The SaaS Podcast - Real Lessons on Growing Profitable SaaS

Building software is easier than ever. Growing it into a profitable business is the hard part. Every week, a founder gets specific about what actually moved the needle: finding product-market fit, landing customers, pricing, defensibility, and durable growth. Host Omer Khan has interviewed nearly 500 software founders, from their first customers to real scale. You get what actually worked, not theory. Lately that includes the honest take on AI: what it changed about building and selling software, and what it didn't. New episodes every week.

The SaaS Podcast - Real Lessons on Growing Profitable SaaS is a general podcast hosted by Unknown Host, with 0 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Unknown Host hosts The SaaS Podcast - Real Lessons on Growing Profitable SaaS, a general show with 0 episodes published.

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  Episode #494

  Founder-Led Sales to $1M ARR With Just 10 Customers

  Sep 10, 202646 minS0

  <p>He needed a big retailer's data to build the product. No big retailer gives data to a company with no product. Felix Hoffmann solved it sideways: 7Learnings sold a paid consulting project, kept the right to use the data, and built its predictive pricing product on top of it. Ten customers later it was at $1M ARR, and he had closed every one himself.</p> <p>Felix explains why a demand forecasting product cannot start with a small customer, how he structured the first pilot as an A/B test so a retailer could hand over half its prices...

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  Episode #493

  Rick Knudtson (Workshop): The email signal he ignored for 9 months

  Sep 3, 202648 minS0

  <p>Nine months in. Close to zero customers. He was ready to hand the money back to investors. Rick Knudtson had already sold one company, so Workshop started with the idea he found interesting: an intranet. Customers kept telling him to fix email instead. The rebuild took 30 days and brought in 10 customers.</p> <p>Rick explains why big enterprises cannot run internal comms on a cheap marketing tool, how a year of newsletters and ungated resources filled the pipeline before Workshop had anything to sell, and what changed when the founding team stopped defending its own idea and started listening...

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  Episode #492

  Selling Before Building: $1M ARR in Six Months

  Aug 27, 202647 minS0

  <p>Ten thousand ads, all built by hand. Julius Körfgen left that grind to build Uplane, software that automates it, then sold to his first customers before writing a line of code. Uplane reached a million dollars in ARR in about six months.</p> <p>Julius makes the case for selling before building: the cold outreach that got strangers on calls, the one-week sprint from discovery call to working demo, and why he refuses to run a free pilot. Without a dollar attached, he argues, you cannot tell a real business case from a polite conversation.</p> <p>Plus: w...

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  Episode #491

  Enterprise Sales With No Product: Landing a Big Four Customer

  Aug 20, 202644 minS0

  <p>Two founders. Two engineers. No product. Christian Lund closed one of the Big Four accounting firms as Templafy's first customer before the software existed, by selling a point of view instead of a demo. When that customer asked to start with ten people, he didn't say no. He said "yes, if."</p> <p>Christian breaks down his approach to selling to enterprise without a product, why he answered every ten-person pilot request with "yes, if," and how fixing the proof criteria upfront turned trials into company-wide deals. He also explains why disqualifying prospects beats trying to convince them.</p> <...

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  Episode #490

  Featherless AI: When Your Weekend Experiment Makes More Than Your Startup

  Aug 13, 202645 minS0

  <p>He spent two years building his own AI model. Over one launch weekend, a side experiment out-earned it. Eugene Cheah killed the original product and rebuilt Featherless AI around what customers actually paid for. He explains why he concluded people wanted these models more than they wanted his, and how he made the call to walk away from two years of work.</p> <p>Eugene breaks down how GPU hot-swapping changed the unit economics of AI inference, why he charged a flat monthly rate while the rest of the AI industry billed per token, how stripping the technical explanation...

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