The Impacts of Agentic AI for SaaS Businesses & Users with Bill Hewitt

The real true productivity is when it replaces work. And a great and probably the most mature area today is in coding. So today in our shop, over 70% of the code that we write is being written by Claude, supervised by engineers. But the majority of our engineers no longer write code. And it's more efficient. We can be more dynamic, we can change things much faster. We can move software to production much faster because it not only writes the code, it writes all the qa, it writes all the tests, writes all the scripts, and it promotes it to production and monitors the code. And it has a full history of everything that's ever happened. This is SaaS scaled, the podcast where data meets action with host Arman Shrakhi. Each week Armen will be sitting down with CEOs and industry leaders from the technology sector, giving you the insight to innovate without reinventing the wheel. They'll discuss challenges, best practices and how to identify the right metrics. So if you want to get to market faster and in a way that matters, then subscribe and join us every week as we discuss SaaS scale. This episode is brought to you by Curve, the modern no code analytics solution. The tools you need to take action with your data on a platform built for maximum scalability, security and cost efficiencies. If you're ready to reduce complexity and dramatically lower costs, then contact us today@crave.com that's Q R-V-E-Y.com. Hello, welcome to another episode of Sense Scaled and I'm here with Bill. Great discussion. We are going to have probably slightly different than the previous discussions. Bill is extremely experienced with managing companies funded by private equities and decades of managing software. And now we are in the AI age. That is very insightful about it and we will have great discussions. Stay with us for the discussion. Bill, welcome to podcast and please tell us a little bit about yourself and about the company that now you are working with. Armin, thanks very much for having me. It's a pleasure to be on the podcast with you. So as you said, my name is Bill Hewitt. I'm currently the CEO of Link Squares, which is a fully agentic contract lifecycle management system. I've been in the software industry now for 30 years and have worked for companies like Hyperion. PeopleSoft ran a contract lifecycle management company called Auxari that we sold to Koopa Software and have always just enjoyed what software can do for business because it really is about how you apply it and solving customer problems has always been something very central to sort of my ethos and what I want to do in business. So that's sort of who I am. Link Squares is we have about 1,200 customers today. We're one of the leaders in contract life cycle management, providing not only the data repository for contracts, but also all the pre signature elements and workflow that are necessary for contracts to move throughout the enterprise. And when you think about it, every enterprise runs on contracts. Every employee, every supplier, every customer is governed by some type of contract. So it really is the nervous system and it's an area where we take a lot of pride in making sure that companies can get the most out of the information that's in their contracts. And now the topic that it's near and dear to your heart and you have been involved with agentic AI every day now. I would like to have your insight about really how do you feel about really agentic AI changing software world and moving forward and some impacts that you already have observed and is in place and something that you feel like is coming soon. Yeah, at least in my career it's one of the most exciting technology developments. And when I look back over my 30 years, I've seen lots of technologies that have had a lot of promise, but have never always quite fulfilled the promise. And I think AI has the chance to deliver something that is probably even better than what we see today, primarily because it changes the way systems work. And up until now, software and systems have always had a human element. There's always had to be a human in the loop to make it work the way that it needs to work. And AI in many cases now removes that need. So what we're excited about is we now have the ability to build agents within our system that can do things for the customer. But customers can build their own agents based on their own business requirements. So it dramatically changes the experience for the customer, it dramatically changes the way we develop software and ultimately allows the customer gain more control over the value they receive from whatever platform they're using. So many companies feel like AI definitely is adding value and it's really something very complementary to what they do. But they still do not believe that AI is at the point, or agentic AI is at the point that can replace what they were doing traditionally. What it means to them is that they wanted to keep whatever they are doing and then leveraging AI capabilities as a complementary kind of thing to it, and then it just adds productivity. Maybe it helps them a little bit to move faster, maybe helps their users, but that's the stage that they think they are in is it something you would agree with or you think it's coming sooner than what most people think. And agentic AI is not far from really being the only thing you need. And you really don't need the traditional software the way you used to. Yeah, it's a great point. I think for most people, their use of AI is very, is mostly generative AI today. So for example, I gave a keynote speech last week. I needed to fill in the blanks on a number of Topics. I used ChatGPT to go fill in the blanks for me. It dramatically cut down the time it took me to build my speech. So it made me personally more productive. The second step is really the process productivity. So how do I make a business process more productive? So a good example would be using prompts and LLMs in a customer support environment where the customer can come in, ask a series of questions, get answers to their questions without a human being involved. And that's more efficient for both the customer and for the company. The real true productivity is when it replaces work. And a great and probably the most mature area today is in coding. So today in our shop, over 70% of the code that we write is being written by Claude, supervised by engineers. But the majority of our engineers no longer write code. And it's more efficient. We can be more dynamic, we can change things much faster. We can move software to production much faster because it not only writes the code, it writes all the qa, it writes all the tests, writes all the scripts, and it promotes it to production and monitors the code. And it has a, has a full history of everything that's ever happened. So when that level of systems, level AI impact begins to hit other parts of companies, they're going to see a dramatic change in productivity where the work is being done by the system, not by humans who are just becoming more efficient based on the system. Now you mentioned that 70% of the code is being now developed by AI. But also people are involved, of course, to review the code, to manage it, to supervise it, but. And that will impact also the other parts, not just coding, but related to coding like QA will change as a result of that. Product management will change. Documentation will have a different meaning, technical documentation of the product. Now that AI may be relying on it more than before, at least to do a QA and maybe doing softer product management helps. How do you see it that from software perspective, software company's perspective, a SaaS company or software company perspective, do you see it more like that will decrease the number of people that they need to hire. Existing software companies may need less resources or in action. Really, it's just the change of using the resources, not really lowering the number of resources. And it's getting more productivity out of it rather than the company that had 200 people now is going to have 100 people. Yeah, I think it's a little bit of both. But if I look at it from what we do in a CLM perspective, think about somebody who needs to go create a contract. Let's say it's an NDA between them and a customer. And today they go to a file, they look at previous NDAs or they type in to a prompt what kind of NDA they're looking for. Their job is going to change because now they're looking through a file structure and tabs and previous works and they have to determine on their own what the best form might be in an AI centric world. They have a conversation with the system and through that conversation the system is going to give them the answer versus give them options. And so they become more of a manager of the system, like they would manage people, but it makes the entire department more efficient. So for example, in our business, in the software business, we have sales development representatives who now become more pipeline supervisors to make sure that the system is doing the work that we want, that it's generating the leads that we want for the companies that we think we can provide value for. So it changes the work that they do. I think for some companies that are still using people for more manual tasks, you'll see some efficiencies there as well. I think it primarily changes the job that you have today and you are very well versed and experienced working with investors in different companies that you have worked with. Do you think there is an expectation on the investor side that when you are leveraging AI, then you need to show more, maybe efficiency or capital efficiency now that AI is in place, or the understanding is still very new and it may take time to really establish that in order to get to that place. Yeah, I mean, there is a learning curve, there's no doubt about that. But what I do know is what investors really want is growth. And this removes a lot of barriers to growth, not only for the vendor, but for the customer as well. Because they can do more research faster. They can understand the difference between 10 different vendors versus going through an arduous RFP process. They can let the system do that evaluation for them based on the information that's out there. So there's, there's real compression of time. That compression of time is a direct input to the efficiency metric which can help drive growth. Which is why I say I think AI is going to be the next great economic accelerator for the global economy. Yeah, no, I'm with you. You mentioned the evaluation takes less time. I have been using that very actively and I see that the impact. Because your research can result, you know, much faster. It's very comprehensive result you get. And you know, just a few years ago you had to do it, it was impossible to just do it within 30 minutes. You had to spend days to collect all of this information that now you can just leveraging different LLMs. And it's also very interesting to see different LLMs really look at it analytically differently. Right. So there's some of the information that you may get better from one model versus the other models. So that that's really interesting as well. So in this particular age now we are in kind of AI age. We are, you know, building software using AI probably faster as we learn, if not today still maybe we are at the very earliest stage and we need to still establish the foundation, but it's coming, right? So we know that every three months, every six months is going to get better, faster, cheaper. Now we get to the point, not so far from where we are at one point, we get to the point that building software, building software applications, products is getting much faster, much cheaper. Do you think building software businesses is going to get also at the same rate, cheaper and faster or do you think still building a software business is totally different ballgame and it may even get more difficult, not easier? No, I think it does get easier. And I think we've seen people already embrace the technology to not only make the software development process easier, but the marketing of the software, the selling of the software, the support of the software, and if you take an agent first or an AI centric first approach, then that's how you're going to think about building your company. What that results in is dramatically faster growth. You still have to provide value for whoever your customers are. And you'll see a lot of these business grows very, grow very quickly and then they'll be disintermediated by somebody else. But for a lot of them, if they can sustain value and continue to add capabilities to their product, they'll be able to continue that trajectory for some unlimited amount of time. If I'm a founder, a SaaS founder, that I'm kind of starting the company, I'm not at this stage of maybe more established companies that you have Worked with, but they are going to start today and it takes some time to get to the point of maturity of the business and the product. Do you have any advice for them that what they should do or should not do in order to really make sure that they stay relevant and their business can grow to the point they want in the future? Yeah, that's a great question. I think you're going to see a dramatic rise in the value of product management, which I think a lot of people don't fully understand. But if you are not talking to your customers on a regular basis about what your product's doing now, you have the ability to change your product in moments, just not days, not weeks, not months, not years. Waterfall is dead. Even Agile is dead. This is like demo to production. And if you don't understand the difference between what customers want and what customers need, then I think you'll continue to struggle. But I also think you have to come to grips with the fact that not everything you develop is going to be beautiful and that the customer is going to decide what beauty looks like and that you have to be self aware enough to realize that, hey, the customer's usually always right. So that's a big part of it. But honing those like product management's always been tough because you've got to make tough calls. The calls are easier now, but you've got to be better at discerning what's a real requirement versus just something that's nice to have. Yeah, thank you. That was essentially what you said is, you know, if you have a very. The product management role is going to be even magnified in the age of AI. Absolutely. Because then you can do more, you can do better, you can do faster. If you have a great product management in place, then that magnification, that multiple, that multiple will be much larger. And if you are limited by your product management, then the result may be less. And that's a great point. Now I'm going to ask you a random question before we get back to the second phase of some questions. Out of the cities that you have traveled to, which city would be a city that you would say Arman, if you wanted to spend two weeks, you better go to this city. I loved it. I had a great experience there and probably I would recommend you travel there too. That's a great question. If I were to pick a city that I was able to spend some time in, but I want to spend more in, I would say it's probably Mexico City. City. Such a diverse cultural environment, food environment, the arts. There's so much you can do and I just think it's, you know, it's such a metropolis that people usually don't think about, but really is a major city. I definitely want to spend more time there. Fantastic. No, thanks for sharing it with us. When was the time that you were there and you enjoyed it? Is there a particular time you would suggest for people to go? It was about 10 years ago, but it was, it was just for business. So I mean, it was during the summertime or winter time? What time of the year? Yeah, it was during the summertime. It was I think July, August time frame. Yeah. Yeah, okay. Fantastic. No, that's great suggestion has always been my miss to go there. I have some American friends as well as some Mexican friends have told me a lot about Mexico City and never made it there. But definitely a great city, especially where I am in Austin, Texas. We are easier for me to get to for you, maybe from Boston is a little bit farther, but on my side there's less excuse not to get there. Now back to the AI questions that we have. And based on the software that you are writing and managing contracts with AI agents and everything, how do you see that, for example, this agentic AI, the way that you even can enable your customers to develop their own agents and work with your software, how do you see that in the future your users may not be just humans, there might be more actually digital workers using your software. And how do you see the impact of that in your software? The way you design software, the way you perform, the way you manage, maybe even pricing, licensing. What would be the impact of that kind of change? Yeah, it's a great question. You know, we, we think about CLM in the agentic world as providing every user with their own dynamic experience. And that dynamic experience is different every time they use the product. So today they may use it to generate an NDA. Tomorrow they may use it to generate a multi interdepartmental workflow that, you know, for one of their biggest customers or one of their most difficult contract types, it changes every single day. The experience has to be the same. It has to be easy to use, it has to be easy to converse with. So the system underneath has to be very, very smart about interpreting what the user's asking for and get smarter with every interaction. So I think what'll happen over time is as users become more familiar with the system, more capabilities emerge. Their use of it will drive their productivity and efficiency. They'll start to build their own agentic technology to do the things that are repetitive for them. So it might be generating a certain type of report or doing contract renewals. Things like contract renewals is a great example of where the system could be doing the work for you. Let's say a contract comes up for renewal, it automatically goes into an agent cycle. It sends an invoice and a renewal letter to the customer, it collects the funds, it renews the contract and the CRM system and then it's done its job. So that typically would be done by a renewal specialist today. And so that something like that could be fully automated within the system. But I think it'll happen more and more as they learn the system and they learn how to use the system within their particular environment. And to me that's the most exciting thing because you're no longer hard coding applications that only do things one way. You're doing it the way every single individual customer wants. And many SaaS companies nowadays, they charge per user and that's the way they scale their software. As the company that is using their software is getting bigger and growing. So it also helps them to really grow with the customer. And if the customer is using agentic kind of AI capability and the agent is working 247 and working faster and get the job done, how do you see that can be kind of, you know, that change can be impacted, can impact the licensing, pricing. And how should software companies, SaaS companies look at it and say, okay, this is the better model for us, rather than just perceive. Yeah, I mean, I think the logic applies pretty simply here. If you're going to have a human doing the work and that work is going to be replaced by an agent doing the work, you're probably going to pay the agent the same way you pay a human. So if you need one human, you pay a certain amount. If you need five humans, you pay a certain amount. You should pay dramatically less for an agent to do the work, but you'll still pay based on consumption. And so the way we think about it in the contract world, there are people that need to do fairly straightforward things. Create a contract, redline a contract, look up a contract term. Those are things that they can do within the system. It doesn't cost anything more. That's access to the information that they already own. When it comes to the system doing work on their behalf, and that's using more sophisticated agents, more sophisticated models, then that will most likely be consumption based. And typically what you would expect is some level of consumption to be included in the contract, but capped at a certain level and anything over that is paid for separately by the company. Now you mentioned also another good point about really the marketing and when you go to AI and ask for advice, I wanted to evaluate different products, they will be able to dig into a lot of data sources very quickly, come back and say the best probably option for you would be this one. And they can get all of those information from reviews that they review from products from capabilities from the website. I mean, they can dig into all of those sources in a matter of seconds and really provide you a very comprehensive. But at the same time, I feel like sometimes not on the B2B kind of side, on my personal experience side, when I go to AI and ask, can you give me the best advice for I don't know which TV I should buy, for example. And at that point the AI knows me a little bit and says, Armen, I know you based on the characteristics that I know from you then probably should. The best bet is these three options or this option will be the best bet for you to go with. And that can be very convenient, but at the same time it can be a little bit dangerous because then in that case, believe or not, that is a kind of bias. Right? So. And what kind of information you can provide to the AI agent to really buy that recommendation, because that's a powerful tool to have. Just imagine if anyone in the world go to that software and that AI agent and just ask the same question, what kind of this type of software I should purchase. And the AI engine come back and say for you, this is the best option that can be a fantastic organic, at no cost marketing lead generator and dimension. How do you feel that with that power in the hand of AI now sending your leads and customers toward you or not sending them, is it something that probably, you know, makes you very concerned as the CEO and leader of a software company and the kind of recommendation you can get. And how do you feel about that? Yeah, it's a fantastic point. If you think about, you know, go back, go back 50 years, no computers or no readily available computers. You know, how would you, how would you find out? Well, you'd, you'd get on your phone that has a cord on it, you'd call Mrs. Jones next door and you'd ask her if she bought something like that, or you saw that she has a new car, how does she like it? Or you go downtown or you'd see somebody else. Like that's how you would. And you would talk to a small number of people or you might go to the store and the salesperson would tell you all about the product and that would be your primary source of information. So you're still going to a community. It's just that your community is completely digital now and AI driven. So as a, as a vendor providing value based solutions, we have to make sure that our customers are getting the most out of our products in order for them to be in the market. Talking about how they like them, where they think there are challenges, why they recommend us. And we have to be putting out content as well to educate people about what the product can do for them, what kind of problems it can solve, the value it can create. So building that community is an incredibly important part of what we do and then making sure that that content is getting into these LLMs. So when people go and search for this information, they're seeing not only what we provide, but what our customers in the market provide about why we're the better fit. So it's fair to say marketing will be more about educating the market than about advertising. Because of AI, that movement will be faster now that all the marketing teams need to get better and better at educating rather than just advertising. I think it's two things. One is for a long time now, users have had the ability to go search and do research on available solutions, whether it's Google or another search engine. And I think gartner said that 74% of enterprise buyers do their research before they even contact a vendor. So they're forming an opinion anyway. Now they can form it, not only form it fast, but to your earlier point, they're not doing the work to sort through what the different features are, what the different. Is this good for a big company? Is it good for a small company? All that work is, is being done for them. But as a, you know, from a marketing standpoint, I not only want to make sure that I can feed that engine to make sure that we're fairly represented, but then I'm looking for, I'm listening for intent, I'm looking at activity, what people, you know, we can track what people are doing on their websites, what they're looking at, different pages, not only in our site, but competitor sites as well. So we know when there's a, a dramatic increase in productivity, that's an intense signal. That's a, you know, we could have an AI robot reach out. We could, you know, propose a demo or a webinar or one of those things. So it is becoming a little bit scary because, you know, as we, we all know, like we'll be Walk. You'll be walking around the house talking to your partner about something and all of a sudden you'll get an ad for it on TV and it gets a little, you know, it's like if you ever want to test that, just walk around your house saying say the word diaper 100 times and see how many diaper ads you get on your TV in the next two days. So it's similar to that. There is more sense and respond and listening going on in the market than ever before. But as a company, we need to get the people seeing the value in our product, talking about it, being part of that community. And that's a community that we've always been very in touch with and very proud of the value that they've gotten from Link squares. Great point, Bill. I would like to ask you, as my last question, to recommend a book either personally or professionally. You liked it and it was impactful. I'll tell you what a book I just read written by a friend of mine, his name is Peter Bailey and the book is called My Epic Journey. And it's about the story of his life basically. But Peter is one of the leading executive coaches, corporate coaches, on how to get the most out of your own personal well being as well as your professional well being. But it's a fascinating story because I grew up with Peter and I learned a lot of things about Peter that I didn't know anything about professionally. Probably my favorite business book is a book called the Goal. It was written by a gentleman by the name of Ellie Goldratt and it's really written as a novel, but it's written about a manufacturing theory called the theory of constraints. And for years manufacturing has been focused on planning. And Ellie's theory was basically, look, you're not focused on the constraints, the bottlenecks in the system. That's really what your issues are. And the reason I like it, it's not because I'm a big manufacturing guy, but because you can apply the theory of constraints to virtually anything you do. And if you're running a company, you're always dealing with constraints. Constraints can help you make better decisions. But if you're not balanced as a company, you know, you're not going to get the kind of output that you want. So for me it's a critical part of decision making, critical part of problem solving, which if you're in management is what you do most of the time. Thank you very much for sharing it and also thank you very much for joining us today. And it was great having you and this was a very informative discussion, so I appreciate sharing your thoughts with us. Arman, thank you for having me. Thank you for listening to SAS Scaled with Arman Eshragi. For show notes and any resources mentioned in today's episode, go to sasgaled.com if you're enjoying our show, give it a us a five star review and share on LinkedIn and be sure to subscribe for any updates on future episodes. Thanks for listening. This episode is brought to you by Curve A the modern no Code analytics solution. The tools you need to take action with your data on a platform built for maximum scalability, security and cost efficiencies. If you're ready to reduce complexity and dramatic lower costs, then contact us today@crave.com. that's Q R V E Y dot com.