so we, we've covered a ton in today's episode, you know, from some of your personal examples and how, you know, sometimes using AI might just be more Expensive. It might be better, right? It might be making us dumber in the end. But you know, as we wrap up, what's your one most important takeaway for business leaders out there grappling with that same thing, you know, feeling, yeah, I'm, I'm becoming more productive, but I might be coming a little dumber. What's your best takeaway for everyone?

Yeah, don't choose the hype. I think the hype right now is MCP and model context protocol and whiteboarding. Don't chase it. Think of your specific use cases, think of all the repetitive tasks that your company has or you are doing and think of can AI help me here? Don't go chasing, oh, can AI create reels for me with one click? Yes, it can. But is it going to add value to your audience? Probably not, right? So think of repetitive tasks where you know, you, you can use AI as a complement but don't think of replacing AI as your full fledged assistant yet. And I, the way I like to believe is like this is the worst AI will ever be right. That's how I like to think. In two years ago, Claude AI, the coding output wasn't like great. Now Claudia can build your website in less than two minutes, right? Like a full fledged gaming, gaming thing with Unity. Etc So to business leader, as I mentioned, think of all the repetitive tasks that you can automate. Use any 10 use make.com right? Automate your workflow but don't chase the clout and don't chase those clickbaity titles. You can go on YouTube and you can find like people talking about how AI replaced my, how AI helped me structure my life. That's great. But those are just for recording purposes. You go talk to them. That's they. That's not a real use case.

Love it. I think some, some great takeaways and some wise, some wise words for, for those of us out there, you know, struggling to, to walk that tightrope between, you know, productivity but still retaining all of that knowledge that makes us special, unique, human. So Sumit, thank you so much for sharing your time and talents with the everyday AI show. We really appreciate your time.

Yeah, thanks a lot. J. Thanks. Thank you. All right.

All right everyone. There was a lot of great info there. If you missed anything, if you need to hear it again, if you need to know more, our newsletter is where that's going to happen. So if you haven't already, please go to your everydayai.com Sign up for the free daily newsletter. If this was helpful, tell someone about it. Right? So if you're listening, maybe here on, on LinkedIn or Twitter, just go ahead, repost, retweet, reacts, whatever it's called, help. Help someone out. Also help us out. Tune in tomorrow and every day for more Everyday AI. Thanks, y'.

All. Yeah, thanks. Bye.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going for a little more AI magic. Visit your everyday AI.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next time.