YouTube Video 2z0WM3CWgX4 ![rw-book-cover](https://img.youtube.com/vi/2z0WM3CWgX4/maxresdefault.jpg) ## Metadata - Author: [[YouTube]] - Full Title: YouTube Video 2z0WM3CWgX4 - Category: #articles - Document Tags: [[ethics]] [[governance]] [[training]] - Summary: YouTube Video 2z0WM3CWgX4 - URL: https://www.youtube.com/watch?v=2z0WM3CWgX4 We have to talk about the ads. >> Oh, here we go. Okay, straight in. Let's go. >> So, yes. Okay, >> for those of you who don't know, you all had to get up here by going up an escalator and there's the big activation that says, "Stop hiring humans." That's Jasper's company. Yeah. >> And earlier this week, Bernie Sanders posted an ad and asked, "How will those displaced workers survive when there are no jobs or income for them?" >> He actually also said, "Great idea." So let's we look at the balance. >> I think he might have been sarcastic but but what would you say to him in response? >> I would say first of all thank you very much for the free sponsored post. That was very kind. We got a lot of a lot of leads from that. So first thank you. Um, secondly, I would say AI in its current state, as much as we say stop hiring humans and we have very dramatic advertising, if it continues on the part that's on now, I actually think could create more jobs than it would take, unless there's some significant advancement in AI that likely isn't an LLM, I do think it's going to be like a singledigit multiple of productivity and going to be taking over the mundane repetitive work that humans don't enjoy doing. Um, so the messaging I would say is it's shock value. >> Yeah. >> Yeah. Yeah. >> Yeah. And Sarah, you're approaching the question of AI agents from more of an HR perspective. So, what's your reaction when you see ads and discussions like that? >> She can't say anything positive because that would ruin them. >> No. I mean, as former CMO of Salesforce, I have deep respect for great marketing and provocative marketing. And so to be at the epicenter of relevance is always going to be controversial. So it's you know you get people's attention and that's um that's really great for for marketing. On the topic though uh at Lattis we do deeply believe in the opportunity that AI brings for people and really ampl amplifying us uh not really talking about the co-pilot but more like from the HR lens scaling ourselves in a way that we can have better understanding remove biases and yes remove the wrote mundane but also scale us in a way that uh it just wasn't possible for AI to know as much as we can because AI can distill everything down for us in a way that can give us better understanding to have more human conversations. >> Yeah. And I saw that you wrote in a blog post last year that of three decades in the tech industry, the AI boom is the most dramatic shift you've seen. So I wanted to dig a bit deeper on that and like what was the moment that you knew that this was such an impactful moment? Yeah, I mean I've been around I'd like to think I'm younger than I am, but um you have >> a very cool dress. >> Oh, thank you. You know, the dress and the shoes got to have the the pink velvet pumps, right? >> Um >> so I've seen the shifts. I've seen uh cloud, social, mobile, and AI is more transformative because it's not just um a technology. It's transforming the way we work. And it is so happening so fast. And so that's a thing where it's yes it's a technology transformation but more than ever more so it's a people transformation. It's a change management and it's happening so fast in a way that we need to be very diligent in paying attention to not just how it can be helpful but how it can be hurtful. Um you look at some of those trends like I mentioned social and mobile. two technologies that were incredibly transformational. Um, democratizing voice, democratizing access to information. Um, but it we didn't ask ourselves like is this going to make us anxious? Is it going to make us addicted to our devices? And it took us like a decade to even put controls in place. So being so transformative, it's important that we also take this moment right now to ask ourselves those questions so we can do it responsibly. Do you think that like I feel like the conversation around AI like everyone has a really really strong opinion. Jasper's very much leaning into that strong opinion to drive marketing. Um do you think that people have such a strong reaction because we've seen how within our lifetimes like social media has changed, smartphones have changed, like things are totally different within a span of like 20 years. >> Short answer, yes. Um the longer answer is this remains the same that the fear the uncertainty and the doubt is very prevalent in us as humans and marketing you know that says don't hire humans it does it it creates that like whoa what's happening am I not going to be relevant um but it's a wakeup call to all of us it's an opportunity right now because we are all on the same starting line we are all learning this now and so I look at this also Alo is an opportunity for potentially equalizing things because whether you're a woman, whether you're a man, no matter where you live, it's an opportunity for us to all learn now. No matter our age, you know, it's an opportunity for us to all learn and be part of this new transformation that we're seeing uh in in the industry. >> Yeah. And something I've been thinking about throughout disrupt is that like last year, the year before, I also moderated panels related to AI and just the amount of like what's theoretical and what's tangible shifts so much year to year. And it's such like just a time capsule of where we are yeartoear. And so on the topic of hiring AI agents, I feel like last year that's something that like didn't seem as possible, but now it's seeming a bit more possible. like how do you think that this has evolved recently? >> Yeah, I can I can jump in there. So, a year ago, the models were so early and the capabilities were so early and everyone was racing to build products and racing to build different types of agents and different app AI companies. But you could see that the majority of the time it wasn't working well. Like even even our product a year ago did not perform particularly well. like we were trying to to manipulate the models into creating a good a strong output for sales, but it was extremely difficult at the time. We've really had an inflection point in customer outcomes and in the ability for Ava, our AIBDR, like outbound sales rep agent, to actually drive real results this year and especially in the past six months. there's been this, it's not that there's been dramatic improvements, it's that there's been improvements in the areas that were really strongly lacking and strongly holding back companies like us from creating these real AI agents that can actually do productive work for you. So I think we're going to continue to see that shift over the next couple years where even if there's not dramatic improvements and dramatic leaps forward even with incremental improvements we're reaching a point where a lot of use cases and a lot of more simple mundane roses repetitive junior roles are able to be automated and able to be augmented with AI whereas before they they weren't as much as people were trying to. >> It's interesting when you think what a difference a year makes. So about a year ago uh last year at Lattis we actually uh had some innovation within our product to document uh digital workers as employees and we shared that innovation. A very simple LinkedIn post, no marketing dollars behind it. Um it went viral, people went bananas and I got all kinds of lashing because this idea of putting an AI in the org chart, they're like that girl is crazy. I don't know what she's talking about. I got clown emoji, all the things, >> right? It wasn't 67 then yet. It was Anyways, but um >> yeah, >> I'm not that cool. >> But I got like a visceral reaction. People said, "You're making AI human." And it was not the intent at all. It was a big misunderstanding was what we saw was we saw what was coming and we said, "This is going to happen and we need to be ahead of this." But a year ago, people were not willing to understand that AI could be an employee. But now, I mean, it's all the marketing and it's what everybody's looking for is how can I have AI employees? >> Yeah. >> And work together with my people and how can it really help me be successful as a company? >> Yeah, that makes sense. We we still get a lot of backlash as you can imagine with our we I kind of we kind of deserve it with our marketing, but uh there's definitely a good portion of people who don't love the idea of AI employees and and the the tagline that we have. We get some really interesting submissions on our website inquiries form. Yeah. >> Yeah. But that's the thing was that having AI employees, what is important is that we don't do this irresponsibly. So when you bring in any entity into your organization, there's rules like we're going to abide by our company values. We're going to mind our confidentiality. We're going to have goals that are aligned to the company goals. and you need to perform based on those goals. And if you're not performant, well, then we can, you know, part ways. And when you part ways, you agree to not take any company confidential information with you. And those processes need to be applied to humans, but they also need to be applied to any entity which you bring into your organization. And so that is the thing is that um there is yet to be full education. This group here is very educated, but the majority of people don't fully understand that the agents are being given access to your data systems to act on your behalf autonomously. That means they're not given a, you know, decision tree, a binary set of rules. And so that requires us to have a lot of thinking not just from a cyber security standpoint but really from a access control and governance of what these agents are allowed to do and have that documentation of when the agents acting um versus yourself. >> Yeah. And I also wanted to ask you about like related to AI employees being part of the org chart. Like as a manager, there are very concrete skills that a manager can learn about how to manage humans and just navigating being a good manager to your employees. How does that change? Like is there something that people need to learn about managing AI employees as well? >> There's a ton to learn, right? Um, but here's I'll actually flip that a little bit because here's what I think is so interesting and powerful is that whether you're a manager or an individual individual contributor or an executive, you're just an employee at a company. Um, you want to come to work and know that what you're doing has purpose. You want to know why you're doing it, how you're doing at it, and you know if if there's any feedback about it. And this is something which has been very hard at work because we have so much information that comes at us. Um it's interesting when you think of all of our systems, all of technology that we've built has been around how you manage information. And information itself is um really there's only four commands used to to manage information. You know, you create, read, update, delete, you know, CRUD. And you think about how we as people have been put into these systems. Like think email for example. If I send you an email and you read it as a person, it doesn't mean that you've heard what I was saying. It doesn't mean that you have listened to the message. Doesn't mean that you are going to necessarily remember it. Not guarantee you're going to take action from it. And if you do take action, is that action what I wanted you to do or not? And that's because as humans, we are emotional. We are not programmable. We are imperfect. We are very different than information. And because I don't think any human would say, "Yeah, I can be run by four simple commands." Right? So when you look at the idea of managing people or managing AI agents, we're fundamentally different. And so managing people AI can help us understand more nuance and un information but the AI is going to be very much around the information and looking at it very differently in how you would um manage it. >> Yeah. Um I think for the vast majority of use cases probably all we're not quite at a point where you actually have to manage an AI employee yet. Like for example, our product is Ava. She's an outbound sales rep. Does like the BDR workflow. >> She's also a model in your ads. >> She she is. Yeah, she's she's famous now. Uh you have limited inputs that you can give to AA. So like there's there's different structures that go into creating the message. You can choose the pain point she's bringing up. You can choose the proof points. You can choose the inputs to to create the emails. You can add coaching. So you can say write the emails like this. Don't write write them like this. So follow these guidelines. But there's not a broad set of inputs that you can give to Ava yet. We're working on a 2.0 version of Ava, which we're going to be launching at the at the end of Q1 next year. That product will be more like a real AI employee where you'll be able to talk to her on Slack and you'll be able to say, "Okay, I want you to spin up a campaign, that kind of thing, where you'll actually be managing them more proactively like you would a human employee. But for all use cases where you have agents right now, like things like Claude Code, um any of the category leaders, they're not yet at a point where you need to manage them. But I think we'll we'll see that over the next couple of years. >> Do you think you'd ever have an issue with like if like would the AI like talk back like as like in like will will the AI have sick days? Like what what happens if >> she did she did speak back to me the other day like I requested a sample email from the the thing in our booth and she sent an email to me saying this is not a realistic scenario because you're the CEO of this company and I'm not selling the product to a CEO. This seems to be some kind of demo situation. >> Oh my god. that that would happen in practice for the majority of people, but if you don't build in guard rails, then the model can talk back. Um, but yeah, that it's not going to be doing anything as bad as a human would do. Like we we just put up some some bus shelters. One of them was like artisans won't get caught on the kiss cam with the head of HR. AA's never going to do that. She's never going to get into a scandal. But >> yeah, >> I mean I I mean I guess you could argue she has been and like she she a lot of >> That's my fault. Her fault. >> Yeah, you're taking the fall. >> Yeah. Um, >> but that is that is the also some of the things is that you don't know exactly what they're going to do. So when you have agents having conversations with your employees or with your customers, you need to have them grounded in your data in the context. And so the context is so important. And so just having an LLM that you put out in the wild without grounding it securely with the right context is it is dangerous. >> Yeah, you're going to get some crazy >> and there's also um there was a study that just came out I think yesterday um around the imper the the how confidently the AI will say something which is not correct. And so that accuracy it comes when you don't have the good data grounding it. And so yes, the internet is is one place where you can say that data is not always correct. Hopefully within your enterprise, you're in a world where you have more correct data. But it's still the same issue is that I mean raise your hand if your data at your company is perfect and you know 100% accurate. Um just kidding. I don't know. >> Good. I'm so impressed. >> I don't deal with the data. I don't know what's going on. But this is what we just have to we can get very excited also from a security standpoint. There's a lot of pressure right now from people like ourselves, CEOs going to their companies and saying, "Put in AI. I want some AIB BDRs. I want this efficiency. I want this now." And people's like, "Okay, yes." And then they do it and they'll miss some steps, you know, putting in passwords like 1 2 3 4 5 6 and things like that. Which >> humans do that a lot. >> Yes. Right. And so we just have to be very mindful um in what it can do because it could put yourself in a bad situation if it does have a bad conversation with an employee or a customer. >> Yeah. And that was also something that you had brought up when we talked about before about how there's certain things that AI absolutely should never do like giving employees performance reviews because we know that an AI has to be trained on something. what it's being trained on reflects the biases of the broader world and there are biases and prejudices in the broader world unfortunately. So like how do you think about like making sure that a workplace remains equitable even with an AI that might have like certain biases. >> So this is where I think there's opportunity because we as humans we all have unconscious bias. It's not just race or gender. It's location, proximity, language we speak. There's uh recency bias. There's so many types of biases. And our human minds are not capable of absorbing all of the information that surrounds people and situations and um everything the context that we would need to know to make as objective decisions as we can and especially when it comes down to somebody's performance. And so the opportunity is that and this what we're doing at Lattis is that I mean who here enjoys writing performance reviews no hands go up right um it's something which is looking in the rear view maybe six months people have to be dragged down to you know reminded five times to go and hunt and peck through all of the information to write a review where the AI can bring it to you have all that context for you summarize it for you and then you can apply your human judgment in a way that is much more fair, much more grounded in context, much more understanding and we can have more human conversations which today time zones alone are hard you know to manage employees globally and so this is something which I'm excited about but I do think that yes when the AI brings you all this information it can even draft things for you. But as a human, we should be making human decisions about somebody's performance or their pay. >> Yeah. And Jasper, you had also mentioned that you wouldn't advise someone to use an AI agent unless if they're 100% confident that the AI won't hallucinate. >> Yeah. >> How do you evaluate that 100% confidence? I would say you don't want to use AI for any task where you need 100% confidence because you're you're never going to get 100% of the time the exact output that you want because LLMs are ndeterministic. Um so but but use cases like humans are also a lot of the time wrong. Like humans are definitely not >> I've never been wrong in my life. >> That's fair. That's fair. That's same. Uh uh but if you're in a lowrisk situation and you're doing something where maybe 99.99% accuracy is good enough, then it makes sense to have an agent. If you're like dealing with the nuclear launch codes, maybe don't put an AI agent in charge of them. But yeah, I think that's pretty self-ex. >> Yeah. Yeah. And then I wanted to go back a bit to um just the general attitudes around AI agents and how like I'm sure all of us in this room would love to have jobs and like have a secure income. And something interesting that Venard Kosla said on stage yesterday was that as like if we approach AGI >> um that the US government should take a 10% stake in public companies to soften the blow and redistribute that money. Do you think that's a good idea? >> Would you rather have a job or get your salary without having a job? I would rather get my salary without having a job, but then I also would worry that like >> I mean there there's just so many questions about like how would that be enforced? Like would companies agree to do that? Um >> would like >> I don't know. I mean there's the the question of like I mean I know there's this is why people are doing studies on UBI but >> I think in the abstract scenario where we actually did achieve AGI um which is kind of what our ads ads insinuate. It's like that's what people think when they see our ads like oh no everyone's going to lose their jobs. Um which isn't realistic with with current technologies like we're just not getting close to that really right now. But in the hypothetical scenario where we did have AGI, inherently that would mean that we would need UBI because there's no way that you could have a handful of people controlling 99.9 recurring percent of productivity in the world. Like it's not a realistic a realistic scenario for for the global economy. So I do think if we were to have AGI, you do need UBI alongside that, but we're far away from that right now. Yeah, >> I would add maybe contra contradictory perspective but I have this conversation very often especially when you think about life and you think about the purpose that we the purpose of life um you know last year I lost uh my parents and things like that make you really think like okay what's what is the purpose and meaning for being here you why do I do this all day and work is deeply personal Many of our identities are intertwined with our work. Does it mean we should be burned out? No. But does it mean that I want to sit and like have my brain rot because I'm not doing anything? Like that's also no. And so this is what's an interesting thing is that if it can be something where whether there's UBI or not um a lot of people are choosing the whole you know touch grass like be more human be more present and there's a lot of value into the humanto human engagement. So maybe a lot of the wrote pieces are done for us but we can then spend time having you know better human experiences like think customer service for example. It's a common thing that they want to you automate the customer care. But if I want to go shopping and I have a I can have a concierge level onetoone human experience with somebody. >> Yeah, >> that sounds incredible. But companies can't afford that today because they still have to have the people doing other other things. So I think there's going to be a shift. It's going to take time. Um, I'm more optimistic that we will have purpose as people and I don't think we want to not have >> Yeah. >> jobs. >> Yeah, I agree. I think inherently humans are always going to find some way to have purpose. Like if we look at the jobs 100 years ago versus today, if they saw what we were doing sat here like tapping on these magical screens like doing like HR, like that that's just like a a an extraordinary concept to tell like someone who was a farmer near a village. Um, and I think we're gonna see another shift like that where the the labor that we're doing in a hundred years we would now maybe see as fake work, but it feels real in that in that >> my youngest um who's now 21, but I remember uh one day I came in and she was this is when you had like the DVD things to watch movies and she was sitting on their DVD and I was like, "What are you doing?" She's like, "I'm working." Like, "What are you working at?" She's like, "I'm working watching Sleeping Beauty." I was like, "That's not working. Mommy does work. She's like, "No, you're working, too." And but that perception of Yeah. like like you're tap tap tap tap tap. It doesn't >> It's not like I'm out there like digging ditches or >> you know and some of those things. Yeah. Um and some of the you know simplest things are are the we thought might be automatable. They're they're not. You know that there's a lot of infrastructure type of work which is very much like human. Also, you could never really automate art, for example, because art is inherently human. Like, if a if a robot does art, then it's not worth anything because the value comes from the story behind it. And I think there's a lot of things like that that will emerge that are just impossible to automate. >> Yeah. >> Yeah. And then getting more toward like things that founders might be thinking of right now with um hiring, knowing when to hire AI and that humanness. I feel like something that founders really love is being in the room with your team and like working on something from the beginning and like all just kind of like coming together. And do you think that people would feel lonely if it's like them and like three AI agents? >> I don't think it's really any different in practice right now to just like using some SAS platforms. Like it's just like a a SAS platform that will do work for you autonomously. like you're still going to need a human team for the roles that that aren't possible to automate yet. Like for example, uh one of our users, they have like six different AI agents doing different things for them. Ava manages all of their outbound. They use qualified for like their inbound sales. They use another agent for their customer support. So they they have this team of AI agents that are managing a lot of the org, but they still have an office where they go into every day where they all are together and just like they they have the agents working inside their computer. So I I don't think it's it's not a binary you have to have agents or you have to have humans. Like inherently you're going to need humans. And you can just you can speed up your time to value. You can speed up the time to to achieve product market fit. You can grow faster. You can achieve more if you build an AI first organ if people are focusing first on finding a way to automate something before doing it manually themselves. And I think this will be a much more healthy workplace because I was sharing earlier we are drowning in information as humans when we go to work. And we think that that is we we've somehow led ourselves to believe that this is the right way we should come to work. We should come to work with a full inbox, tons of Slack messages, notifications on our phone and supposed to like go and understand what's happening. And so all this information is not how we as humans thrive. So when you can have something sorting through the information getting it there you can come and you can have like a conversation you can know what you should focus on and you can be present and the humans then have a much better experience because we're not sick from like too much information like we're not information diabetic you know we are we are healthy and present and able to have those conversations and enjoy what we do. >> Yeah. Um I have one more question and then we have time for a Q&A. So if people want to start lining up at those microphones then we will get to that. But um my final question is I was thinking about how last year Sam Alman said that he has a group chat of CEO friends which one dying to know what that group chat is called but um apparently they have a bet going of when the first solo unicorn will be like when is it just one person who with AI scales a company to be a unicorn. Do you think that's possible? And if so, what would your bet be? >> Yeah. >> Who wants to go first? >> I can I can jump. So, let's say someone wants to build a unicorn. Say they're in like a really hypy space, they can maybe get like a 50 to 100x ARR multiple. So, then they need to get to like 20 maybe even with 10 million AR they could hypothetically get there. I don't see any reason why you couldn't with with the direction that first of all coding tools are moving in. I think the person would need to be technical because they need to be able to understand how to use cla code and to manage it effectively. The person would need to be also good at marketing because even if you're using tools like Artisan and you're using other products to to automate some of your marketing, you need to manage it. But I don't see a reason why one person couldn't build a product that's got some sense of product market fit and then market it to achieve 10 to 20 million AR and then raise a unicorn valuation in the next like 12 to 18 months. >> Yeah. >> Interesting. I would agree. I agree. Um I just go back to uh we as humans work better when we have ideas from each other and I think it I think it would be lonely. Um I'm an introvert myself so I do you know not pretend that everyone may want that but um I do think that the the possibility is there in the current time frame. >> Yeah. Okay. So let's move to Q&A. We have about 10 minutes and we want to make sure that as many people as possible can get their questions answered. So try to be as brief as you can and we'll start on this side and then we'll go back and forth. >> So you first. >> Hi, I'm Meera. Um I I had a question regarding uh assessing confidence in agents. We talked a little bit about uh you know assessing risk in like whether you can deploy them in such and such scenario. Uh, I wonder have have either of you or your teams or are you Yeah. Have your teams worked on like confidence score determination of what LLMs do and like using that in the workflows? Yeah, I mean we we we do measure accuracy and we do um which is different than confidence I would guess, but we do um ourselves make sure that um we have the accuracy measures there and we also have the back stops where people on the back end can look through all responses and just audit them I would say. >> Yeah. Um so our product like I mentioned is is an AI outbound sales rep. So the the output is very measurable like did you get positive responses? is what's the cost per lead you're achieving? Is it higher or lower than what you were getting with a human team? So, we just look at that as a benchmark and compare to the humans. >> Cool. Okay. So, that's an accuracy metric. >> Uh no, just like a a comparison of benchmarks, I guess. >> Okay. Thanks. >> Great. So, we'll go to the side. >> Hey, um my name is Gus. Uh this is for Jasper. Um, as a serial chief revenue officer in early stage technology companies, I I think you're on to something super fascinating. Um, because managing BDRs and SDRs nowadays with the science you need behind them uh to do things, I think you're just going to accelerate all of that. So, I think it's it's it's a very exciting space to be in. My question for you though is how can I join your company? >> What was the question? Sorry. >> How can I join your company? >> How can you join? Oh, well, uh, we only hire AI agents. I don't know if you saw the ads. >> Unfortunately, we're full of humans right now. >> I'll I'll speak to Walker. >> Okay. And we'll go to this side. >> U Yeah, thank you very much. I uh such a great uh discussion. So my question is about an article that BBC wrote about a rogue AI that turned into being manipulative as we see. Let me put a context into it. Uh are you building everything from the engine ground up based on your own infrastructure or you are buying some other spaces from other differences? The reason as to why I'm asking this is number one, how will your agents handle competition in making sure that an employee does not ship some secrets uh to outsider? That's number one. Number two, how will you handle the friction because the friction brought in the manipulation AI actually manipulated the system engineer and told the engineer if you try to shut me down, I will send an email and say that you are dating the HR and the engineer was confused. Yeah, that's >> Yeah. So, we don't build models. We just work with Anthropic and Google and Open AI. That's really them. You're gonna have to ask Sam Alman. I can't answer that. >> Yeah. >> Okay. Um, let's go to this side. >> Okay. Hi, I'm Joe. I have a thought and I'm just wondering about your reaction, what your thoughts are. So, this is really about AI displacing human workers. My thinking is that um you know in previous technological upheavalss there have been accompanied a similar effort to develop new jobs or types of work um that would better leverage whatever the new technology is. Obviously um the AI technological upheaval is of much greater and you know at more broader scale but so is the challenge to do that development to to create those jobs that better leverage the technology. So my question is um do you see such efforts starting emerging somewhere in the timeline you yourself being involved what you would like to see let's hear your thoughts both of you. Yes. So I think the question is around just general like what we're seeing with the human transition that we're seeing um compared to other technology shifts whether it was cloud or manufacturing automation etc. So yes technology has always bred more job opportunity uh in our history. Right now it's the time period is so compressed and we saw trends happen. for example, uh um college graduates, you know, are having a harder time getting jobs. Um and it's because at companies when you're looking at, okay, I need to change my workforce, the easiest people to, you know, lay off are the people that I haven't hired yet. So, it's it's much easier to say, okay, we're just going to pause that. And that was so fast that we felt that in the system. you know, my kid's graduating college this coming year and like I'm like, you need to be on top of this, right? But these people are the most digitally native, the most AI comfortable, the most um malleable, the least calcified in thought, and they are the cheapest as well coming out of college. So, I think that's temporary, and I think that we're going to see that adjustment because now people have said, "Okay, there was a shock into the system. We need to adjust. Now, we've got to normalize and we need to figure out where people are going to go. But historically, we've seen job creation. I'm an optimist. I do think that will continue. I do think that it won't be tomorrow that we'll have um AI agents doing all of our jobs. But it does not remove the urgency for everyone to go and make themselves not just understanding at a high level but well-versed and um uh not just literate but fluent in AI. >> Yeah, I agree. I think the the bar is higher for graduates. Like you can't just go to college, not do any internships and expect to get a job without any real world experience. Like you need to put yourself out there. You need to proactively learn how to do things that are unique that AI can't do and upskill yourself so that you can more easily get a job. >> Let's go back to this side of the room. >> Hi, uh my name is Alec Haya. I I had a question about um we talk a lot about what AI can do um but there's a lot that it still struggles with. um what are the things that you guys are actively working to make better in the process? What do you think the biggest weaknesses are, especially the weaknesses that are here today and are somewhat temporary? Um and then the weaknesses that you think might hang around and be a little bit harder to kind of weed out. >> Yeah. So, I think the one of the biggest weaknesses is the nondeterministic nature of AI. Like we're and that that's not going to change with LLM. It's very very unlikely that will change and you can build evaluations and you can do a bunch of things to minimize the error rate of models but you from what we can see you're always going to have that until we have some major leap in in the technology. Um, but more practically with the way we're implementing LLMs now, cost is a huge barrier. Like you you can't use an advanced model for a lot of different use cases because it's too expensive and people aren't willing to pay that much for the work output and it would be cheaper maybe to get someone in Asia to do it for you than to than to get AI to do it for you. So that's going to be one big barrier until the cost of tokens continues to come down. Um, there's a lot of use cases that aren't yet solved. One that we're trying to solve right now that we're working with Anthropic on is handling back and forth communication between a human and an agent and consistently holding that conversation all the way through from a response to an outbound sales email to having a meeting booked in because there's this tree of infinite paths that the conversation can go down and they can ask like what's your dog called and then the AI needs to know what to say and can't just lie and say like toto or whatever. So you need to you need to have a lot of infrastructure in place to make it effective in these kind of use cases. And there's so many areas in which AI cannot achieve specific job functions that we're just going to continue to to try and evolve and and and be able to do. >> Yeah, the the context is so important and that's also what we're doing and this is like a sales use case. ours is in HR and that contextual grounding for the prompt is the behind-the-scenes work that a lot of the applications are putting into place and so without being able to have those um ongoing conversations the context gets lost but as humans that's the thing is like as humans I can meet you right now I can have a great conversation and then can go off do five other things and if I saw you on the street later I could remember it right but if I was an AI if I've stoped that conversation when I pick it back up, I'm not going to remember it. That context is lost. And then you feel like this was a meaningless conversation because you haven't remembered me. >> And so that is a that's a big opportunity. And it requires on the back end for us as technology providers to build that infrastructure so the context can be um maintained and also um appropriate and respecting permissions and and all those things. So that's that's the value ad that we can um provide and the the large language models. It's just like when Amazon made EC2 and S3 um it it made it easier to have you know computing infrastructure anybody could go build an application but they just made it easier to do that work on the back end. in the LLMs like we're not I'm not building a large model have a small model around like employee health similar to like how Aura makes like a health but not a large language model. >> Yeah, same. >> Thank you. >> We are out of time but thank you both for fast. I know it always goes by faster than you think and I hope this was helpful for I hope this was helpful for the audience and thank you for coming to disrupt. >> Thank you everyone. Hi Ava., YouTube Video 2z0WM3CWgX4, YouTube, 01kacq1b63n1p0hnxz1nn7fpdj.