Pricing in the AI Era: From Inputs to Outcomes, with Paid CEO Manny Medina

Former Outreach CEO Manny Medina discusses his new company Paid, which provides billing, pricing and margin management tools for AI companies. He explains why traditional SaaS pricing models don’t work for AI businesses, and breaks down emerging approaches like outcome-based and agent-based pricing. Manny shares why he believes focused AI applications targeting specific workflows will win over broad platforms, while emphasizing that AI companies need better tools to understand their unit economics and capture more value. Hosted by Pat Grady and Lauren Reeder, Sequoia Capital Mentioned in this episode: CPQ: Configure, Price, Quote Invent and Wander: Book by Jeff Bezos and Walter Isaacson Foundations of Statistical Natural Language Processing: 1999 book by Chris Manning and Hinrich Schütze that Manny cites as a piece of AI content every AI founder should read. (still in print, companion site here) The fox and the hedgehog: Quandri XBOW HappyRobot Owl Crosby

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Your customer will always default to the easiest way to buy, which is either some kind of fixed price or a consumption price for the first year to see if it works. But if it does work, it is up to the AI agent builder and creator to go back to the same customer and say, let's align on things that are important to you and charge for it.

• 0:33Pat Grady?

  Greetings. Today, we're joined by Manny Medina, founder of Paid. Paid helps agentic AI companies make money by dialing in their pricing and costs. Manny experienced the problem he's now solving with his previous venture outreach, where he first encountered the challenges of pricing and margin management, challenges that are becoming top of mind as agentic companies move from experimentation into production. Paid provides the infrastructure that helps AI companies transition from simple activity-based pricing to more sophisticated value-based approaches, allowing them to capture their fair share of the value they create for their customers. In this episode, we'll explore Manny's contrarian views on AI pricing models,

• 1:18Pat Grady?

  his framework for the four pricing approaches that are working today, why he believes specialized AI agents targeting narrow problems are printing money, and what it takes to build a successful business in the age of AI agents. We hope you enjoy.

• 1:35Pat Grady?

  All right, we're here in London for a very special episode of Training Data with Paid founder Manny Medina. Manny, welcome to the show. Thank you for having me. This is awesome. All right, we're going to start off with a high-level question. Okay. In the world of AI apps, Yep. these are your customers. So I think you have a pretty good sense of what's working and what's not working. Yep. What's working? So.

• 1:55Speaker 00

  I think that we are right now in, if you were to take the analogy of hedgehog versus fox, we're in hedgehog land.

• 2:03Pat Grady?

  I love, I love where this analogy is going.

• 2:06Speaker 00

  So like, if you take up a very narrow problem and then you hedgehog into it and you become the best at that one thing, that is printing money right now. Like everyone that I'm seeing.

• 2:16Pat Grady?

  What's a good example?

• 2:19Speaker 00

  A good example, for instance, I love what Quandary is doing. I love what Expo is doing in your portfolio. I love what Happy Robot is doing. There are very narrow cases of problems that have a lot of people in it, that don't have a clear solution for software. Like, there's no software to solve that problem. It's people-heavy. And, and it's interesting because they're not replacing people right now, but they're replacing BPOs. So whatever you see BPOs having a big role, that is food for the apex predator that we're seeing right now in the world of AI, which is AI agents.

• 2:59Pat Grady?

  And for the uninitiated, what is Quandary? What is Expo? What is Happy Robot?

• 3:03Speaker 00

  So, Quandary does policy renewals.

• 3:06Pat Grady?

  Okay.

• 3:06Speaker 00

  Another one that is adjacent to it is a company called Owl that does, they, they, they're in the insurance space too, but they, when they, but they review claims. They review claims data. Again, super tiny. Like, you look at it and you pass because you think that the world is really small. But when you look at all the amounts of claims that people do, and the ones that get left over, you know, they're taking care of those. Happy Robot is, it is doing, it's calling truckers on behalf of brokers. So if you want to send beer from Milwaukee to Boston, and you call, you call a broker to find your trucker. Happy Robot spins up 2,000 agents. Agents call the truckers, which is, you know, a guy and a dog. And they negotiate with each other until they book the load. And then they call the trucker all the way, all the way to the delivery.

• 3:50Pat Grady?

  And of course, once that Milwaukee beer gets to Boston, the Bostonians are going to send it right back home.

• 3:58Speaker 00

  Exactly, but somebody has to move the beer around. So like, so this, this is a thing.

• 4:04Speaker 00

  And, and Expo, of course, does pen testing. And, you know, again, they took out the, the pen testing agencies, they, they rank them, they look like the best, and then they run it for you. So these are, in my mind, very narrow problems. So like, Expo doesn't come and say, I'm gonna be a full cybersecurity solution, which eventually they will be, but then you're saying like, I'm just going to continuously bang against the door of every single app and back, and backend that you have, and I'm just going to figure out a way to penetrate it, and that's gonna happen, you know, with the highest quality possible. And it's gonna happen continuously, which is unavailable right now.

• 4:38Pat Grady?

  And is the converse also true? The things that are not working are things that are too broad in scope at the moment?

• 4:44Speaker 00

  I think there is a lot of traction in things that are broad in scope. In terms of like companies coming out, and they're doing okay, they're quite well, like Harvey's doing quite well. And they're, they're not so broad in scope, like they're narrow into like the legal system. But I'm excited for, you know, what Crosby's gonna do, for instance, you know, they are, they're tackling the problem in a, in a, in a, in the similar space, but with a different approach, you're just like full out replacing, you know, the, the, the lawyer, you know, for commercial, for commercial contracts. But if you go too broad, like for instance, AISDR is a little too broad. And that encompasses a lot of things, it means a lot of different things for a lot of different people.

• 5:25Speaker 00

  There's, there is gonna be swirl. So I don't, I don't, I don't like to characterize it into like, you know, what's working, what's not working. I characterize into what's working now and what's not working yet.

• 5:34Pat Grady?

  Okay.

• 5:34Speaker 00

  You see what I mean? Like, what's going to, what is going to be refined and eventually come through? Like, for instance, the one that I, that I'm waiting for with bated breath is AI assistance for like EAs. Like, who's gonna be my AI EA? And, you know, I think there is Linde and there is Fixer out there. But they're not quite, quite, quite there yet.

• 5:54Pat Grady?

  Yeah.

• 5:55Speaker 00

  You see what I mean? Like, they're not, they're not, for instance, I love, I love Fixer, but I have three time zones that I work through. Like, you know, my, my co-founders in India sometimes, and like, most of our customers are in Pacific Zone, I'm here. And like, getting that to work out just right, doesn't quite work for me. But if I had like, one time zone, and I had like, one line of business, like, if I'm a real estate broker, they are perfect, like, perfect fit for that particular thing. So like, big problem, narrow application, nailed it.

• 6:26Pat Grady?

  We have a, on the EA front, we have a founder to introduce you to. He's, he's in stealth, so I can't say his name.

• 6:31Speaker 00

  Okay.

• 6:32Pat Grady?

  It's coming.

• 6:32Speaker 00

  Perfect. All right. Love to see it. Cause I, this is one of those problems that I'm just gonna wait. I'm not like, I being, you know, hot in EA forever, and I'm just, I'm gonna bite the bullet, and just gonna wait for AI to catch up. So I'm, I'm ready, guys. Send me business.

• 6:48Pat Grady?

  Do you have a sense for which markets are likely to be transformed sooner rather than later, and which markets are gonna be more resistant to AI transformation?

• 6:58Speaker 00

  So I have this, I heard this thesis. When I came up with the idea for, for paid, it was right around when Strawberry dropped.

• 7:07Pat Grady?

  Yeah.

• 7:07Speaker 00

  And you guys wrote that paper on, on the, the shift to, to cognition.

• 7:12Pat Grady?

  Act 01.

• 7:13Speaker 00

  Right, yeah, yeah.

• 7:13Pat Grady?

  Thinking fast and slow.

• 7:14Speaker 00

  I remember where I was. Like, it's one of those things that, like, I, I read the paper, and then I, I listened to somebody reading the paper. And like, I remember where I was. Like, there's so many episodes in your life, you remember where you were when that happened. Like, I remember exactly where I was when that happened. It just hit me.

• 7:30Speaker 00

  And I, I was, I was listening to, I think it was Mamoun, from Kleiner?

• 7:37Pat Grady?

  Mm-hmm.

• 7:38Speaker 00

  Who had this hypothesis that I actually fully disagree with. So.

• 7:41Pat Grady?

  Fully disagree?

• 7:42Speaker 00

  Yeah. So his hypothesis is that AI is going to start with the highest paying jobs.

• 7:46Pat Grady?

  Okay.

• 7:47Speaker 00

  Because that's where the money is, right? So it makes logical sense, right? You go and target the most expensive job, and you just place those, you know, developers, lawyers, accountants, doctors.

• 7:56Pat Grady?

  Mm-hmm.

• 7:57Speaker 00

  I actually disagree with that hypothesis. I think AI is, the highest paid people will buy AI as a side thing, and ditch it with the same regularity that they ditch other things in their lives. I think AI is gonna stick the landing where it actually takes over our role, fully. That nobody else wants to do. So for instance, nobody wakes up and wants to be an insurance actuary or an insurance adjuster.

• 8:21Pat Grady?

  Our partner, Rula Poto, would beg to differ. Yeah. Perhaps, perhaps the only licensed actuary in the world of venture capital.

• 8:27Speaker 00

  All right. So I'm sure there is an exception to that, but like, these are jobs that are hard to, that are hard to backfill.

• 8:33Pat Grady?

  Yes.

• 8:34Speaker 00

  So, you know, when Quandary does is, this policy renewals people, like, they're just like, they're replacing people that are exiting the business and they're not filling it back on, right? The same thing was like, nobody wants to wake up and like, work for a BPO banging out the phone. Like, they do that job for like, six months on, on the way to a different job. So the turnover on these jobs are really high. So what I'm observing from my end is that the companies that are doing really well are addressing pools of labor that are either disappearing because of retirement or they want to do something else.

• 9:05Pat Grady?

  Yes.

• 9:06Speaker 00

  Or they're, or they're run by BPOs.

• 9:08Pat Grady?

  Yes.

• 9:08Speaker 00

  And in that segment, I'm seeing a lot of stickiness. I'm seeing a lot of expansions. I'm seeing a lot of growth and really good economics.

• 9:16Pat Grady?

  Yes.

• 9:16Speaker 00

  Like, I can charge whatever I want. You know, my upper bound of my price is the labor cost. My lower bound of my price is my margin. And, and people are going to town on that. So like, in terms of like, people experimenting with like, outcome based, et cetera, that's where I see the majority of my, of my traction. In the broader, the reason I disagree with like, you know, the rich job replacement is because everyone is gonna go there. You see what I mean? If OpenAI needs another source of revenue, or a company needs another source of revenue, they're gonna go after lawyers and accountants. Why? Because it's hard and they pay a lot. And they buy everything. So like, I feel like that market is gonna be hot for now, and then it's gonna be super competitive. And then you're gonna have a lot of people in it.

• 9:53Pat Grady?

  See, I wonder if you can have your cake and eat it too. I wonder, I wonder if both you and Mamun are correct in the sense that for the higher paying, more creative jobs.

• 10:01Speaker 00

  Yep.

• 10:01Pat Grady?

  I think the co-pilot approach, and I don't mean Microsoft co-pilot, I mean, the, the approach of AI that is giving people superpowers.

• 10:07Speaker 00

  Right.

• 10:08Pat Grady?

  Seems to really be working, you know, Harvey in legal or open evidence in medicine. Whereas for the jobs that are lower paying and a little bit less creative, the full autopilot

• 10:16Speaker 00

  Right.

• 10:17Pat Grady?

  approach seems to be working where you're fully replacing the work with an autonomous agent that can do it. Better, faster, cheaper. And so I wonder if it's both. And then as far as modes for the copilots, I think you're right that because those are big categories where there seems to be a lot of money, there's going to be a lot of competition. I think what we're also seeing is collaborative workflows, which are kind of the eighth wonder of the world as it comes to software.

• 10:37Speaker 00

  Right.

• 10:37Pat Grady?

  You know, collaborative workflows still work.

• 10:41Pat Grady?

  You tend to get pretty deeply embedded into your customer. And then once you're in there, you're providing a ton of value and they don't really want to switch.

• 10:47Speaker 00

  Right. No, it's true. But I think the world has changed a little bit in that, you know, I don't know that you're going to see Asanas anymore or Service Nows or like any of those. Like, you know, they work in the collaborative workflow when it didn't exist and they were, you know, revolutionary. I think now anyone can spin up, you know, you can vibe code Service Now.

• 11:09Pat Grady?

  This is a good topic. So vibe code. Are you a believer or not? Where are you on vibe coding?

• 11:13Speaker 00

  I think I, we're, dude, we spun up paid in like a month and a half.

• 11:18Pat Grady?

  You are a vibe coder.

• 11:19Speaker 00

  And half of it was vibe coding. I mean, we have to throw it away, but this is the beauty of vibe coding. You can throw it away and re-spin it. You know what I mean? Like, there is no, like, there is a lot of people getting hung up on like the whole debugging thing. You don't debug vibe code. You throw it away and you start. And you put it in production and when it breaks, you start. It's wonderful. You can always start.

• 11:38Pat Grady?

  This is very comforting to your customers.

• 11:40Speaker 00

  Yes. Well, I don't have a lot yet. So I don't have a big problem, but eventually it will be a big problem. And to start is a very easy thing. So but back to the workflow question. I think that you're right. So if you become a definitive workflow for X or Z, like, it's definitely a sticky point. I just think that the speed of competition is really high right now.

• 12:00Pat Grady?

  Yes.

• 12:00Speaker 00

  And copilots have, the explainability of the value of a copilot is really hard to land. Like, how do I differentiate one copilot versus the next versus the next versus the next? And they're all can come and say, I'm the same as X, but better or cheaper. And that's a recipe for swirl. So unless they specialize in verticals and say like, if you are, you know, it's hardly worth to say like for, I don't know, patent law, I am the best. And I got 78% of the market. Boom, right? But now you're moving into the very narrow application with very narrow set in a very rich market. It's rich because you own the whole of it, not because the whole market is rich. You see what I'm saying? So that's, that's why, but look, we're all hypothesizing here. Like, I make money either way.

• 12:45Speaker 00

  So I'm happy for all of it to work out.

• 12:48Speaker 02

  So you're trying to jump in to help with this on pricing and packaging? What are you seeing work today?

• 12:52Speaker 00

  So I'm seeing four things stick in the landing with aplomb, with gusto. One is, you know, clearly charging by activity. You know, that's an easy one. It's, you know, it has a credit consumption type model and you can, you can show the activity that was done fairly easily. The other one that I'm seeing more is charging by workflow. When you string a number of activities and you say this workflow is cost this much, like a document review, right? Because then you can separate documents that are small from documents that are long and complicated. Because they have different consumption patterns.

• 13:28Pat Grady?

  And it feels like you're getting closer to value-based pricing as opposed to cost-based pricing.

• 13:33Speaker 00

  Exactly, exactly. So like moving to a workflow allows you to move out of the, the threat mill of charging for, you know, for pure work to charging for actually that is worth something to somebody. And then eventually you will get to some kind of outcome.

• 13:46Pat Grady?

  Yep.

• 13:46Speaker 00

  And what I've been recommending to my customers, not out there yet, but I'm going to give it a push, is to charge, instead of charging per outcome, get an outcome bonus. Meaning if an outcome happens of a particular quality that is measurable, charge for it. That way it, it begins, it opens the door to a conversation of value alignment. And the moment you open another conversation for value alignment, then you start getting into more bespoke contracts with each of your customers, which are super hard to rip out.

• 14:13Pat Grady?

  And historically, that's been a tough pricing model to pull off. Do you think AI changes that?

• 14:17Speaker 00

  I think AI changes completely, completely changes that. Because in the, in the past, we wanted to put everyone in these little boxes, you know, called SKUs. And then we wanted to count SKUs and each Q will have a, you know, a discretionary amount of discounting and whatnot. That was a world of rows and columns and you don't need that anymore. You can, you know, if you go to the largest companies, again, like a service or a sales force, all their large contracts are bespoke. You know, so you know, you send off, you know, Paul Smith or, you know, their CRO to go and sit down with, you know, the counterpart and he comes back with a deal. And the deal has all sorts of complications in it that doesn't belong into the like the CPQ world. You know what I mean?

• 14:59Speaker 00

  And I don't know why in the agentic world, you wouldn't do that all the time with the customers that you want to go big with. And there is no, you know, you can always put a chat interface to say, interpret this contract for me and give me the annualized value. You can inquire, you know, the all the body of contracts that we have done and get a sense for like your unit economics and your growth and like what this looks like. So I think that custom contracts is here.

• 15:24Pat Grady?

  Okay, you had four things. There was activity based, there was workflow based, was outcome a third?

• 15:28Speaker 00

  Outcome is a third.

• 15:29Pat Grady?

  And what was the fourth?

• 15:30Speaker 00

  The other one, the fourth is paid by agent.

• 15:32Pat Grady?

  Paid by agent, how's that work?

• 15:33Speaker 00

  And so I've been working with a lot of the AISDR companies to get into, to introduce this as a concept. Because a lot of what they're doing is replacing, say, 80% of what a normal SCR would do. And a SCR, you know, fully loaded will cost you some more between 70 and 90,000 dollars a year. So you can pay instead of saying a platform fee, say like, you know, I'm going to deploy X many agents. The agent is going to do this amount of work that is equivalent of a 90,000 dollar a year SCR. I'm going to charge you 20,000 per agent. The agent is going to deliver this much work and you can pay me a bonus for meeting, for meeting booked.

• 16:12Pat Grady?

  Yeah, how do you, how do you define? I guess, how do you define the job of an SDR? Do you just say, hey, your human SDRs have a certain quota. This agent's going to hit the same quota.

• 16:22Speaker 00

  Yeah, when you hire an SDR, the first thing you get is activity.

• 16:24Pat Grady?

  Yep.

• 16:25Speaker 00

  So you get X many calls, X many meetings. You have a book of accounts, you have, you know, contacts within each of that account. And each, each of those contacts get an activity, right? So that's where you get the, you know, 100 calls a day type of SDRs. You can do the same thing with an AISDR. You can say like, you're gonna, you're gonna draw a, a, a boundary around the activity that this agent is going to do. And then you're going to charge for that agent. Because the output is the same, right? And then, and then your job is to say, look, instead of paying 90,000, pay 20,000 for the agent. And then pay me a bonus for meeting booked. Pay me a bonus for an opportunity close one, which is very similar to the equivalent of hiring, which is the hiring of a human in the flesh, SDR.

• 17:07Speaker 00

  And you get to dip into the headcount pool of budget, as opposed to the tools pool of budget. So you're not in the rev ops purview in terms of like where my head, where my budget is coming from. You're on the HR, which is far larger. So that's what I'm sort of like trying to steer people away from,

• 17:26Speaker 00

  from, you know, charging like it was a tool, because then you're constrained, right? Like then the CRO has a budget for so many things and you'll get a sliver of that as opposed to like full headcount replacement.

• 17:37Speaker 02

  What are the pitfalls with, that you're seeing with companies that are ending up in the, charging as a tool bucket rather than charging for the work?

• 17:45Speaker 00

  That then you get pigeonholed into seats.

• 17:47Speaker 02

  I guess like, what are people doing that makes them get pigeonholed?

• 17:51Speaker 00

  A lot of what I'm seeing selling is the vast majority of AI agent companies are doing PoCs right now. I mean, they look like contracts and they look like their money, blah, blah, blah, blah, blah. But in reality, every company in the planet got an AI mandate. So somebody in that company went and, you know, pursue some software and then they bought it. And they bought it as software and as a trial.

• 18:11Pat Grady?

  Vibe revenue.

• 18:12Speaker 00

  Yeah, a hundred percent.

• 18:13Pat Grady?

  A lot of vibe revenue.

• 18:14Speaker 00

  Okay, so like, so now you have the vibe revenue curve. And now soon, we're going to come into renewal land. And that's going to separate, you know, the wheat from the chaff. And at that point, you're going to figure out who real, who got real stickiness and who doesn't. And that's where the real money decision scheme is going to come in. Because they're going to figure out like who made money, who didn't make money, what kind of value they deliver or not.

• 18:34Speaker 02

  They'll see the outcomes.

• 18:35Speaker 00

  And then we'll see the, right, exactly, a hundred percent. And it's funny because, you know, a lot of my early customers, I told them that how I thought about the world and it's like, yeah, that will never happen. And now they're calling me back and be like, hey, I just got my first contract that only pays me per outcome. And I call on you because I don't know who else to call. So I feel like this is going to be pulled by the buyer. You see what I mean? As a way to mitigate risk. Because AI is risky in a number of dimensions. And outcome actually lowers your risk.

• 19:05Pat Grady?

  Is this in the four things you mentioned? Activity, workflow, outcome, agent. Is that a maturity curve of sorts? Like, is the idea that you want to get to selling agents? Or maybe you want to get to selling outcomes?

• 19:19Speaker 00

  It's a fascinating question. So the answer is, I think there is a maturity element into it. But it's a little bit of like making your own adventure element to it. In that, in that there's a bottom line. So everybody has to get out of selling by activity. If you stay there, somebody will come along and say, I'll do the same thing for cheaper. And then you are in a nightmare scenario in which there is tons of others who look just like you. Messaging is just like you. And the only way to separate the wheat from the chaff is to try. And now you're like churning from one to the next. So, so yes, there is a maturity level in that if you don't move out of that bottom one, which is easy to sell, you'll get competed out.

• 20:03Speaker 00

  Once you get into workflows, then you're into value-based pricing. And then you're defining what the workflow is and why is that important? And then you're in a deeper conversation. And that forces a much better alignment. And that requires some, so I guess the answer to your question is yes. That requires some level of maturity to have a conversation with your customer. Your customer will always default to some, like the easiest way to buy, which is either, you know, some kind of fixed price or a consumption price for the first year to see if it works. But if it does work, it is up to the AI agent builder and creator to go back to the same customer and say, let's align on things that are important to you and charge for it.

• 20:35Pat Grady?

  Do you have any sense of which markets are likely to stay with value-based pricing? And which markets are likely to collapse into cost-based pricing? Have you seen sort of early indications from the companies that you're talking with or working with? You know, of markets that are trending in one direction or the other?

• 20:51Speaker 00

  So what I'm seeing right now is that for those who are targeting BPO budgets, to win that business, they go at the BPO price and lower it. And they say, I'm going to do the same as a BPO, cheaper 24/7. And I'm going to accumulate all the data that the BPO used to do. But I'm seeing, but again, I'm seeing that as an intermediate step. Like, that is not the full step. That's just a way to get into the market and win it.

• 21:20Speaker 00

  Then I wonder, the BPO is not gonna just sit there and like, just take it. You know what I mean? Like, this is, these are relatively large companies and they can just as much buy somebody's technology and deploy it. So I wonder what will happen once the BPO turns around and like, deploys their own agents, replaces their own people, uses the data that they have internally to train or to make it better, and then go to town and defend themselves. I was actually talking to, you know, VCG about this and they wouldn't tell me that they're doing a lot of engagement with BPOs, but I sort of like sensed it. And I don't know that they're just gonna sit on their hands and like, see their business go away. Like, that will never happen, right? So like, I wonder, how does it gain sort of like, levels, if you would?

• 22:04Speaker 00

  Like, when, where is the balance of trade? I don't, I don't know the answer to that. But I, I think that to get into a market, you see a lot of initial, you know, let's price it the easiest way for somebody to consume, but to advance into the market, you may need to switch to something else. Like, in the A I S E R also that everywhere, like, everyone came in and charging by some kind of like token or credit or like activity, but then it became a bloodbath. And there's like 50 of these guys and they're all kind of like, sound the same. So unless you start putting, making some assertions of your quality and putting your pricing to back that assertion, meaning I'm gonna get you five qualified meetings or I'm gonna charge you per agent that replaces a human being, then you're gonna get, you know, competed away. Yeah.

• 22:42Speaker 02

  And as you move into these more, the later maturities of pricing models, how do you see people measure and actually implement these things?

• 22:49Speaker 00

  I think that's kind of the beauty in that, to each customer, the definition of success is gonna be a little bit different. And a little bit of like, I feel like I was like John the Baptist walking around like eating locusts and honey and like, looking like a crazy man telling people that they should do bespoke contracts and everybody was looking at me like I'm crazy. Now it's coming around to say like, you know, the ability for you to understand your customer's business and price and contract around it and have the engine behind it to support it, is actually a competitive advantage in a world in which you all have the same tools. But it wasn't obvious, it wasn't obvious when I started. Like, you know, I remember we talked in like September last year, like it wasn't obvious back then.

• 23:34Speaker 00

  It's getting a little bit more obvious now as we're turning on the lights in different parts of the market. Where people are saying, yeah, we need to do something that, you know, is very unique to me. So that I can protect that, that asset or that contract. Second of all, you know, I think it was Seth Godin who said, pricing is part of your story. You know what I mean? And how do you differentiate in your market is your story has to be different. And if your story is different and your pricing is the same, your story ends up being the same. You see what I mean? So aligning with, and this is why like Sierra doesn't have pricing on their, on their, on their main page. Because they're sitting down with each customer and they're finding out what's important to them. Is it time to resolution? Is it that the customer resolves a ticket and then buys something? Is it, you know, a CSAT? Is it MPS? Like, what is it, right?

• 24:18Speaker 00

  And then you, you build the box around, then you say that that's, that's your outcome function. It's just the same as a objecting function in, in, in, in machine learning. Like you create this function of where you want everything to go. And then you keep iterating towards it.

• 24:31Pat Grady?

  Yep. Yeah, well put. All right, talk a bit about the cost side of the equation and how margins play into this.

• 24:39Speaker 00

  So it's really interesting because this is another one that I'm, I'm contrarian. Like everybody's telling me that the cost of tokens is going to go down. And this is going to become a commodity and whatever, whatever. I think in a world of reasoning.

• 24:52Pat Grady?

  Yep.

• 24:53Speaker 00

  Where is inference time compute worth more than training time compute? I just don't see how that, at least in the immediate future, I just don't see how the, this, the token price goes down. Because you're going to require like deeper level thinking. So what the problem with agents right now is that you, you sort of like workflow them, right? So you, you know, you, you go to, you know, Langraph and you, you put your boxes and what, what, what each does. And like you string them together. But the fundamental problem with that is if you have a hallucination at the very beginning of that chain, you're screwed. You have all sorts of like, you know, bad activity happening all through.

• 25:25Pat Grady?

  Yeah.

• 25:25Speaker 00

  And like, there's no amount of eval that is gonna like rescue you out of that. So like, the better way to do it is to have the model do most of the work. You see what I mean? As opposed to have like these little boxes of work. Have the model do most of the work, have a good, you know, eval framework to make sure that, you know, that it's doing the thing that it's supposed to be doing, and then enroll it out. In that world, where you have less error rate, the, I don't see the cost per token going down. I see that if nothing else is gonna go up, as the models get more advanced and like smarter.

• 25:55Pat Grady?

  Well, or it could be the horse race between volume and price. And price for a fixed workload may go down over time, but workloads increase.

• 26:04Speaker 00

  Right.

• 26:04Pat Grady?

  Because you're throwing more computed things at inference time, or because you're just doing more sophisticated jobs.

• 26:09Speaker 00

  Yeah, I think over the long arc of history, I think you're absolutely right. I think in the very short term, as we're trying to figure this out, I just don't, I just don't know, sort of the short of it.

• 26:18Pat Grady?

  Yeah.

• 26:18Speaker 00

  And, and the second thing that I'm seeing actually, which is my big aha moment, is that

• 26:24Speaker 00

  agents are using one modality, and the moment you nail that modality, you wanna use all these other modalities, right? So you do text, and then you want that to do a phone call, or to take an inbound call, and to do an outbound call, or to like a Van Avatar, or whatever that is. And then you're incurring costs that are not LLM, but are third-party APIs. So the full cost of the full service, you got your cloud cost, you got your LLM cost, and then you have like all this other stuff that you have to buy to make it sync in the different modalities in which it's used. Or even like, you know, buying data, or like, you know, buying whatever. And that is what's driving up the cost. So if you look at a, say, an avatar company or a phoning, you know, agent, their cost is not quite the LLM. Their cost is how long are you gonna stay on the phone, and like, the number of dials that you do, or like, how long does the avatar run, etc.

• 27:08Speaker 00

  Like, those are, those are compounding costs that you have to look out for. So like, The problem that we have right now in in cost mode is that because everything like all the activity of the agent goes down through this eval framework that acts as a proxy before the token goes to the L L M, you don't know who's incurring what cost. So you don't know what customer is profitable to you, what customer is negatively impacting your margins, you don't know what agent is doing good job, what agent isn't, you see it as a whole. You see what I mean? And this is why like the margin problem is such a bear to solve.

• 27:39Pat Grady?

  Well, and generally speaking, margins are a reflection of the amount of value that you're providing to your customer. Do you see that in AI apps right now? Or is there a mismatch between the amount of value that companies are providing and the margins that they're able to get?

• 27:52Speaker 00

  It's a mismatch because people don't know how to price and people don't know their cost. So this is why the problem compounds a little bit in that, you know, agent companies are relatively new. So they come to the market just trying to like get business, right? So I'll price in whatever way you want to buy. And only later I find out whether I win or lost. You see what I mean? So I think that this is this is just the beginning of the game that as they understand the unit economics, they're going to price better. As they understand the value delivery, they will price better. But they just don't see it yet. So for instance, we built this thing in paid that, you know, we look at an activity or a workflow, and then we make this call to to the service that tells us, what is the human equivalent

• 28:33Speaker 00

  of the same work? In what country? Right? So, you know, if the work is kind of hard, you know, it goes looks up the type of work, how long, how much would that person make per hour? And how long does the work take and returns a value? So we give our customers this little bit of pricing guidance that says, the human equivalent of the same amount of work is this, you can price up to that point. You see what I mean? Or at least use that to go and say, I need an increase in in in what I'm getting paid because this is actually pretty expensive. But without that, it's it's it's kind of tricky. And it's not like you have Simon Kuchar like price intelligently alongside you, guiding you all along, right? They come in once a year and then they they piece out. You're left holding the bag. Whereas you actually need guidance on this stuff every time you

• 29:18Speaker 00

  talk to your customer to get you to you're getting you're getting your prices worth. Like the the problem we're seeing is that the values accruing to the to the customer, not to the not to the agent business. They're capturing all the value of all the savings. And that needs to change.

• 29:32Pat Grady?

  Yeah.

• 29:33Speaker 02

  So you started a company to help this. Tell us a little about why and what your mission behind it is.

• 29:38Speaker 00

  When we were rolling out agents at our reach. And I wanted to understand the business, the business fundamentals of the agents, my margins, the value that I'm adding and how am I adding value? The underpinning software supporting me was not helpful. It was not built for a world in which pricing needs to evolve, where the agents are doing, are delivering more than just, you know, bits and bites to deliver in this full outcomes. And that just stuck in my head as I moved to London and I stepped aside from being a CEO. And I sort of like noodle on that. And the problem kept on bugging me. So I'm like, is this a problem that was just me? Or, you know, who else had this problem?

• 30:20Speaker 00

  So I spent, you know, a couple of months just calling friends and, you know, other founders. And I always have this trick, right? Like I know a lot about sales, right? And they know a lot about agents. So we will do a cross education, you know, ask me like an AMA, like you ask me anything about like building out sales teams. And I asked him about like what it's like to run an agent business. And I found that this, like running the business itself was all spreadsheets. So when I, and that's number one. Number two, some of the problems were actually difficult, but not intractable difficult. There was just a lot of work. So I love when there is a problem that is big. People are hacking around it and the problem is not like simple as like, you know,

• 31:03Speaker 00

  a couple of lines of code kind of solves it. So we, that, that sort of was the inspiration behind it. Solving the problem. Number three, I wanted to build a company that I get to work with like the new founders. Like, you know, because they are building a company themselves. And that kind of energy just drives me. So like, you know, the most fun thing to do when I was running average was customer conversations. But the customer conversations at the founder level are so raw, are so full of like wondering, mystery and energy. And like, I can just see my energy tank just going up and up and up in every single one of those conversations. And I'm like, I want to do this for a living. Like this is, this is a great place to like exist.

• 31:48Speaker 00

  And the market is going to be big. And it's a small enough market that I can just call, call everybody. And like, most people will return my call. Cause it's founder to founder stuff. You know what I mean? I see your problem, maybe I can help you, maybe you can help me. And boom, you're in, you're in a conversation. So like, it didn't almost feel like selling. It felt like I was solutioning. And at the end of the day, like I would tell them where I'm building this thing. And they were, yeah, let me try it. And like I had a hundred percent history on people who said, let me try it. I'm like, oh shit, let's go.

• 32:15Speaker 00

  The worst that could happen is somebody buys something.

• 32:18Pat Grady?

  We haven't actually said explicitly, what is paid? So maybe, maybe just answer that question. What is paid?

• 32:22Speaker 00

  Yeah, thank you. So paid is the business engine for AI companies. So what we do at paid is that we build the entirety of your billing, invoicing, monetization,

• 32:38Speaker 00

  pricing, even at this point, we're doing collections, revenue recognition. So the entirety of your back or vendor management, margin management. So the entirety of the back office you need to get your business up and running to understand the unit economics and run your business. That's what we're building at paid. And our first foray into the market was our monetization engine and our margin management engine, which is the biggest problem that we're seeing in the market. But we're building the adjacent. So the problem compounds, right? Like the moment you solve monetization and invoicing, then you need to solve collections. The moment you solve margin, then you need to solve vendor management and so on and so forth. So you're, we're just building the unified layer that allows you to run your business in one place.

• 33:17Pat Grady?

  How much of what you learned at Outreach transfers directly to building paid and how much is new?

• 33:25Speaker 00

  The human aspect is the same. Building themes is the same. Inspiring is the same. Selling a heterocapability is the same.

• 33:33Speaker 00

  The, what's new is how savvy the world has become in terms of company building. I think you made this joke in our, in our podcast that, you know, you look at an AI engine company, you take the hood off and it's just building a company. And the building company part has gotten so much smarter. Like everyone that I talked to is like, is way more advanced than I was at the same stage in my building of Outreach, where people have seen, you know, what happened in SaaS, the whole arc, and they're building completely differently.

• 34:08Pat Grady?

  I was gonna say, is that a good thing or a bad thing? Cause I think the positive case would be people are better informed. They're just making better decisions and they're expediting a lot of the aspects of building a company that are not unique to their specific company. I think the negative case would be that people are blindly pattern matching and not understanding the causal determinants that actually lead to healthy businesses over time. Do you think it's more the former, it's a good thing, or more the latter, it's a bad thing? Maybe somewhere in the middle, case dependent?

• 34:37Speaker 00

  To be frank, I haven't stopped to think about that particular question. But if I were to put a qualifier to it, I think that the initial conditions are different. Meaning they're starting from a point in that I'm gonna keep the company small. I'm going to own more of my destiny. So we're gonna raise in a different way. We're not gonna be growth at all cost. I've seen it from several founders already that they take more time honing in who their ideal customer profile is.

• 35:05Pat Grady?

  Yep.

• 35:06Speaker 00

  And making sure that they scale that versus scaling everything.

• 35:09Pat Grady?

  Yep.

• 35:09Speaker 00

  So when I started Outreach, I was always trying to figure out what are the edges of my market? Who should I be selling to? And it turns out I can sell to everybody and that actually makes the problem worse, right? Because I can sell to a startup, I can sell to a very large company, like Adobe was one of my earliest customers. As much as I can sell to the Hillary campaign, as much as I can say to a repo company. They all have communication problems, they all have workflow problems. But they all have completely different ways of getting to them, honing in the product for their particular solution. And it was really hard for me to let go. And I sort of like wallow in the sea of business that I had from every walk of life. Where if I were to relive my company, I would like really hone it in with intention and say like, okay.

• 35:52Speaker 00

  So what does make Outreach a billion dollar run rate company? And then like stack from there. I'm seeing these new founders coming with that point of view. I'm like, what is the narrowest profile that I can sell without a lot of friction? And then going up from there. Now, the problem with that is then they maybe restrained their ICP. I mean, they may not be trying, they may not be experimental enough to grow the company to a, from single product to multi-product to platform.

• 36:19Pat Grady?

  Yeah, but quality tends to scale, right? If you really nail it for a small audience.

• 36:23Speaker 00

  I agree.

• 36:24Pat Grady?

  And you can start compounding from there. That's probably better than being mediocre for a big audience.

• 36:27Speaker 00

  A hundred percent. And like, and it just makes life more fun.

• 36:30Pat Grady?

  Yeah.

• 36:30Speaker 00

  Because your roadmap is a lot clearer.

• 36:33Pat Grady?

  Yeah.

• 36:33Speaker 00

  Your, you know, your tickets, they all look the same. So like the scaling of all the other operations is actually easier when you have one type of customer that you're serving with excellence. And then you get known, the world of Musk gets bigger, like all that happens more organically. Again, like I wish I knew that. You know, when I started Outreach and it was faster to like, all right, let's narrow, narrow, narrow, narrow, narrow. Let's stay super focused on this two things or one thing.

• 36:55Speaker 02

  All right, Manny. So how does one get started with paid?

• 36:57Speaker 00

  So it's a great question. We are now onboarding manually to make sure that we have all the pieces dialed to your business. So you apply and there's a short questionnaire. It's like monetization margins and what breaks you in. We'll schedule a conversation for onboarding and the beauty of being an early-stage startup is that all the onboarding is done by me and my small team. We make sure that we're capturing your agent work correctly. We're making sure that we're guiding you with best practices because we understand the market. At this point, we've seen pretty much everything under the sun. So we understand your market, how you usually charge and give you a few ideas. Get your invoicing trail going, get your margin trail going. So you have visibility into how you're making money.

• 37:41Speaker 00

  And we'll be a short call away at all times. So just apply, make sure that you have an agent business and some customers and then we'll take care of you from there on.

• 37:49Pat Grady?

  And what's it like to be part of your team? Maybe what words would you use to describe the culture of paid?

• 37:55Speaker 00

  I know this is super trite, but the first word that comes to mind is fun. And the reason it's fun is because we're serving an industry that in itself is fun. Like everyone that I talk to that is building agents out there, they can't believe they're doing this for a living.

• 38:12Pat Grady?

  Yeah.

• 38:13Speaker 00

  You know, they can't believe they're like, these are like-

• 38:16Pat Grady?

  What a time to be alive.

• 38:17Speaker 00

  What a time to be alive. They're doing stuff that, and they're getting paid to have fun. So like all our conversations are super fun. Like nobody, like, I remember when I was in SaaS, there's a lot of people who are stressed out and there's all this like, you know, milestones and whatever. So maybe because everyone is early-stage right now. So there is not a whole lot of growth rounds happening. So nobody has like a number that they have to hit or like an efficiency they have to hit.

• 38:41Speaker 00

  But everyone is just like enjoying the discovery. So it's a little bit like that book from Business of Innovation and Wonder. Like everyone is innovating and wondering, like living the art of the possible with like models improving every seven months. Like you have a new toy to play with like every seven months.

• 38:58Speaker 00

  I think the ability, so this is understated, the ability to vibe code an idea, to just at least show how it works and then actually build it, has made the iterations and the conversations so much faster. Like you can just like- Say like, we think we should build this, or I have, you know, have a lot of energy around this thing. And you can just write it, and you can see it work, and you can tweak it a little bit, and then present it in front of everybody and sell it like you're selling internally to another, to another person. So this ability for us to be brass tacks in terms of like, what are we building for whom we're building? Being so small and getting so much work done in a small team and being so close to our customer because we're early, it's just fun. I think, I think that's the best word to describe it.

• 39:42Pat Grady?

  Very cool. Love it. All right, let's jump into the lightning round. You ready?

• 39:45Speaker 00

  All right.

• 39:45Pat Grady?

  That's it. All right. Question number one. Who is on your Mount Rushmore of founders?

• 39:53Speaker 00

  Jeff Bezos for sure.

• 39:54Pat Grady?

  Okay.

• 39:56Speaker 00

  He's a, he's a, he's a big, a big name founder in my, in my life.

• 40:02Speaker 00

  I have a lot of friends that are founders. I just, I just really, they're really inspire me, you know? Like Todd Olson from Pendo, he's, he's a great founder that I just find, he's a great human being as well.

• 40:15Speaker 00

  I really like what, you know, Sam Altman has done with, with OpenAI. I think like the ability to just, you know, push out innovation with regularity and, and be a showman in, in the world. I think it's, it's something that I aspire to be.

• 40:31Speaker 00

  You know, the Colson Brothers are really special to me because they're so voracious in their appetite and their reading and the, and how they think about the world. That, you know, they're so, even though they're, they're very young, they're so wise that I really look up to them. Awesome.

• 40:48Speaker 02

  What's one piece of content that every AI founder should read?

• 40:51Speaker 00

  You know, I've been thinking about this one a lot because the thing that changed my perspective in AI is actually a very old book about a statistical natural language processing that was written by a guy called, his name is Rich Manning. It was mandatory reading at Stanford, computer science program on the natural language program course. I don't know that it is anymore because it's so old, but it's like one of those like oldie but a goodie kind of thing where they tell you how to, you know? You know, how a Markov chain works, how you know, the length of the look back and look forward to try to predict the next word is like the early days of machine learning. And a lot of the stuff that we're doing right now is still based on this statistical approach.

• 41:36Pat Grady?

  Yep.

• 41:37Speaker 00

  So I know that, you know, a lot of advances have been done and like, you know, we now, you know, cut tokens in many different ways and optimize in many different ways. But I feel like if you don't understand where L came from, I don't know that you're gonna get where it's going. So that book is, it's actually not a hard read, even though it sounds like a hard read. It's a fairly easy read, is written in a fairly, you know, normal and accessible way. And I can't believe more people haven't read it yet.

• 42:01Pat Grady?

  What AI product can you not live without?

• 42:04Speaker 00

  Oh, perplexity, that's an easy one.

• 42:06Pat Grady?

  What do you do with perplexity?

• 42:08Speaker 00

  Oh, we do everything like, it's so weird. No, seriously, it's so weird, like fashion advice or like, you know, like, yeah, so the hardest thing for me is to have to take a driving test again. Like, come on, like, you know, I know it's the wrong side of the road and everything, but like, having to relearn everything is just absurd. And I've been, you know, pushing away, learning how to drive here in the UK. And my, my wife had to beat the bullet because one of us had to drive at some point. And she just went to perplexity and looked for like, you know, advice on finding a good person to help her how to drive. And like, she found this super guy that has helped her go from zero to driving in like no time, which I, you know, I didn't know perplexity can do that, but like it can. So it's, it's taken over pretty much every aspect of our life.

• 42:54Speaker 00

  That and of course, I don't write anything without Anthropic anymore. Like Claude is my constant companion for pretty much everything I do. It's like my, it's like a friend that I talk to and I shouldn't be talking to.

• 43:07Speaker 00

  If we were to have imaginary friends, Claude is mine.

• 43:09Speaker 02

  Models are commoditizing, yes or no?

• 43:13Speaker 00

  No, not yet, not in a world of reasoning. I think that we're just scratching the surface where this can go. And there's a lot to go.

• 43:23Speaker 00

  Like, if you see every new model coming out, the input tokens are like far more expensive than the one they leave behind, like by a factor of like six or seven or eight, like not by a small amount. And I think that this is just gonna continue as we discover new things.

• 43:37Pat Grady?

  On what date did we or will we reach AGI?

• 43:43Speaker 00

  I think it's.

• 43:46Speaker 00

  I think it's kind of here already, just in an underused kind of way. We haven't really bottomed out everything a model can do. So I think it's just it's behind door number three or something like I think it's already here. We just haven't acknowledged that it is.

• 43:59Pat Grady?

  Yeah.

• 44:00Speaker 02

  And then what was your what's your most optimistic future state for AI? Describe it.

• 44:05Speaker 00

  It's a it's a scaffold for human imagination. I think we also haven't really, you know, absorbed how much smarter we get when we have somebody else doing a lot of the thinking and discovering for us. It's sort of like when somebody props you up on the shoulders, like all of a sudden you can see farther and longer is AI is doing the same thing for us. We can we will now be able to see farther and longer and like come up with like things that were impossible before. And I can't such a time to be alive.

• 44:33Pat Grady?

  Yeah. Last question, one piece of advice for AI founders.

• 44:37Speaker 00

  Stay focused on a very narrow set of customers. Don't worry about TAM. Disregard, and they say this all over in the world, disregard VC advice about big TAMS. A small TAM will be big TAMS as long as you deliver a superb experience.

• 44:55Pat Grady?

  Awesome. Thank you, Manny.

• 44:56Speaker 02

  Thank you.

• 44:57Speaker 00

  Thank you. That was awesome.