Why the Future Belongs to Agentic AI with Daniel Saks, Landbase

I think everyone I speak to knows that AI is the future. I think there was a phase for a decade where the majority of people didn't feel comfortable with digital, didn't know what it was and needed to be educated. And there was a position where you could position from like fear of if you don't transform, you will fail. And the reality is what manifested over the last 15 years is that those companies that didn't adopt the new did fail or are a relic of what they were. A GE or an IBM relative to a Microsoft or a Google, who would've thought? So I think that we're past that. It's funny but there was this push from like when SaaS emerged to digital transform and I feel like the world's digitally transformed at this point. It's totally different. It's will AI leapfrog and take your business? And is what you're building gonna even be relevant in two years, six months, a month from now? So I think like those who are closest to building the research and the foundation models, I think recognized not only the disruption of the models, but now starting in 2025, the dramatic cost reduction.

Welcome to another episode of our Traction podcast. This is the Next wave. The Next Wave is a different take on our podcast where we're bringing back some of our most favorite guests that have either graced our stage or joined our podcast 10 years ago, five years ago and we're going to revisit their topics to see do they still hold up in Today's World of AI Trust. Traction is brought to you by LaunchAcademy CA, one of Western Canada's main tech hubs and an international accelerator program that provides you access to the Canadian startup visa as well as boast AI your go to partner for R D tax credit. We're back with another episode with another great guest and friend of the pod, Daniel Sachs. He's a serial tech entrepreneur and CEO and co founder of Landbase, a company dedicated to transforming go to market strategies through the integration of machine intelligence and human performance. Prior to founding Landbase, Daniel co founded and served as Co CEO of AppDirect, a global leaders in subscription commerce platforms where he helped the company achieve unicorn status. Also a great partner for Traction, we hosted a conference together in San Francisco which was a tremendous success. Daniel's been on the podcast many times, but he graced our stage in 2015 and we're going to get into a lot of great clips from that. But through his career, Daniel has been recognized for his innovation and leadership earning spots in Forbes 30 under 30 and being named one of the most exceptional entrepreneurs by Goldman Sachs. He is also host of a popular podcast called Decoding Digital, where he interviews leading experts on topics ranging from venture capital to digital transformation, helping listeners navigate the fast evolving digital landscape. In addition to his entrepreneurial ventures, Daniel is trusted Advisor to Fortune 500 companies, helping to build software distribution and cloud strategies. He's a graduate of McGill University. He serves on the university's principal international advisory board. And beyond his work in tech, Daniel is an avid skier and enjoys spending time outdoors with his wife and two children. Daniel, welcome back to Traction.

Hey Ray, Great to be back on the pod. I wanted to give context to my background both at AppDirect and now Landbase. So I started in Silicon Valley in 2009, really at the height of the Great Recession, just when cloud was emerging, and really had this vision about how do we make cloud services, which were just emerging, accessible to businesses around the world. And the goal with AppDirect was to make it easy for businesses to find, buy and manage these emerging cloud services and digital services. And I Co led Appdirect for the better part of 15 years. And really throughout that growth, we saw a SaaS industry which is in its infancy. So in 2009, the first thing I did was create a list of SaaS apps and got to know founders or early team members. And this was Aaron Levy at Box and Drew at Dropbox and Harley at Shopify and Michelle and Matt at cloudflare. And these were literally like tiny companies, just people that had cool ideas and the market was really small. But I had high conviction that SaaS would be massive. And if you look at what happened over that next decade, SaaS didn't only eat software, but software ate the world. And today we see it in the zeitgeist that every company is a digital company and is a tech company in order to survive and thrive. So if you fast forward to the founding of Landbase a couple years ago, my view was that the biggest pain point that businesses face is generating predictable revenue or leads that convert. And it became really complex over the years to be able to target customers or prospects, know how to reach out to them and what channel to write and what message. So when large language models were emerging, we really dug into machine learning and uncovered the potential to create a new generation of models that went beyond understanding language, but that understood action. And we trained the world's first agentic model purpose built for go to market. I would define agentic AI as AI that takes Action based on data. So therefore you can execute a task or workflow such as generating leads. And the theme across my whole 15 year plus career has been helping B2B businesses thrive through access to technology and really opportunity your new channels and go to market avenues.

So you've been at the forefront of many tech trends. So you went from Cloud to SaaS and now you're jumping into AI. So this is going to be a really interesting conversation. The last 10 years, so many things have evolved. I want to jump into our first clip, really focusing on enterprise sales. You had some really great things to say on stage and we'll see how that's bridged over to today's world with AI.

So first clip, when we were two.

People in an apartment, our focus was to make money from day one. And what we said is, how do you make as much revenue from the onset it's probably signing a really big deal. So all of our focus went into making ourselves appear mature, permanent, long standing to get the confidence to sign a big deal. Our first deal was actually with Bell Canada, who everyone knows here. And at the time if we went to any vc, they would have said, you're crazy, there's not a chance you're going to be able to sign one of the biggest companies in Canada. And what we said is, okay, in order to do this we need to really look like we have something special and, and that we're giving something that they can't get from anyone else. So what we did is we spent a lot of time establishing the methodology and the thought leadership around cloud and why telcos would be well suited to service cloud and why AppDirect was the best opportunity for Bell. And I think one of the challenges in the startup ecosystem is that a lot of people when they're starting is they want to be hackerish, they want to be casual, but that doesn't fit with enterprise culture. So what we did was actually the opposite. We wore suits and ties every day. We printed decks that were like consulting style, old school and we micromanaged the quality of those decks. We used to learn and I used to interview people that worked at telcos and like government and all those traditional industries to get a sense of what their culture was like. And we totally adopted for their culture. So one of the things we came up with in the early days was the notion of a culture karma chameleon. So how do you like adapt to the companies you're working with? And that was so much a part of how we evolved.

There's so Much to unpack here. I love that this is the first clip. First off, as a Canadian, I love a Canadian reference. Daniel, you're a proud Canadian as well, going from enterprise thought leadership to cloud thought leadership to AI thought leadership. Back then you said you're putting handbooks together and whatnot. There wasn't much thought leadership out there. That was a brand new term. If not, it might not have been anything back then. You probably helped cultivate what thought leadership is to today, where everything is coming out so fast, new language models coming out, new features coming out. How do you stay on the top of being a thought leader in AI in today's world compared to what you did with Cloud and SaaS 10 years ago?

It's really interesting to see that click because starting the company for the second time, you would have thought I would have taken a lot of the playbooks and learnings, but I actually did the exact opposite of that story. So right now we're targeting SMB as our primary market because we think it's an easier way to learn with faster feedback cycles and without complication around data rates. So our initial target customers B2B, smaller companies, non enterprises. I haven't created a printed deck in two years. I'm not wearing a suit today. So it is very interesting if you look at the differences, some of the reality to your point on thought leadership, I think the reality is that in 2009 there were maybe a hundred companies that were really working on SaaS that were players that you could find. Maybe you could argue that there were a thousand others. But in terms of my definition of true, like SaaS, native multi tenant SaaS, there weren't that many. There were a lot of ISVs that were maybe saying hey, we're cloud, but you could tell they weren't. I think that's similar to today where there's not that many agentic AI companies that are actually out there at the application layer. If I were to count, there's Lambase, there's some in our category, there's Decagon or Sierra or DevRev or poolside. But I still think in terms of true native capacity at the application layer, there's actually a limited amount. But the biggest difference is that there's so many people creating so much content and so much noise in all the media channels and becoming like you mentioned my background at McGill. When I was at McGill, no one ever went into entrepreneurship. We didn't even talk about it. Now you go to campus and everyone wants to be in tech and there's this entrepreneurial ethos across Montreal and Canada and as of Silicon Valley. So I think that if you were to compare and contrast, it's almost like literally 180 turn in the kind of it being cool to be a founder, the related content or the amount of thought leadership out there. So it's, it's a totally different world.

So how do you make yourself, as Lambase and Daniel Sachs stand out in terms of, hey, we know what we're doing with AI. We are agentic AI natives and you should be doing work with us, we should be helping you go to market. How do you stay at the forefront of that?

It's really hard. So in, like I said in 2009, maybe there were two competitors to AppDirect. There was Dropbox and Box and there was Shopify and Wix or Magento or whatever. But there weren't that many competitive tiers. Like literally we thought we were ahead of the curve in coming up with our category and I can't even keep track. There might be like dozens and dozens of funded companies and then maybe a thousand bootstrapped or family, like maybe like angel companies. And then there could be like, I don't know, there's just a sphere like out of everywhere. So competition is rampant. Everyone says the same thing. I think the reality is it's hard to position differently. In my view, I bring it back to the same first principles. Where do I have strong conviction in what I see differently in the world and how can I build a lot of moats to give me a durable competitive advantage? So I think in this era, which would have been the same as 15 years ago, a data moat is a way to win, to have an algorithmic advantage, a talent moat. So get scarce resources. So for example, our chief data scientist was a Stanford PhD in Neural Networks that started a Sequoia backed company that got bought by ZoomInfo. I'm kind of like the only person in the field that's been working on neural networks and go to market for 15 years. And then we've brought in the head of machine learning from Crunchbase and the person who designed workflow engines at YouTube. So very scarce resources for what we're doing. And then there's capital moats. I think the reality is today, especially if you look at the foundational models or some of, let's say the code gen companies, their advantage is just a capital moat. How much capital do you deploy to be the biggest? As fast as possible, but the bar is higher than ever. So I don't think it's enough to have just a capital motor talent moat. You need to have the traction and you need to have the brand. You need to have a sexy product. So it's a really high bar.

And talk about high bars. You've got a great team, you guys, for all those purposes, you know what you're doing and you guys are leaders with the term of culture, karma chameleon with the enterprise where you're adapting to them. Do you find now that because you're at the forefront of AI, a lot of people are trying to catch up or SMBs are trying to figure out how do I adopt this into my workflow? Are they now trying to mimic what you guys are doing and where you're putting go to market and thought leadership? I think in the SaaS that gotten 180 as well, where instead of you trying to mimic the enterprise, the SMBs need to start thinking like you and acting like you and taking your lead.

Yeah, I think like in SaaS in 2009, no one thought that SaaS would work. So you faced resistance from enterprise, you faced resistance from small businesses, you faced resistance from the incumbents. So essentially like from 2007 when Cloud or SaaS emerged to 2014, I honestly think like most people just said this isn't going to work. It's all about on prem and this cloud thing is going to fail. And in AI it's the opposite. So you have incredible tech incumbents, you have all these like unicorns, you have Fortune 500, you have startups, you have small businesses. Literally everyone knows that they need to be AI centric and they're really good at adopting it. Everyone has become a technology company. So I think it's like again, like 180. Where in the past era I faced resistance nine times out of ten. In this era it's acceptance nine times out of ten. But there's a million different options. So the client doesn't understand the differentiation between you and the thousand other people out there.

Oh God. This is a great segue into how people actually evaluate risk. Let's jump to the next clip and we're going to talk about enterprise risk versus S&P risk.

So much of this is just encouraging a culture of innovation. And I'd say that any CEO, no matter how mature the company is, no matter how mature the person is, they know that their companies are going to be disrupted by technology and they need to take action. Those that don't will be left behind. So I think a lot of the sales positioning when you're let's say a younger tech company or pretty nascent, selling to a bigger company is highlighting that risk. So highlighting here's where the market's going, here's how technology is disrupting your company, here's the researcher unique value that we know that you don't. And now let's work together to really address your long term value.

You gotta like flip the narrative from we're risky to we're the safe bet for our risky future.

Yeah. And we can help you in the long term.

So I love that at the end like we are a safe bet for a risky future. That's every startup needs to eat that dog food and convince the people that they're targeting that. No, we are the ones that you want to bet on. Even though we might be new, we might be a small team or this technology is just hitting your radar now, but you need to brace for the future. And I think that can't be under stressed in this day and age with AI. AI is touching so many different aspects of not just the workflow in a business, but people's day to day lives. And we've had numerous conversations this week of how people are actually using G ChatGPT or perplexity for their own personal lives, just let alone their work life. And so how are you seeing people, especially in the SMB world embracing AI or acknowledging that it is something that they need to start thinking about now rather than later?

I think everyone I speak to knows that AI is the future. I think there was a phase for a decade where the majority of people didn't feel comfortable with digital, didn't know what it was and needed to be educated. And there was a position where you could position from like fear of if you don't transform you will fail. And the reality is what manifested over the last 15 years is that those companies that didn't adopt the new did fail or are a relic of what they were. A GE or an IBM relative to a Microsoft or a Google. Who would have thought? So I think that, I think we're past that. I think it's funny but there was this push from like when SaaS emerged to digital transform and I feel like the world's digitally transformed at this point. It's totally different. It's will AI leapfrog and take your business? And is what you're building gonna even be relevant in two years, six months, a month from now? So I think like those who are closest to building the research and the foundation models, I think recognize not only the disruption of the models but now starting 2025, the dramatic cost reduction. So in my view the last couple years the predominant let's say investor mindset was let's pour money into the infrastructure layer and let's drive a lot of training costs and there'll be a few leading models. So I think I saw this in the infrastructure layer with Cloud in 2009, which was from 2079. Let's say there was a war to figure out who would win and IBM had Savvis and there was Rackspace and there was all these brands that were actually bigger than aws and Azure didn't exist and. But I think what happened was like there was this infrastructure war and it played out over a few years but most of the value from that infrastructure war where so much capital was deployed, like literally every telco was buying a colo center and it was like a ton of cost, right? And there were only really three winners. It was aws, Azure and, and gcp. And I think it's very similar where there's like a infrastructure war right now, a ton of capital being deployed. But I think there'll be a couple winners, maybe a few. Luckily due to open source alternatives, I think that a lot will go to open source. But now I think the question is like where does the value accrue at the application layer? And I think that a lot of incumbents will do a really good job of adopting this technology and giving them a head start. But I do think there will be certain startups that are playing in greenfield spaces where their market opportunity could be 5x what it would have been starting a SaaS company in 2009. So I think it's a really hot high velocity market, but huge opportunity to be had.

Do you in your data life or sorry in that land base do you find opportunities and the brick and mortar or manufacturing space or is it all pretty much still at the software and knowledge base type business?

So my view is that historically there was tech and there was the rest of the world and tech would be a certain number of tools that would make up a certain amount of gdp, right? Like now it's a little bit bigger than it would have been five years ago or seven years ago. The tech to a market is just enabling humans. I think with the advancements in machine learning, you're literally flipping the model where tech used to be a tool where humans work in it. And we literally work for and live in our software. And I think the future of technology is that the software works for us. We don't work for the software and therefore, right now we're used to prompting our AI via chat, but the software should prompt us. So I think the best application layer companies will have the data and intelligence to say, here's an action you can take, do you want to take it or not? But the AI will be doing the work of what would have been done across many tools, many fragmented, let's say data sets or software systems, and a lot of siloed teams. So I, I'm a pro human kind of person, which is tech is always about humans. But I do think that this next frontier of tech is going to mean that humans are doing the higher value, creative relationship stuff and all the research, all the kind of mundane will be done by machines. And what that means from a financial profile is generally the old world or traditional economy is probably still 7, 10x bigger than the tech world, and that's tech for the taking. So if you take a lot of these service companies, an accounting firm, a legal firm, a marketing agency, a sales agency, an H VAC company, they traditionally have really low gross margins and very high cost of goods sold. And the beauty of the software business model is that you could run at 80% gross margins and therefore you see a lot more value. And I think the big unlock for a startup today is not going after the software incumbents, but going after greenfield spaces which are very manual today but could be fully automated in the future. So you're going to take a company that like an accounting firm maybe was running at 20, 30% gross margins and you're going to use AI injected in it, you're going to make it better, and in the end the value is going to be better for the customer, it's going to be way more accurate and it's going to be mainly software delivered. So it could be an 80% gross margin company. So I think that the big opportunities for startups are going to be not competing against the incumbents. Like to me, I don't think the next company that's going to be bigger than Salesforce is going to do CRM. I think it's that they're going to replace a lot of manual stuff that's going on by humans and have a data moat or advantage in the models to be able to achieve their outputs.

And this is actually something they talk about in an article that you put out on LinkedIn called the 7 Reasons that Gentek AI Will have a Breakout Year. I'm assuming you're talking about 2025 here. One of the facts, or the. I think it was the Sixth point was you're getting away from software or your day to day in software and more human interactions. And so the AI will do all the workflow and the mundane tasks, which then allows you to free up your time to actually have those face to face conversations and close deals. Because without closing a deal, you can be the best technology, best structured team. But no sales means no business.

Yeah, exactly. Our brand statement at Lambase is reclaim your day. And it's the concept that over the last decade at work, we've literally worked for our software, lived in our software, hunched over our screenshots, and that's really not that fun. And to me, what's fun is meeting face to face or working on creative problems, or doing things that make us more human. So I actually believe that while there's reality that AI is going to take on a lot of the tasks that humans are doing today, I think what it's going to do is allow humans to reclaim their day so they're doing things that are much more human and leaving the manual work to machines. So that's why I really think the key is how do you harness human performance with machine intelligence to drive really good outcomes? And that's my view of the next 10 to 15 years that I hope to see it pan out.

Yeah, I want to circle back on to closing deals because your AI is not going to close the deal for you. It's going to be the owner of this SMB or some of the people that are normally stuck behind a desk doing mundane work that can actually now talk to their clients and actually interact with them. So we're going to jump to a clip and because you've had some stuff to say on this five, 10 years ago, and we're going to look at how that's evolved now.

Ultimately, when you're working with a big company, you need to add business value. So what I'd say is that the most important thing that you should always be focusing on is how you're going to either save money or address one of their concerns, optimize for revenue, get them new business, always focus on the business value. But at the highest level, you're right that a lot of companies want to be able to show that they're innovative. One of the ways to do that is to talk about innovative companies they're partnering with. So that's definitely a way to do it, is to get in via the innovation arm and really bridge that gap.

So from that clip, like you're talking about bringing value to the table, whether you're saving money or optimizing workflows, this is speaking directly to what AI is able to do today is optimize workflows, reduce expenses, free up capital to do other things. Have you seen a shift in how to close deals from 10 years ago, or is it still the fundamental same bring business value to the table and you'll be able to close a deal?

Yeah, I mean, at the beginning of the conversation, we talked about a little like a little bit of what's changed 180. I think that there's like fundamental basics to business and it's, you know, you want to bring relevant value add products and that typically means you're going to save time, you're going to save cost and you're going to perform better. And if you can do that, doesn't matter what technology wave you're running in, you're going to add a lot of value and relevance. And I think what I get excited about is how do you do things not 10% better, but 10x better. And typically the best shot at having that disruptive change is when you're coming in early in the technology wave. Got lucky starting in SaaS in 2009, but very similar was calculated in starting Landbase today, where there's this disruption at the infrastructure layer, providing opportunity at the application layer. And the fundamentals, though, are exactly the same. You need to have as an entrepreneur, you need to have strong conviction and a vision, and then you can take a new technology or disruptive force and mold it to something that's going to be different than exists and that's very differentiated. Therefore, like probably 10x better at least than whatever existed in the past, but also a magnitude better than your competition in the future. And then it really comes down to the culture, the mission, the vision, the team, the values, and ultimately your conviction in that vision. So I feel like while a lot of things have changed in different tech waves, the fundamentals are already always there.

And do you see quite of a gap 10 years ago between Enterprise and SMBs to today? I think Enterprise and SMBs function, I think a lot like just because the technology allowed them to.

Yeah. The one thing I'd say is in terms of buying cycles, enterprise buyers are much more experimental and have budgets to deploy faster, but look more like an SMB in profile. So I think that historically the enterprise procurement process was such where it was very hard to become a vendor, it took years to get in through legal negotiation, et cetera. I think what's happened with this AI era is that people have unlocked Budget for short term tests. So I think what you're seeing in this AI native application layer era is unprecedented revenue trajectory. So land based hit 7 figure ARR within months of launch and that historically would have been something that would take a company a year plus. So I think we're definitely seeing unprecedented growth at the same time. Like when I sold some of these original enterprise deals you were able to negotiate three five year locked in agreements and that's not happening in enterprises and it's not happening for SMPs either. So I think that there's yet the pace is faster to evaluate, faster to deploy and faster to decide if there's value. Which means that the bar is much harder for products today. It's easier to try but harder to be retained.

I think we might have jumped the gun here because this is actually the topic of the next clip I wanted to share. So let's jump to the. Then we'll come back here.

Say you were to start out now. Do you think that large corporates are actually interested in products built by startups?

For sure.

And I think the way that you need to do it is again show the business value. So if you're two people in an apartment or in a garage, that's not enough to get someone to listen to you. But if you have a unique position on the angle with data driven research to back that up that someone at a bigger company doesn't see, they'll understand that value. But again you need to put it in their terms. So you can't just go and have a conversation at a coffee shop with them. You have to essentially present something that would be of the caliber that used to be presented on how they can save magnitudes of money. It has to be in the tens of millions of dollars. It can't be in the few like little things.

Think big, think big.

Okay, so speak their language. Student of the industry, Good governance. Yeah, don't be like break things move fast. And whether you like it or not, sometimes you have to actually kind of speak their language a little bit. And even if you are trying to break things and move fast.

Exactly.

And the biggest thing is that fast for a large company, whether it's government, financial services, media, et cetera, that could be a two year time span fast for a startup is maybe a day. So I think that you need to understand that if you're working in a big opportunity, it's going to take years.

As you mentioned before we play that clip. You said large enterprises are having budget allocated toward experimentation. Do they still shy away from startups providing that innovation or do you think that barrier is kind of gone and they're willing to adopt?

I think that barrier's gone. I think we're living in a totally different era. The world has been flipped on its head. So you went from a world where technology and startups was like a weird foreign thing to a world where it's the norm and everyone recognizes the sophistication of enterprises with their technology stack. Like JP diamond says this to JP Morgan, he's like, I have more engineers than like almost any tech company. So like inherently they're a tech company. I think if you look at it just most Fortune 500s right now, that if they stayed in the game and competed in their category, they're really sophisticated, they've deployed their own stack, they're probably experimenting a lot. I think people are even the government very open to trying things from startups. So I think we're in a different world where it's yet easier for anyone to try anything new. But what exists in the same world is that value point. So I talk about this in the world of go to market, which is relevance trumps personalization. So in the world of outreach or inbound messaging, a lot of people are going to be like, okay, I can get from a signal that you know you're Canadian. So I could send a note being like, I'm Canadian, you're Canadian, it's Canada. Should we hang out and show a coffee mug? And you might get a response. But that doesn't mean that the person's gonna wanna work with you because the relevance needs to be there. So I think what I said in 2015, which exists today, is that you need to show the relevance and the value in your product and you need to be explicit about that and also have a concrete reason for them to say yes now. So I think if you have the perfect product but you don't have a compelling event, it's not enough. So with Lambase, we help businesses leverage real time signals and data to understand the right time to reach out to someone. But also we focus our machine learning on the relevance. So what's the value? How are we saving you money? How are we saving you time? How are we delivering a better outcome? But what we found from looking at tens of millions of campaigns and analyzing it, this idea of like personalization or friendliness, it's irrelevant if you don't have the relevance and the real value prop. So what I said still stands from 10 years ago, which is you need to not offer a little Bit of value or marginal value improvement. It needs to be like way better and way bigger.

And speaking about things that may still stand the test of time, is the term break things move fast still relevant? In AI, things are definitely moving fast.

In AI, things are moving faster than harbor or. It's funny because if I look at the. This is like a very personal thing. But if you look at Mark Zuckerberg's personal arc, there was a phase where he was doing his move fast and break things. Then there was a phase where he was apologizing for everything. Then there was a phase where he was like pro very left social issues. And now he's gone totally 180 where it's like, we don't need any moderation. And I'm not going to apologize. I think that maybe somewhat represents the evolution of the, let's say, political zeitgeist in Silicon Valley or impacting tech, which is that these things go in waves. And I think ultimately as a business leader, you have to have strong conviction in your principles. So for me, I've always been the believer that business is about achieving a mission and it's not about espousing your social values or mission. So regardless if the politics have trended right or left, I've always focused on let's focus on the business, let's focus on the mission. And that's why we're all here. But I think there's different approaches. And yeah, if you fast forward to today, I would say that you could find someone who really believes in good governance and good security and good quality, and then you find others who are willing to cut corners. And I honestly don't think there's a right or wrong. I would have said this probably in 2015 or earlier, but when we started AppDirect, we looked at the companies and the leaders that we admired most. And we found that all these amazing companies, Walmart, Four Seasons, even the Trump Organization, whatever it was, they all define their values. And what we found is that, you know, I might like the value of humility, but another company could be really successful with ego. But just the sheer fact of defining your values or your principles and your mission, that's what led to success. So I think, look, there's many ways to run a company. There's many different philosophies. And as an employee, you have the choice to join a company that stands for what you stand for. And I feel that therefore it's more important than ever for companies to stand state what they stand for. So move fast and break things has never resonated with me. I think in the era today you definitely have to move fast. But I think you can also put good governance first, you can put quality control first. But I would say we're moving faster. It's just the cost of compute and the cost of building has gone down dramatically. So something that used to take years to build literally takes like months going on, maybe weeks going on, maybe minutes.

So over the last 30 minutes or so we've talked about how things have changed, but we also circle back to how things have stayed consistent and tried, tested and true. You're going to flip to our last clip and you're going to see how some of the things you may have not noticed this, but you've been hitting on all these points throughout the conversation here.

When you're servicing large enterprises concretely, like things that big companies need from you that maybe you as a startup don't need or you wouldn't have have thought about whether it's like a regulatory thing.

Or something like that Completely.

I think the biggest thing is governance. So when you work at a big company, you're gonna be working with hundreds of people and your startup might be only 10 people. So if you don't create a framework for how you communicate with those customers, it's gonna be almost impossible and they'll drown you. So you need to say here's how we'll work together.

Here's some methodologies.

Hey, we use Jira and Slack, so therefore you need to be aware of how we communicate. So a lot of it's in education and alignment and that also sometimes has to do with actually executive sponsorship. So making sure that you have relationships, senior level within these companies. So if something goes wrong, you can pick up the phone and say here's what we need. And really honesty and alignment on why things are different between working with a startup is so important. So I'd say that just that awareness is so much of it.

Okay.

Honesty, alignment, governance. You hit on all these things throughout our conversation here and it's refreshing to know that 10 years ago you were thinking the same way and that hasn't changed. I think governance, especially in the world of AI, is very critical and important. People's data is being used in different ways and honesty, integrity is something that's going to be looked upon 10 years later. Looking back, who were the honest and proper governance dictators of AI within their organizations and what your thoughts like, how is that governance translating to selling to SMBs with the use of AI, are they oblivious to it or you know, it's important, but they're too small to do anything about it. Like, how are SMBs sold on the governance side? Or.

I think it's all about trust. So whether it's an enterprise or whether it's an SMB, trust is more important than ever. And you create trust in a brand for your company, but personal brands are more important than ever. So trust in the individual. And what's been consistent with a business is you're always doing business with people. So I think what's going to be more important than ever is people are going to look under the hood and say, sure, here's the website or here's the technology, but I want to see the people that are building and ultimately the trust is going to come from that personal reputation. I'll put a crazy prediction out there, but I think in a year from now, a good chunk of business users are going to have more than 10 AI agents that are doing shit for them. And the when we talk about governance, I think that I face this the hard way, but I think that there's going to be the option to put AI on autopilot and there's risk of brand issues and hallucinations, but I think someone's going to have to be held accountable. Yeah, I think that within every AI native application, the application is going to natively run these agents that are going to do work for you. And a lot of control will be what type of authority do you delegate to these agents? And it could be like all the authority or it could be none. And what I found from a lot of our data is that the Copilot model doesn't make things 10x better. It actually you're just interacting with a chat and it's helping you brainstorm, but it's actually not harnessing machine intelligence. In order to harness machine intelligence, you need to allow the AI to tell you a recommendation and crunch all the data to come up with an answer. So my belief is that we're going to see much more of like an autopilot model. But the human can say yes, no, or edit, and the more that humans say yes to everything, the higher risk that their personal brand and therefore business brand is going to be degraded. And the stricter that they are on, you know, not adopting tools or saying no to everything, then they're just going to fall behind because they're not going to be using the most productive tools. So I think every business user is going to face this challenge at work within the next 18 to 24 months, maybe even Year, which is what level of authority do I give to my AI agents for different functions? The example of that I'll give tangibly is about six months ago, someone recommended this LinkedIn kind of tool that allows you to comment on users and things that you do. So I thought, oh, that's cool. Like, I always comment on stuff and it's going to go after my contacts and say nice things. But I configured it, I want a professional tone, et cetera. And over the, over the weekend I had it on. It sent 2,000 messages in languages that I didn't speak. Total hallucinations. In fact, I was terrified because one person actually did follow up and she was very kind about it, but I had called her a bro. I was like, yeah, nice, cool thing, bro. So anyway, like, that is not me, but I think ultimately people have to be held accountable for the authority they delegate to an employee, a human employee or an AI agent. So I think the key in this era is there's going to be a spectrum of if you don't use AI, you're going to be totally left behind, but if you use it on autopilot with no guardrails, you're going to have a lot of risk. So I think every business user is going to face this personal challenge of where do I sit on that spectrum for the different roles of authority that I'm going to delegate across different tasks or applications?

Yeah, I think that's a key point. You can defer responsibility. You ultimately have to be accountable for not only your own actions, but the actions of your workforce. And in today's day and age, that workforce is going to be AI enabled. Daniel, you said this back in January. You think agentic AI will have a breakout year. We're halfway through the year and I think you've been nailing it with all seven predictions.

Amazing. Really good to connect. Ray, I always love being a part of the traction community and cool to see this Next Wave series and it was fun to get the throwbacks as well.

Yeah, we always close it out with a call to action. Daniel, what can our audience do for you? What can our audience do for Landbase?

So ultimately we're here to help every business with their go to market and their go to market efficiency. So you can come to landbase.com learn more. We have a trust assessment. I talked about the importance of digital trust, but we use our machine learning algorithms to analyze your URL to give you a perspective of how a perceived or how a potential buyer will perceive your brand. And we give you ways to augment that and then we can also help you with go to market execution which would be running campaigns to ultimately generate leads. So would be happy to help the traction community. You can reach out on our website, you can reach out to me@DanielAndBase.com or on LinkedIn or my website at DanielleSax AI DanielleSax AI.

That's awesome. All right Daniel, this is awesome. Love having you back on the pod and we will look out to see more thought leadership coming from you and Landbase.

Amazing. Take care Ray thanks thank you for.

Tuning into this episode of the Next Wave podcast by Tracktion. If you enjoyed our show, please subscribe to our YouTube channel at YouTube.com artuptraction and give us a five star review on Apple Podcast and Spotify.

This episode is brought to you by Boast AI. Each year the US And Canadian governments give out billions of dollars in R and D tax credits and innovation incentives to fund businesses like yours. But the application process is cumbersome, prone to frustrating audits, and receiving the money can take up to 16 months. Boast AI gets you access to research and development tax credits and innovation funding opportunities without the headache and red tape. Join thousands of North American companies leveraging boast AI software to maximize cashback. Check out www.boast AI.

This episode is brought to you by Launch Academy. LaunchCademy is Western Canada's main tech hub with over 6,000 entrepreneurs being incubated from over 100 different countries. Our companies have raised over 2.5 billion in funding and they come from a variety of different backgrounds, from blockchain, AI, cybersecurity, quantum computing, agtech, fintech, healthtech, you name it. If you're interested in learning more, check us out at launchacademy Cat.