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Conversations with founders and operators at businesses between 1 and 100 million

  1. 4d ago

    E64: Profitable Marketing with Bryan Bumgardner

    In this episode of 1 to 100, formerly The SAAS Operators Podcast, Bryan Bumgardner from Northbeam joins us to talk about AI adoption, measurement, software moats, and how Northbeam is growing. We start with dashboards. AI can give you the answer directly, but most companies still want to see the numbers, understand how the answer was reached, and keep the workflows their teams already know. Bryan explains why that makes AI adoption as much a change management problem as a technology problem. We talk about why AI-native startups can change faster than larger companies. New companies can build their workflows around AI from day one. Larger companies have existing teams, systems, incentives, and processes that make the same change much harder. Bryan explains why Northbeam sees part of its job as helping customers move into a more AI-enabled way of working. Northbeam already has the data, measurement systems, and experience of thousands of brands. AI can make that collective knowledge easier for customers to access and use. We also talk about what creates a software moat when product development gets cheaper. Bryan argues that Northbeam's main asset is its data. The company has built identity graphs, device graphs, and petabytes of data that cannot be recreated by simply building a similar interface with AI. Rishabh makes the case that AI creates more value when it helps companies grow than when it only cuts costs. Cost savings have a fixed ceiling. Growth does not. For a company like Northbeam, the opportunity is using its data and intelligence to help customers make better decisions about where to spend the next dollar. Bryan also explains what is working for Northbeam's growth. The company focuses on education, authority, relationships, small dinners, and its Media Buyer newsletter. The newsletter grew from about 2,000 subscribers to more than 100,000 by publishing aggregate performance data and giving marketers a way to compare their results with the wider market. We finish with measurement. Bryan explains why there is rarely one perfectly correct answer to whether a campaign worked. Northbeam combines incrementality testing, MMM, MTA, and experienced media strategists to help brands make decisions with the highest probability of being right. The lesson for software companies is AI makes product development easier, so the value moves toward assets that are harder to copy: proprietary data, institutional knowledge, trusted relationships, and people who know how to turn those assets into better decisions.

  2. Aug 26

    E63: The AI War Machine with Rabah Rahil

    In this episode of 1 to 100, formerly The SAAS Operators, Rabah Rahil joins us to talk about what software businesses look like when AI makes development cheaper, increases leverage, and changes how companies buy. We start with the idea that SaaS is done. Rabah argues that this is overblown. Rishabh points out that software consumption is still growing quickly, while companies like Anthropic can produce huge amounts of revenue with far fewer employees than older software companies. The bigger change is the amount of leverage software now creates. We talk about the rise of AI-powered services. Rabah thinks many businesses would rather buy an outcome than another software tool. AI lets agencies and service companies deliver that outcome with much less headcount, while keeping the domain expertise and flexibility that software alone can miss. The go-to-market model also changes by market. Some companies need PLG with very fast time to value. Others need founder-led sales, CEO-to-CEO selling, and a services layer that helps the customer implement the product. Rishabh argues that the middle ground is becoming a difficult place to build. Rabah also explains what he has learned building Doctrine, internally called War Machine, while using it inside a real marketing team. His main lesson is get the product into the hands of real customers as early as possible. A product can feel productive to build, but founders can use product work to avoid the harder job of building the company and selling. We also talk about why distribution matters more as development gets cheaper. A better product can still lose to an incumbent with stronger sales, relationships, and market access. Rabah argues that building software is becoming easier while building distribution remains difficult. The lesson for founders is build for real demand, sell the product that exists, and choose a go-to-market model that matches how your market buys. AI makes it easier to build. It does not make distribution, trust, or customer adoption automatic.

  3. Aug 19

    Building David with Brandon Doyle

    In this episode of 1 to 100, formerly The SaaS Operators , Brandon from DAVID AI joins us to talk about building an AI transformation company across e-commerce, construction, law, and other industries. Brandon explains why DAVID AI moved from AI-powered marketing into a broader service model. One client was paying about $48K per month across four different software products. DAVID AI replaced them with one custom system that costs about $9K per month.We talk about why e-commerce can be a harder market to serve. The operators are often early adopters, willing to build internally, and surrounded by platforms like Shopify, Meta, and Google that are already adding AI to their products. In other industries, the gap between what AI can do and what companies are using today is much larger.Brandon also explains why he thinks AI services can serve almost every business. DAVID AI can work with masonry companies, law firms, HVAC companies, roofers, software companies, and e-commerce brands because the core job is finding where AI can remove cost, simplify systems, or improve how the business works. We also talk about what happens as Shopify, Meta, Google, and other large platforms automate more of the work agencies and software companies do today. The role of the service company may move toward strategy, system design, and making sure the automation reflects how the business actually wants to operate. Brandon explains how DAVID AI hires engineers through one-day hackathons. The harder hire is someone who can enter a company, understand the business, identify what should be built, and explain the solution well enough to get the company to act. We also talk about the gap between companies at the front of AI adoption and companies that are still several steps behind. There is a large opportunity for people who understand the tools today to help the rest of the market catch up. The lesson for founders is don't let your network decide which market you serve. The best market may be the one where your product or service creates the most value.

  4. Aug 17

    E61: How Alex Persson Rebuilt Privy

    In this episode of 1 to 100, formerly The SaaS Operators Podcast, Alex Persson joins us to talk about rebuilding Privy after it went from a nine-figure acquisition to a business that was close to worthless in less than two years.Alex explains why he now treats most business problems as product problems. Since rebuilding Privy, the company has gone from almost no growth to 30% growth while remaining profitable. His focus is product quality, customer feedback, and removing the small points of friction that compound over time.We talk about how Alex looks for undervalued assets, why he wants Privy to stay default alive, and how the company acquired two venture-backed businesses that had raised around $100M combined. Privy paid with equity instead of cash and acquired products, revenue, and talent at a fraction of the capital previously invested in them.We also talk about venture capital and how quickly sentiment can change. A company can become attractive to investors almost overnight, even before its long-term enterprise value is clear. Alex and Rishabh explain how good investors use capital, structure, and relationships to improve the probability of a good outcome.Alex explains how he approaches acquisitions when founders and investors want a different outcome. He looks for situations where investors can get liquidity or equity in a profitable company, founders can move on, and Privy can keep compounding the acquired business.We also talk about the difference between a founder and a CEO. Some businesses need someone to create a new direction. Others need someone to reduce volatility, improve process, and keep building enterprise value over time. Alex argues that the job depends on what the business needs at that point in its life.The lesson for founders is know what type of business you are building, what type of capital fits that business, and what role the company needs you to play. Long-term success can come from compounding at 20% or 30% per year just as much as it can come from raising large rounds and growing as fast as possible.

  5. Aug 17

    A big announcement....

    Jeremiah is officially a free agent.In this episode, we talk about his departure from KnoCommerce and Stamped, what he learned operating inside Tiny, and the decision he now faces, take a break, spend more intentional time with his family, or start building the company he has been thinking about for seven years.We get into founder motivation, money as a scoreboard, the difference between freedom to do nothing and freedom to build whatever you want, and whether it is possible for a lifelong builder to genuinely switch off.Then the conversation moves into AI and the increasingly strange reality that different people appear to be living years apart from one another.Most people are still using AI like we used it two or three years ago. Meanwhile, a mechanic can learn to code, build a software company by himself, and reach a projected $10 million revenue run rate in less than two years.We discuss what happens when individuals stop selling their time and start building productive assets, why AI could radically reduce operating expenses, and how those productivity gains eventually show up as lower prices, better products, greater abundance, and consumer surplus.We also talk about whether real estate will demonetize, why companies may need fewer people while creating more job openings, and which human abilities become more valuable as execution becomes abundant.The answer may be judgment, curiosity, creativity, emotional intelligence, and the ability to understand what another person actually wants.This is a conversation about what founders build next, how AI changes the structure of a company, and what remains scarce when intelligence and execution become cheap.If you'd like to talk to Jeremiah Prummer about how he built, grew and exited Kno Commerce, then led 3 software business through profitable and steady growth as the CEO, Jeremiah is now on MentorPass: https://www.mentorpass.co/jeremiahprummer

  6. Aug 14

    E58: Building AI Employees

    In this episode of the SaaS Operators podcast, Jack, Jeremiah and Rishabh talk to Burak Karakan about how he's building an AI data team companies can use.They cover why his company started with a data integration layer before adding agents, how that helps tackle messy, multi-source business questions, and whether the company plans to move from time to insight toward taking action on a business's behalf.The conversation moves into open source as a trust-building strategy, Burak's reluctance to lean into services, and the SMB versus enterprise debate, with Rishabh and Jeremiah weighing in on the opportunity sitting in enterprise.Burak explains why he'd rather build like Stripe than operate like McKinsey, even if it costs him some upside.The episode opens with a detour into baby monitors and smart diapers, and closes with Rishabh's "does it matter or not" framework for cutting through the noise and giving honest feedback.

  7. Aug 13

    E56: Building AI from Bangalore with Yash Chavan

    In this episode of the SaaS Operators Podcast, Rishabh Jain is fresh off three 20 hour days, a 20-minute layover in Denver, and four hours of sleep. Fueled by coffee and diet coke with zero complaints.The conversation starts with the AI adoption gap. Rishabh came back from Cincinnati with a clear read, the average person there is about two years behind SF, not nine months. Jeremiah added that the early adopter bubble is small, and the people outside it are just now using ChatGPT to rewrite website copy. Yash shares what’s happening in the India AI space. Bangalore is moving, Anthropic and Cursor both have offices there, and a generation of graduates who want startups over Infosys are driving it.Jack raises the first mover question. If anyone can build what used to take six months in an afternoon, what's the actual moat? Rishabh's answer: it depends on what the business is optimizing for. VC-backed, you land grab. Cash flow business, maybe speed matters less. Shipping velocity and stability get unpacked too, and Rishabh draws a line. Agentic workflow software doesn't have the same availability requirement as transactional software. Claude goes down for two hours while an agent runs a task, it doesn't matter.Rishabh shares how he built a bot trained on how he thinks, gave it a public Slack channel, and let the whole company use it. People ask better questions to the bot than they'd ever ask him. CEO time goes from scarce to abundant.The episode closes on when to get out of sales calls. Yash's framing is the cleanest: stay in until the rate of learning drops. Once you stop getting new insights, hand it off.Chapter List:00:00 The Demands of Leadership and Work-Life Balance06:02 Regional Disparities in Tech Adoption12:46 First Mover Advantage in a Rapidly Changing Landscape20:32 The Importance of Shipping Velocity in Business25:55 Stability vs. Availability in Software32:01 Creating AI Agents for Enhanced Workflow42:37 The Role of Founders in Sales Calls

  8. Aug 13

    E55: AI Native Teams with Jacob Posel from HQ

    In this episode of the SaaS Operators Podcast, Jacob Posel joins Jeremiah, Jack, and Rishabh to talk about HQ, a cloud-based file system built on top of Claude Code and Codex that launched two days before recording.The origin story is good. Jacob meets Corey Epstein, sees a product called Indigo that was ahead of its time but waiting on AI to catch up. They stay in touch. Corey eventually puts Jacob on an internal tool called HQ. Jacob gets hooked, starts pushing the team to build a version for multiple people, and when Ramp published their internal Glass tool, Jacob tweets that they built Ramp Glass for everyone. The demand comes in fast, so he joined the company.The core problem HQ solves is one that Jacob kept running into across every business he consulted with. AI tools are built for solo use. Everyone's working in silos, repeating work, building their own janky version of the same thing. HQ gives teams a shared cloud workspace where skills compound. One person's breakthrough becomes everyone's baseline.Then the conversation goes somewhere more interesting. Rishabh pushes on who actually buys this. His argument is that the buyer isn't the average CEO, it's the founder, because founders are transformers and CEOs are optimizers. The person most likely to get value from HQ is someone who's willing to stay on the treadmill as the technology keeps moving, not someone who wants a finished system handed to them.Jacob's take on pricing is worth sitting with. A customer costs about a dollar a month to serve. The play is distribution. Get HQ into as many businesses as possible, stay close to how people interact with AI, and the monetization builds from there.The episode closes on something most people aren't saying clearly. Getting your team AI native isn't a software problem or a gamification problem. It's a coaching problem. And right now the gap between the people doing it well and everyone else is enormous.Time stamps:00:00 Unexpected Connections: A Humorous Mix-Up05:40 Building HQ: The Journey to Team Collaboration10:42 Targeting the Right Market: Finding HQ's Place16:10 Optimizing AI Usage: The Economics of Token Management22:00 Balancing Standardization and Personalization in Teams24:25 Navigating AI in Business Strategy25:55 Identifying Key Buyers for AI Solutions26:46 The Role of Founders vs. CEOs in AI Adoption27:45 The Mindset Shift Required for AI Integration29:34 The Challenge of Employee Adaptation to AI31:25 The Importance of Continuous Learning in AI33:26 The Future of Work: AI and Employee Dynamics35:18 The Impact of AI on Job Roles and Expectations37:10 Financial Pressures and AI Adoption38:58 Coaching and Support in AI Implementation40:44 The Evolving Nature of AI Technology42:31 Driving AI Adoption Across Organizations

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Conversations with founders and operators at businesses between 1 and 100 million

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    1 to 100
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    2025 - 2026
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