Get Paid with Manny Medina

Manny Medina

Welcome to the world of AI agents – where digital workers are reshaping everything from monetization strategies to GTM plays. https://podcast.paid.ai

  1. Stay, Go, or Slow: The Scaling Signals Most Founders Ignore | Mark Roberge

    5D AGO

    Stay, Go, or Slow: The Scaling Signals Most Founders Ignore | Mark Roberge

    In part 2 of this episode, Mark Roberge, Co-founder of Stage 2 Capital, former CRO of HubSpot, Harvard Business School professor, investor, and author of The Science of Scaling, joins Paid’s Manny Medina to break down the real mechanics of scaling in an AI-fueled market. They delve into execution, exploring how to decide when to accelerate, when to hold, and when to slam on the brakes. Mark also shares the Stay / Go / Slow model, founder versus VC misalignment, AI bubble dynamics, business model innovation, and why retention should be slide one in every board deck. “I have a beautiful hack for you called the stay or go or slow model.” The Anti-Annual Plan Mark challenges one of the most sacred startup rituals: the annual plan. “It’s so stupid that we build these annual plans when you're a $2,000,000 business and we abide by them like they’re scripture.” Instead of blindly chasing a 2-to-20 growth promise, Mark proposes a quarterly decision framework agreed upon in advance with the board. After each quarter, you evaluate three signals: Demand generation for healthConversion performanceLeading indicator of retention If all three are green, you accelerate. If any are yellow, you hold the pace. If any are red, you stop pouring gas and fix the system. Most Founders Are Scaling at the Wrong Pace According to Mark, roughly: 45% are going too slow45% are going too fastOnly 10% are at the right pace.Going too slow means the window closes. Going too fast means burn outpaces signal. “If you burned a billion dollars this year and you’re not OpenAI, that’s probably too much.” But burning a dollar is too little. The real skill is calibrating scale risk to context. A high-moat airport software company does not scale like Cursor or Day AI. Winner-take-most markets require aggression. Most-driven markets reward discipline. New Logos Should Not Be Slide One In today’s AI wave, Mark sees a dangerous pattern: Pilot revenue labeled as ARR.Experimental deployments treated as durable revenue.Boards are obsessed with new logos.“The first slide in your board deck should be your leading indicator of retention.” Customer success must be a first-class citizen metric. Not logo count. Not headline ARR. Retention-leading indicators signal real value creation. Everything else is noise. Are We in an AI Bubble? Mark’s answer: yes. Signs of a classic bubble include: Extreme valuation multiplesExtraordinary burn ratiosOvercapitalized first movers‘Vibe revenue’ that looks sticky until renewals hitOn first mover advantage, Mark cites the broader pattern: fast followers win more often than first movers. The first mover wins roughly 35% of the time. The fast follower wins closer to 65%. “I think the last two-year cohort will see the highest failure rate in startup history.” At the same time, the breakout winners could define a generation. Founder vs. VC Incentives VCs have 20 bets. Founders have one. Investors optimize for outliers. Founders optimize for life-changing outcomes. Some investors would rather see a company fail fast than grow steadily at 60% for six years and sell for $700M. That tension fuels overscaling and unnecessary risk. Business Model Risk Is the Startup’s Advantage AI is forcing a rethink of monetization. Per-seat pricing made sense in traditional SaaS. AI automates work. It compresses seats. The safe play is per-module. The bold play may be consumption or outcomes-based pricing. Startups have an advantage: they can take business model risk. Incumbents can’t. Sales compensation plans, revenue expectations, and public market pressures trap incumbents in legacy structures. Today’s Value Prop Won’t Win Tomorrow One of the most strategic insights of the episode: the product printing money today will likely not be the long-term moat. Mark references Amazon’s early focus on books as a wedge. Design big. Start small. Print money in phase one while building infrastructure for phase two. If you build the future too early, the market isn’t ready. If you only optimize for what sells today, you lose the long game. Companies Mentioned HubSpotOpenAIAmazonSlackNotionCursorDay AISiebelServiceNowHarvard Business School See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

    32 min
  2. AI Hasn’t Changed: How to Scale Without Blowing Up

    FEB 19

    AI Hasn’t Changed: How to Scale Without Blowing Up

    In this episode, Paid’s Manny Medina sits down with Mark Roberge, Co-founder of Stage 2 Capital, former CRO of HubSpot, Harvard Business School professor, investor, and author of The Science of Scaling, to break down what actually changes in go-to-market during an AI boom, and what absolutely does not. Mark argues that while AI is accelerating workflows, it has not rewritten the laws of scaling. Human decision-making hasn’t changed. Retention still matters. Unit economics still matter. Hiring 17 reps overnight is still dangerous. They go deep on product-market fit and why it’s not a feeling, the Stay / Go / Slow scaling model, founder vs. VC misalignment, systems of action vs. systems of record, and why the current AI cohort may see the highest failure rate in startup history. “If you burned a billion dollars this year and you’re not OpenAI, that’s probably too much.” First Principles Still Win One of Mark’s central points is simple: AI does not change behavioral science. “AI is not going to change the behavioral science of how humans make decisions.” Much of AI 1.0 has been workflow streamlining, not workflow reinvention. The fundamentals of buyer psychology, sales process design, and value creation still apply. What does change is leverage. Mark believes the first major unlock in go-to-market AI is increasing selling time. “If you increase selling time from 25% to 75%, you triple X productivity right there.” Product-Market Fit Is Not a Feeling Most founders say they’re ready to scale when they ‘feel’ product-market fit. Mark rejects that entirely. “Product-market fit is when you create customer value consistently.” The metric? Retention. Specifically, net dollar retention is north of 100%. In early stages, you can’t wait a year to measure retention, so Mark pushes founders to define a leading indicator: What usage behavior in month one predicts long-term retention? Slack used 2,000 team messages.HubSpot used three features adopted.Notion used weekly engagement.If 80% of new customers hit that indicator, you have product market fit. If not, scaling is premature. The Stay / Go / Slow Model Instead of locking into rigid annual plans, Mark proposes a quarterly decision framework. After each quarter, you evaluate: Demand generation for healthConversion and quota attainmentLeading indicator of retentionIf all are green, go faster. If some are yellow, stay the course. If any are red, slow down and fit it. “It's so stupid that we build these annual plans when you're a $2,000,000 business and we abide by them like they're scripture.” New Logos Should Not Be Slide One In today’s AI cohort, Mark sees a dangerous pattern. Boards ask for new logos, founders report ARR growth, then pilot revenue gets labeled as ARR. But value creation lags. “The first slide in your board deck should be your leading indicator of retention.” Customer success should be a first-class citizen metric. Founder vs. VC Incentives VCs have 20 bets. Founders have one. Some investors would rather see a company fail fast than ‘skimp along’ at 6-% growth. But a founder who builds a durable $700M exit instead of chasing a trillion-dollar dream may protect life-changing outcomes. This tension fuels overscaling. Are We in an AI Bubble? Mark’s answer: yes. Signs of a classic bubble: Extreme valuation multiplesExtraordinary burn ratiosExperimental deployments counted as durable revenueFirst movers overcapitalized “I think the last two-year cohort will see the highest failure rate in startup history.” At the same time, the winners may be generational. Today’s Value Prop Won’t Win Tomorrow The most strategic insight of the episode: The product printing money today is unlikely to be the long-term moat. Mark references Amazon’s early book focus as a wedge. You design big, start small, and build the infrastructure for what the market will want in five years. If you build the future too early, the market isn’t ready. If you only optimize for what sells today, you lose the long game. Companies Mentioned HubSpotSalesforceWorkdayZoomInfoOpenAIMicrosoftAmazonSlackNotionCursorDay AIHarvard Business SchoolBoston Consulting GroupSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

    34 min
  3. How ElevenLabs Scaled from 20 to 500: Building Growth Systems in a Crowded AI Market | Luke Harries

    FEB 11

    How ElevenLabs Scaled from 20 to 500: Building Growth Systems in a Crowded AI Market | Luke Harries

    In this episode, Paid’s Manny Medina sits down with Luke Harries, Head of Growth at ElevenLabs, to break down how one of the fastest-growing AI companies in the world thinks about growth when everything is crowded, noisy, and competitive. Luke joined ElevenLabs when there were about 20 people. Today, it’s approaching 500, and pushing hard from best-in-class model to full-stack product company. Luke and Manny go deep on why traditional marketing channels are the wrong mental model, how ElevenLabs treats launches as systems, and why video quietly became their highest-leverage growth input. They also unpack hiring mistakes, why onboarding should feel like a video game, and which classic startup roles are being squeezed hardest by AI-native teams. “The overall approach we take at ElevenAds is to try and build growth systems. And so these are, like, treating each channel as its own system and really optimizing it.” Growth Is a System, Not a Channel At the core of Luke’s thinking is a framework that replaces vague channels with concrete systems. “When we break down what actually is a growth system, there’s three main parts. There’s the actual system itself, so that’s the people, the checklist, the automations, the code. There’s your model for the system and the analytics, and then there’s the goal.” Instead of asking how to incrementally improve performance, ElevenLabs sets aggressive output targets and works backward. “Let’s say we’re only getting two meetings booked per month from webinars. We’re like, how do we go from two to 200?” The work then becomes identifying and scaling the inputs that make that output possible. “How do we max out every single one of those inputs?” Why B2B Growth Feels Slower Than Self-Serve Luke contrasts his background in self-serve growth with the realities of B2B. “I come from much more of a self-serve high-volume game where everything can be an AB test. Everything now with B2B is much more like, Okay, over a quarter, we spend this amount of money, we do a shot this way, how did it work?” In B2B, learning cycles are longer, and bets are bigger. “Use your intuition, learn from what worked in the past, put your foot down hard, and give it your best shot.” Why Video Became the Highest-Leverage Growth Hire One of Luke's earliest and most unconventional growth hires at ElevenLabs was a motion designer. The reason? Leverage. “We realized the biggest lever for these launches is just really good engaging videos.” As an audio-first company, ElevenLabs couldn’t rely on text alone. “You really need to show audio through video. You can’t just rely on text.” After experimenting with agencies and contractors, the overhead became obvious. “Contractors and agencies, there’s so much overhead. They need to learn the style, the brand.” Bringing motion design in-house turned launches into a repeatable system instead of a scramble. Treat Case Studies As Launches Luke explains why most companies underutilize their strongest proof. “Lots of companies, maybe you’d like to create a case study, but you don’t do that push in the launch.” When ElevenLabs published a case study with Revolut, they treated it like a full launch moment, and it showed. Hiring, Onboarding, and When It Doesn’t Work Out The biggest lever for improving hiring outcomes is onboarding. At ElevenLabs, onboarding is designed to build momentum fast. “We try to do onboarding where it’s kind of like a video game where you, like, start small tasks which build up, which have an impact.” Early, direct feedback is non-negotiable. “I try early on to give concrete feedback because then not only do you help shape the person to the company and get the best output, but also you’re building that muscle together if I'm going to give you feedback.” From Model Company to Product Ecosystem Luke describes ElevenLabs’ evolution in two phases. “The first is the zero to one billion ElevenLabs.” The next phase is depth and surface area: orchestration, integrations, and enterprise readiness. “Then there’s the whole orchestration, then you do integrations with Salesforce, with HubSpot.” Voice orchestration itself is technically complex. “There’s speech to text, text to speech, and the hand taking, and that has to happen in microseconds.” Final Advice Luke’s advice for marketers and operators trying to stay relevant? You can just do things. Proof of work matters more than credentials. And for anyone hesitating: “Jump headfirst. Don’t think too much about it.” Companies Mentioned ElevenLabsRevolutPostHogSalesforceHubSpotGoogle GeminiAnthropicLovableRetoolSemrushDeutsche TelekomPagBankMetaResendSupabaseStripeAnthropicY CombinatorOpenAI See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

    43 min
  4. The Pricing Mistake 90% of AI Founders Make

    JAN 28

    The Pricing Mistake 90% of AI Founders Make

    💵Monetise your AI software with credits — start free on Paid! SaaS pricing has lived in a fantasy world. For 20 years, software got to charge per seat, print margins, and ignore what the real economy has dealt with forever: variable cost, capacity, and brutal competition. This week on Get Paid, Manny Medina brings on Dimi, a pricing strategist from Simon-Kucher, to drag AI pricing back to reality. Hotels, airlines, retail, transportation… industries where pricing is a weapon, not a spreadsheet. They break down what SaaS leaders are missing as agents show up: your cost is now variable, your “seat” metric can actually decline, and cost-plus pricing is a trap that forces you into a race to be the cheapest. Dimi explains why usage pricing often incentives the wrong behaviour, why per-minute pricing is fundamentally broken for voice agents, and why outcome pricing is the right north star but way harder than people admit. He also gets into the uncomfortable truth founders avoid: the best B2B revenue is already “personalised pricing” and we just call it discounting. If you’re building agents, trying to protect margins, or figuring out what to charge when your product has real variable cost, this episode will change how you think. 🟢 Links & resources Get Paid.ai → Follow Manny Medina, Founder/CEO of Paid.ai on LinkedIn - → Paid.ai on LinkedIn → Subscribe to AgentTalk (Substack) 🟢 Listen on other platforms: → Substack → Apple Podcasts → Spotify See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

    52 min
  5. AI Pricing Masterclass with HubSpot Founder Dharmesh Shah

    JAN 21

    AI Pricing Masterclass with HubSpot Founder Dharmesh Shah

    💵Monetise your AI software with credits — start free on Paid.ai. Dharmesh Shah didn’t just build a SaaS company — he helped shape the modern SaaS era. As co-founder of HubSpot, he took the company from zero to public and played a central role in defining how software is built, sold, and priced. Now his focus is on what breaks when AI agents stop assisting humans and start doing the work themselves. In this episode of Get Paid, Dharmesh joins Manny Medina for a direct conversation about the next platform shift — and why it’s closer to the dawn of the internet than another product cycle. Manny is the host of Get Paid and the founder/CEO of Paid.ai, focused on how AI companies price, package, and monetise agent-driven products. They unpack why reasoning models changed everything, why “AI will kill SaaS” is the wrong question, and why the real disruption is the abstraction layer moving up. From the limits of vibe coding to why focus still beats building everything yourself, the conversation goes straight at the uncomfortable decisions founders are avoiding. Dharmesh also shares how HubSpot is making the transition for real: throwing out the roadmap, resetting parts of the culture, and running HubSpot Next like a startup inside the company to build agent-native businesses that don’t fit neatly into the core org. On monetisation, he’s blunt: why seats still matter, why credits are inevitable, why outcome-based pricing isn’t always the right answer — and what happens to software economics when agents replace work instead of enabling it. If you’re building AI products, rethinking pricing, or wondering whether your SaaS model survives an agent-first world, this episode will challenge your assumptions. 🟢 Links & resources Try Paid.ai Follow Manny Medina, Founder/CEO of Paid.ai on LinkedIn. Paid.ai on LinkedIn. Subscribe to AgentTalk (Substack) 🟢 Listen on other platforms: Apple Podcasts Spotify Youtube See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

    1 hr
  6. Stop charging for access. Start charging for results.

    JAN 16

    Stop charging for access. Start charging for results.

    Dan Griggs has seen multiple platform shifts up close. From taking Sitecore through a private equity transformation to leading finance at Intercom, he’s spent his career navigating what happens when business models break and how to rebuild them. In this episode of Get Paid, Dan joins Manny to unpack one of the biggest shifts in software right now: the move from seat-based SaaS pricing to outcome-based pricing driven by AI agents. Dan walks through Intercom’s decision to launch Fin, the AI agent for customer service, and why charging per seat stopped making sense once software started doing the work itself. He explains how Intercom became one of the first companies to price by outcomes, why they landed on 99 cents per resolution, and what that shift meant for margins, sales incentives, procurement conversations, and internal operations. The conversation goes deep on the real economics of AI agents: how resolution rates affect margins, why simplicity beats precision in pricing, and what breaks when companies try to apply the old SaaS playbook to agent-driven systems. Dan also shares how Intercom brought sales, support, and customer success along for the ride, and what founders and CFOs consistently underestimate when making this transition. If you’re building AI agents, thinking about outcome-based pricing, or trying to understand how software economics change when AI does the work, this episode is for you. If you like this podcast, please subscribe on YouTube, Spotify, Apple Podcasts, or wherever you get your fix. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

    57 min
  7. You're going to get usurped by an Al company

    JAN 9

    You're going to get usurped by an Al company

    Maria Colacurcio built Smartsheet into a Pacific Northwest giant. Now, as CEO of Syndio, she's betting the company on a pivot from SaaS to agentic AI. And she's not looking back. In this episode, Maria walks Manny through the launch of Syndi, an AI pay expert that transforms how companies make compensation decisions. Instead of annual pay equity audits that send CFOs scrambling for remediation budgets, Syndi embeds fairness as a constraint in every offer, every promotion, every pay decision. The result: companies save millions in payroll waste while actually improving equity outcomes. Maria is candid about what "burning the boats" actually looks like. She discusses the internal communication challenges of asking employees to commoditize their own product, why some attrition is inevitable during a pivot, and how she keeps her board aligned when engagement scores are dropping and Blind is lighting up. Her solution to board prep? A custom GPT loaded with her deck, messaging, and each board member's particular interests, so meetings become strategic conversations rather than rabbit holes. The episode also covers TD SYNNEX's early adoption of agent-powered HR, why the EU Pay Transparency Directive will force multinationals to explain their pay decisions, and how Syndi tracks the network effect of compensation choices over time. Revealing, for example, that 28% of "ex-OpenAI premium" hires leave as non-regrettable attrition. For any CEO wondering whether to bolt AI onto existing systems or rebuild from the ground up, Maria's answer is clear: your faster, more early-stage competitors will quickly overcome you if you don't go native. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

    39 min

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Welcome to the world of AI agents – where digital workers are reshaping everything from monetization strategies to GTM plays. https://podcast.paid.ai

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