In this Founded & Funded episode, Madrona Managing Director Soma Somasegar sits down with Charles Lamanna, corporate vice president at Microsoft, to unpack his journey from startup founder to corporate leader. They dive into what it takes to build a successful AI-transformed organization, how the nature of business applications is evolving, and why AI agents will fundamentally reshape teams, tools, and workflows. This conversation offers a tactical AI adoption playbook—from “customer obsession” to “extreme ownership”—as Charles delivers insight after insight for startup founders and enterprise leaders navigating the age of AI.
They dive into:
- Why business apps as we know them are dead
- How AI agents and open standards like MCP and A2A are reshaping software
- The shift toward generalist teams powered by AI
- What startups are doing today that enterprises will follow in 3–5 years
- How to focus deeply on a few high-impact AI projects instead of chasing 100 pilots
Listen on Spotify, Apple, and Amazon | Watch on YouTube.
This transcript was automatically generated and edited for clarity.
Soma: Now, Charles, you came back to Microsoft when Microsoft decided to acquire your company, MetricsHub. How was that sort of entrepreneurial experience, and then transition back to a large company? Any learnings that you want to share that you think other founders or entrepreneurs might find interesting or valuable from your experience?
Charles: Absolutely. From my time on the outside of Microsoft, there were two big things that I learned and internalized in a profound way. The first is true customer obsession. That means even if you’re the engineer writing code, really understanding exactly how your customers use your product, what problems they’re trying to solve and what they’re looking to try to get out of it. That obsession has followed me since then, and I’ve really tried to bring back and inject deeply into Microsoft.
We do things like customer advisory board. We had one a couple of weeks ago with a few hundred customers came to town, and we have great quantitative analysis of how people use our products, where they get stuck, what our retention and funnel look like. Those are things that sometimes you forget or lose in a big company like Microsoft, because you have this amazing go-to-market arm, and you can make money even if maybe you aren’t delighting your customers. That has been a huge change. I think, of course, any startup is not going to be successful if they don’t really understand their customer and the pain points they’re going through.
The second thing is this idea of complete ownership, and when you have this sense of complete ownership, it doesn’t matter who’s responsible for doing something, if it’s necessary for the product or the business to be successful, you do it. And that is the biggest separation from a big company and a startup because in a startup, you don’t look around and say, “This is somebody else’s job.” It’s your job. If you’re a founder, everything is your job. Whether that’s responding to a customer support request, figuring out how to set up payroll, or doing financing. All of that is part of the job, and you never second-guess it. You never think for a second, “I need to hire someone to do this, or this is somebody else’s problem.”
That’s another thing, as you go into a big company like Microsoft, sometimes it’s easy because there’s such a robust support framework around you. You’ll say, “Oh no, I don’t do marketing, I don’t do finance, I don’t do this selling process.” Bringing back that extreme ownership has made it so much easier to create these successful businesses inside of Microsoft over the last 10 years. Things like Power Apps and Power Automate, they’re really expanding Dynamics 365. It’s that sense of total ownership.
Soma: I love those two things, customer obsession and complete ownership. Thanks. As I was just mentioning, Charles, we’ve heard Satya or Microsoft publicly say this on many occasions, like, “Hey, business applications as we have known them are dead.” We know that with AI, there is a tremendous amount of re-imagination of what business applications could mean or could look like that’s happening, including places at Microsoft. How do you think about this?
Charles: As the guy at Microsoft who works on business applications, sometimes the truth hurts, but business apps as we know it are indeed dead. I think that’s just the truth of it, and the analogy I always make is, it’s going to be like mainframes. I’m not saying tomorrow there will be $0 spent on CRM and ERP and HCM inside the enterprise. People will probably spend the same amount of money they did before, maybe a little bit less. They’re not going to do any innovation or any future-looking investment in that space because a system of record designed for humans to do data entry is not what transformation is going to look like in the world of AI agents and AI automation.
Instead, what will probably happen is you’ll see this ossification of these classic biz apps, the emergence of this new AI layer, which is very focused around automation and completing tasks in a way that extends the team of humans and people with these AI agents that go and do work. And if I kind of break it down, what’s in a biz app, I always have thought there are basically three things. It’s a basic form-driven UI gooey application on mobile and the web. It’s a list of things, and you can drill in and edit the individual things, whether it’s orders, or leads, or sales items. It’s a set of workflows that are statically defined, which codify how a lead goes to an opportunity, or how you close a purchase order. Very fragile, not dynamic.
Then it’s some relational database to store your data. That’s what a biz app was. Those aren’t the three elements of what a business application is going to look like in the future. Instead, it’s going to be closer to business agents. You’re going to have a generative UI, which AI dynamically authors and renders on the fly to exactly match what the person’s trying to do. You’re going to replace workflows with AI agents, which can take a goal and an outcome and find the best way to accomplish it, and you’re going to move from static relational databases to things like vector databases, and search indexes, and relevant systems, which are a whole new class of technology. When we fast-forward 10 years from now, you’ll look at those two things and it’ll be so clearly different, but right now they’re just beginning to separate. The gist of it is yes, indeed, biz apps, the age of biz apps is over.
Soma: When you mentioned forms of UI, in our workflow and database, you literally transported me back to my VB days.
Charles: Yes, yes.
Soma: Those were the things we were thinking about to help democratize application development. The fact that 20 years later we are still, at least today’s deployed application world is, tells me it is time for some disruption and some innovation.
Charles: Yes, exactly. I always joke, if you go and you look at a biz app that ran on a mainframe, it looks remarkably similar to a web-based biz app of today. That’s not going to be true in 10 years.
Soma: Whether it was the internet wave or the mobile platform wave, it always takes several years, many years, before you would find what I call canonical applications that define what the platform is capable of. In the AI world, I sometimes wonder whether that is still ahead of us as opposed to behind us. For all the hoopla and excitement that the world has seen around ChatGPT, that’s one sort of AI app that has gotten to what I call some critical mass in terms of adoption and usage.
Now in the startup world, there are a bunch of others like Perplexity, Glean, Cursor, Runway, Typeface, and a whole host of other companies that are getting to some level of critical mass. Some of these applications are targeted at consumers, some of them are targeted at enterprises, and some of them have aspirations to go both directions. What do you think is going to be the time when we can look and say, this is what a modern business application is going to look like, and throw away all the mental models you have about what that could be? Do you think it’s around the corner? Do you think it’s a few years away? What do you think?
Charles: I think we’ll see what the shape starts to look like very clearly in the next 6 to 18 months. I think because you already have glimmers of it, and then I think it’ll take longer to be mainstream. The refresh cycle of biz apps and core business processes takes a little bit longer, but in my mind, by 2030, this will be the prevalent pattern for business applications and business solutions. And in the next 6 to 18 months, you’ll really have it codified.
We can look to some of the places that have moved faster, like I’ll use Cursor as a great example. If you take Cursor, it’s a AI-powered application, tailored to provide an entirely AI-forward environment for a coder or developer. If you think about that, there’s the same type of work that happens for sales, or customer service, or core finance, like if it’s budget analysis, or reconciliation, or for core supply chain. You’re going to see things like Cursor or GitHub Copilot show up for each of those disciplines and be extremely tuned to take what people used to do and reimagine it with AI.
Just like how you have things like vibe coding, you’ll have vibe selling, vibe marketing, and vibe legal work. Those things will all show up. There are great companies out there. Harvey is a great company on the law side. There are a lot of companies that are emerging that are starting to do that. And of course, I’m biased. I think we have a lot of great stuff at Microsoft. We have very broad adoption of our Copilot offerings, but I think we’re going to see that fill out by industry, by business process, and by function.
The last thing I would say, which I think is probably one of the more interesting elements of all of this, is right now we’re taking the way organizations are structured and just mapping them to this AI world, right? Oh, you have a sales team, so they need AI for sales. You have a customer support team, you need AI for customer support. I don’t know if that will be what the world looks like at the end of the decade. You’ll have new disciplines, and new roles. Maybe you don’t have sales and customer support as two divisions. Maybe it’s one. Maybe sales, marketing, and customer support all become one role, and one person does all three. I think we’re going to reason through that, and that element is what will probably take the longest. We’ll probably have a wave of great technology for the old way of working that have new ways of working. Then another second wave of great technology, but all I know is it’s definitely going to be an exciting couple of years.
Soma: Your last point particularly made me think about this, Charles, instead of AI for sales, and AI for finance, and AI for this, and AI for that, do you think people are starting to think about, hey, what do people need to do in a company to get their job done, or to get their work done and start thinking about workflows that may or may not stay within a particular function or a particular discipline and cross discipline? Do you think there’s enough of that push that’s happening already, or is it coming in the future?
Charles: It’s very early. I mean, what’s amazing is that startups are doing this because startups, in a world where you have extreme ownership and you have to do whatever it takes to succeed, you don’t feel constrained by disciplines and boundaries. If you want to see where the enterprise world or where mid-size companies are going to go in three to five years, look at what startups are doing right now and that’s exactly what they’re doing. Different structures, different ways of working, and there are two things which I think are going to really drive a lot of this transformation.
The first is, these AI tools bring experts to your fingertips. As a result, you can be a generalist with a team of expert AI supporting you. That’s how I feel every day. I have an agent that helps me with sales research. I’m not a salesperson, I’m an engineer, but I don’t have to go out and talk to a salesperson to get ready for a customer meeting. I have a researcher agent, which helps me prepare and reason over hard challenges. I have a document editing and proofreading agent, which makes me a better writer. I have all these tools, which make me more of a generalist, kind of overseeing these set of AIs. What that translates to is probably de-specialization in the enterprise, de-specialization in companies where you have less distinct roles and disciplines, more generalists powered by AI. That’s item one.
The second thing is, what makes a team? We always think a team is a group of people. The big change is that the team is a group of people and AI agents. That’s really how we need to start thinking about how we organize organizations and companies, and how we even go out and do hiring. If you think about who you work with, you’ll start to, increasingly I think of it as — here are the people I work with, and here are the AI agents I work with to get a job done. That means you have meetings, you have calls, you have documents you work on together. Those two things will help drive that transformation. It’s not like a startup sits down and says, “How should we structure ourselves for the future?” They tackle this problem, that problem, that problem in the best and most efficient way, and it happens to look like that. So that is, I think, probably a lot of the changes that we’ll start to see.
Soma: You talked about this notion of, a team as not just a bunch of people, but a bunch of people plus a bunch of AI agents. Can you take it one step further and say, hey, every information worker or knowledge worker is really a human being plus a bunch of AI agents at their disposal? Is that a good way to think about it?
Charles: Absolutely. The way we approach it is every individual contributor, everybody who individually does work, will increasingly become a manager of AI agents who do the work. We have a thing we talk about internally at Microsoft, which is in the past we built software for knowledge workers to do knowledge work. In the future, probably most knowledge work and most information work will be done by AI agents. And a knowledge worker’s main responsibility will be the management and upkeep.
Soma: To orchestrate and manage.
Charles: Exactly. That’s where you get this idea that you can be much more of a generalist and an expert, and this is how you get a huge productivity gain. You’re not talking about, oh, I’m 10% more productive or 15% more productive. We all are going to have entire teams of AI agents working for us. We can be 5 or 10 times more productive if you get that right, and that’s what gets me excited because that’s what starts to change the shape of the economy and really create abundance of doctors, lawyers, software, and all of those things.
Soma: People fondly refer to 2025 as the year of agentic AI. First of all, do you agree with that? How do you see the role of agentic AI or AI agents as far as the next generation of business applications go?
Charles: It definitely is the year of agents. Everyone I talk to, from the smallest to biggest company, understands what agents are and they want to get started with deploying agents in their enterprise. You can see, you have Google with Agentspace, you have Salesforce with Agentforce. We have plenty of agents at Microsoft in and around Copilot. OpenAI is talking about agents, Cursor is talking about agents, everybody’s talking about agents.
It very much is beginning to diffuse — kind of like how 2023 was probably the main year of chat AI experiences on the back of ChatGPT and Copilot’s launch, that’s what 2025 will be, but for agents. Business applications, in particular, are going to be the ones most changed as a result, and I think you’re starting to see it. Every company I work with tells me, “I’m excited by business applications with AI, that’s great, but I really care about business agents. Tell me how I can get agents deployed in my back office, in my front office? How can I grow revenue, cut costs, using agents?” That is a new conversation, which to me means it’s the era of agents.
Soma: We’ve gone through a major platform shift almost every decade or so, and sometimes during this platform shift, every major player would go off in their own direction, trying to figure out what it means for them and what they can do with that kind of thing. If you go back to the internet platform way, you could argue that HTTP was something that sort of came in pretty early on, and everybody adopted and said, “We are going to be behind this kind of thing.”
Similarly today, when I think about this agentic world, I look at a protocol like MCP, or a protocol like A2A, and see a tremendous amount of industry consolidating. In fact, the thing that surprised me is that Anthropic, in MCP’s case, came out with MCP, and within a few months, pretty much anybody that mattered talked about how they’re all in on supporting MCP and came out with their own offerings. That level of industry consolidation around something is both exciting and fantastic. How do you see that?
Charles: It’s probably 30 years since we’ve had such an industry-wide convergence on an open standard, back to really the original open web HTML, HTTP, and JavaScript. It’s incredible because that means more opportunity for startups because there’s really not some strong incumbency advantage, as a result of open standards. Also for customers. I can buy 10 solutions, 10 different AI agents, and I have confidence that they’ll work together. Even at Microsoft, we support A2A. We’ve announced that a couple of weeks ago. We have MCP support for a couple months, and we’ve even contributed back changes to MCP that have been accepted and merged with a bunch of other companies for authentication to make that work well with MCP.
This is going to be great because a typical company has so many, say, SaaS applications and databases today. In the future, they’re going to have a ton of these different agents and tools for agents. That’s what the future is going to look like. If you think about what it’s like to be in an IT department that has 300 different SaaS apps, it’s so painful to integrate them. I don’t think it’ll be as painful in this world of MCP and A2A and that’s huge opportunity for lots of these startups, which can be so fast and agile using these AI tools and can interoperate with the big footprints that exist in a typical user’s day, whether it’s consumer or commercial.
Soma: I want to go back to one of the earlier things you talked about, which is customer obsession. You mentioned that you had a customer advisory board, and a couple of hundred customers come through. When you talk to enterprise customers, where do you think they are in the journey of adopting AI, whether it’s in the form of business applications, next-generation business applications, or Copilots, or what have you? Do you think they’re in the early stages, mid-stages, or later stages, and what are you hearing from them?
Charles: It’s a big spread out there right now. Some companies are almost like a tech company in terms of how aggressive and ambitious they are with the AI transformation, usually that comes from a very top-down investment focus from the CEO, the board, plus having business and IT and tech resources equally engaged. A lot of companies are very early, and they’re looking for that first big win. Maybe they have a few POCs, a few prototypes, a few experiments. They don’t have that big top line or bottom line moving win.
What’s interesting is that if you went back a couple of years ago, it was all about building things yourselves. Everybody had dev teams calling APIs and using models. We’re coming out of that because people realize how hard it is to assemble these things and get business outcomes. It’s the era of these AI finished solutions, whether that’s in an agent or this new type of AI application like Cursor. That is starting to be the main place that companies are looking to get that value quickly. If I were to take a step back and maybe do a pattern match of what are we seeing for companies that are being most successful, enterprises that are being most successful, the three main things when it comes to the AI transformation.
First, they’re being very focused on driving real resource constraints into the organization to drive productivity improvement. If your budget grows every year, you don’t feel a lot of pressure to improve your unit performance inside the organization. That’s a hard thing to do, particularly if a company is growing. The second thing is having a big focus on democratizing access to AI. Companies which are struggling are the companies that don’t have AI in everybody’s hands every day.
If you want to become an AI-transformed company, the only way to do it is all of your users, no matter where they are, technical, non-technical, need to be picking up and using these tools each and every day. If you don’t have that, people will have dreams of the magic AI can do, which isn’t grounded in reality, or they’ll be unnecessary skeptics for future projects. Get AI in the hands of everybody. The third and last bit is don’t spread yourself a mile wide and inch deep. For companies that are successful, they don’t do 100 projects, they do 5 projects very well with a lot of force and with continuous improvement in mind. That’s kind of what I see as showing up as the most successful enterprise organizations.
Soma: That’s great. Did you hear the Shopify CEO make a prompt from a few weeks ago about how everybody should be thinking about AI?
Charles: Yes.
Soma: That dovetails with what you’re saying about, hey, make sure that everybody has access to AI tools?
Charles: Exactly. I go out and tell my team, “This year, you won’t be promoted unless you use AI tools if you’re an engineer, because how can you really say that you’re on the cutting edge of AI software development if you yourself are not using AI?”
Soma: That’s great. Charles, earlier on, you talked about customer obsession and complete ownership. Some of the learnings that you had from being a startup founder to coming back to Microsoft. Going hand in hand with that, how do you think about agility? One of the things I worry about, and I was part of Microsoft, so I can sort of say that I’ve been there, but as the company gets larger, sometimes you sort of wonder whether the agility is what it needs to be, the level of urgency is what it should be. How do you encourage your teams and Microsoft to say, hey, I want to operate with the same level of urgency and agility that a startup does?
Charles: There’s three big things that we’ve done to help instill that. The first is, for the most intense period since I’ve been back at Microsoft, it’s mission-oriented. Everybody understands what the mission is. All of our software, all of our technology, all of our products is going to be completely disrupted by AI. Do we want to be the people who watch that happen, or do we want to be the people who do it to ourselves? The energy is off the charts. I’ve not seen folks at Microsoft working as hard and pushing the limits and boundaries and innovating in the last 10 years I’ve been there, as there has been over the last couple of years. That’s kind of item number one.
Number two is when you’re in a big company, there’s always this incredible inertia and this incredible layers of bureaucracy, and process, and layers of decision makers, and consensus building that slows everything down. That’s where extreme ownership and this desire to grind through anything is really critical because anything you want to do, if you want to innovate, there’ll be 100 reasons why you cannot do it. You have to find the one reason why you can and how you can, so that extreme ownership grit to really push through all these barriers to go be successful.
And the third piece is really encouraging experimentation and being willing and rewarding failure if it produces learnings. We have these interesting forums at Microsoft where folks will come in and say, “Here is a product experiment we’ve done, or here’s an AI model experiment we’ve done.” We have these every week and they share good or bad. Here’s what we tried. It didn’t work for these reasons. Here’s what we tried. It did work for these reasons. It’s almost like the cloud post-mortem culture that you had to develop with repair items and a blameless post-mortem.
It’s this continuous experimentation, innovation feedback loop around model and AI products, and doing both of those because those are both equally important, is how we’re really starting to drive this culture of, it’s not build a plan for six months and we’re going to run the plan no matter what. It’s build an experiment, run it in a day, learn, run it another day, learn, because that’s what all the good AI companies are doing. Those are just a few of the things. If you look at the pace of innovation, Microsoft is definitely moving faster than we’ve ever moved before.
Soma: That’s a super helpful framework to think about, as teams and organizations are thinking about how do they operate with the same level of urgency or agility that is required in today’s age. It’s not a nice to have or hey, yeah, someday I’ll do it. If you want to survive and if you want to be ahead of the curve, you need to do it today. Now, coming to the personal side a little bit, Charles, I’m sure AI is impacting your life in a positive way, whether it’s at work or outside work. Are there one or two tools that you use on a daily basis, and can you talk a little bit about what those tools are and how they change what you’re doing?
Charles: I will exclude all my Microsoft tools that I use all the time, in the interest of being different a little bit, because I use a bunch of those, and one of my favorite features that have been released lately is the deep research functionality. Between o3 and Deep Research, you can get some amazing insights. A big thing I like to try to do is really have a good view of the market to try to find blind spots. What startups are out there being successful, and how are the big competitors doing when they do their earnings, announcements, or conferences?
What I can do with Deep Research is I can basically have a very specific question, and I run this basically every week. I’ll give an example, help me understand the financial performance of business application companies, and who is accelerating versus decelerating, and what are some interesting facts and terms around usage that they’ve announced. I can basically describe this nice little big healthy prompt, send that off, come back 10 minutes later, and I get a beautiful little view. This is a way that I stay on top of what’s happening in the market every week. In the past, I could do this by reading various places, Hacker News, and on X, and stuff like that. But this gives me a really in-depth view report, almost as if I truly had a competitive researcher full-time doing work for me.
That has been game-changing and my poor team is probably tired of me sending screenshots to these reports because I use that for a lot of public information. Second thing is, I’m a big user for image generation tools. I have subscribed to Midjourney. That’s just so much fun because I never was a great artist, but I’d say I can create lots of fun images and pictures and I share them with family and friends. That’s kind of like a relaxing thing for me to do. And I don’t have Photoshop. I would never have opened up and drawn free form, but I can have that feeling of creation and creativity in a way I wouldn’t have before. It’s interesting. It’s a new kind of hobby, a new accessibility. Again, back to the generalist specialist thing, I’m definitely not a specialist artist, but I can use AI.
Soma: It’s a good outlet for your creativity.
Charles: Exactly, exactly.
Soma: That’s fantastic.
Charles: I cannot wait for companies like Runway, as they mature capabilities to be more than just images to videos. I can’t make a film or a movie today, but I bet in the next 10 years I’ll be able to make a 60-minute film, like really. So that’ll be fun.
Soma: That is great. On that note, Charles, thank you so much for taking the time to be here with us today. I really enjoyed the conversation, and we took it in multiple directions, and it was fun to be able to hear your views, your perspectives, and your experiences. Thank you so much.
Charles: Thank you for having me.