The SaaS Podcast - AI, Growth & Product-Market Fit for SaaS Founders

Five years to the first million. Zero dollars raised. NFL teams pay the same price as high school teams. Hewitt Tomlin built TeamBuildr into a $10M ARR vertical SaaS company by focusing on one job function and refusing to charge enterprise customers more. Founders will hear why flat pricing drove more growth than premium tiers ever could. Hewitt shares how a single conversation with a college strength coach pivoted TeamBuildr from a social app to industry-specific SaaS, why founders who plateau at $500K ARR have a product-market fit problem, and how building for a job function instead of a market segment unlocked every customer from high schools to the NFL. Plus: Hewitt's take on why he won't build AI features until his customers ask for them - even as his biggest competitor bets on replacing coaches with AI entirely. TeamBuildr has 45 employees, has never raised funding, and still operates on the same co-founder agreement from 2012. This episode is brought to you by: 💖 Gearheart → Book a free consult and get the first 20 hours free 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🏢 Build vertical SaaS around a job function, not a market segment: TeamBuildr focused on the strength coaching workflow rather than targeting colleges or pro teams separately. This unlocked every segment from high schools to NFL teams with a single product. 💰 Flat pricing can drive niche SaaS growth through social proof: Hewitt charges pro teams the same as high schools, trading premium revenue for NFL logos that validate TeamBuildr to the volume market. As a bootstrapped company, this was more pragmatic than building enterprise tiers. 🎯 Stalling at $500K ARR signals a product-market fit problem: Hewitt advises that founders putting in full-time effort but plateauing for consecutive years should stop tweaking their go-to-market and reexamine whether their product actually solves what the market needs. 🤝 Treat early users as partners, not beta testers: Hewitt didn't send logins and wait for feedback. He showed up at conferences, called coaches personally, and built relationships. His first customer Dr. Steve Smith is still someone he stays in touch with 13 years later. 🧠 Listen to what customers want, not what they say they want: Customers describe missing features because they can't articulate the outcome they need. Hewitt's job is to peel back the request and identify the real workflow improvement, then decide what to build independently. 🛠️ Don't build AI features for the sake of building them in vertical software: While competitor Volt bets on AI replacing coaches, Hewitt waits for actual customer demand. He uses AI internally for developer productivity but won't ship customer-facing AI without conviction it enhances the profession. 🚀 Inbound marketing gets stronger as your niche SaaS customer base grows: Hewitt transitioned from cold calling to inbound by telling customer stories. Following HubSpot's principle that the best inbound originates with customers, a growing base made content and social proof more potent over time. Chapters What TeamBuildr does and who it's for How the idea started as a social app in college Revenue, team size, and business structure today Pivoting from athletes to coaches The conversation that changed everything Building the MVP and making the first dollar Getting free users to actually use the product Listening to what customers really want Competing with Excel in a market that didn't know SaaS existed Five years to the first million in ARR How Hewitt knew he had product-market fit Outbound vs inbound on the way to $1M Why half the customers are high schools Charging NFL teams the same as high school teams Building vertical SaaS around AI without replacing coaches Why customers aren't asking for AI yet Lightning round Resources Full show notes: https://saasclub.io/476 Join 5,000+ SaaS founders: https://saasclub.io/email

Sarah Ahmad offered her first product for free during COVID. Nobody signed up. Her next company hit 10,000 customers and 8-figure ARR. The difference was SaaS product-market fit - validated before writing a single line of code. Sarah shares how she and her co-founder tested demand with a landing page in the YC community, signed 100 paying customers using Google Drive and a Stripe link, and built Stable into the leading AI-powered virtual mailbox for businesses. She also explains why the SEO playbook that built the company stopped working and what replaced it. Stable serves over 10,000 companies - from solopreneurs to enterprises like DoorDash, GitLab, and Realty Income - with 50-60 employees and operations across 20+ US locations. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 💖 Gearheart → Book a free consult and get the first 20 hours free 🔑 Key Lessons 🎯 Test SaaS product-market fit before writing code: Sarah's first startup Mistro failed because she built the full product before validating demand. With Stable, she validated with a landing page and manual operations - signing 100 paying customers before writing any software. 📉 Zero signups at zero price means no product-market fit: During COVID, Mistro couldn't get users even for free. That signal was clearer than any metric - if people won't use it for nothing, the problem isn't pricing, it's relevance. 🛠️ Use embarrassingly manual MVPs for market validation: Stable's first version was Google Drive, Zoom, and Stripe. Customers sent IDs via email. It was embarrassing, but it captured real demand while the team figured out what to build. 💰 Spend enough on paid ads to get real signal: Sarah's team spent only a few hundred dollars per week on ads - not enough to know if the channel worked. She now recommends spending thousands to saturate high-intent searches before optimizing. 🚀 Word of mouth scales when you solve a real pain point: Stable reached 1,000 customers before hiring anyone for growth, with a team of just 6-7 people at $1M ARR. Genuine product-market fit drove organic referrals without a marketing budget. 🤝 Compensate for a rough product with exceptional customer experience: Sarah and her co-founder personally onboarded every early customer via Zoom and handled all support. People forgive a rough product when you solve a real problem and show up for them. 🏢 Physical operations create a moat AI can't easily replicate: Stable's processing centers and logistics network across 20+ locations give it a defensibility layer that pure software companies don't have. Chapters Introduction First startup Mistro and why it failed Discovering the virtual mailbox opportunity Validating demand with a landing page The no-code MVP with Google Drive and Stripe How Stable differentiated from legacy incumbents Getting to 1,000 customers with a team of 6 The paid ads mistake most early founders make From manual operations to building software How AI is changing the product and industry Testing SaaS product-market fit versus building blind Shifting from product builder to CEO Resources Full show notes: https://saasclub.io/475 Join 5,000+ SaaS founders: https://saasclub.io/email

100 restaurants. Every order processed manually. Zero lines of code. Zhong Xu built Deliverect by turning integration partners into a SaaS distribution channel that scaled his product 10x faster than direct sales. Here's how he reached 80,000 restaurants and nearly $100M ARR through partnerships instead of cold outreach. Zhong shares why he launched with a Wizard of Oz MVP, how he convinced competing software companies to distribute his product, and why he opened 10 offices in a single quarter during COVID to block local incumbents before they could form. Plus: Zhong's take on why AI might turn his platform into commodity infrastructure - and his strategy to stay ahead. Deliverect connects delivery platforms like Uber Eats and DoorDash to restaurant systems across 50 countries. Zhong previously co-founded a restaurant software company that merged with Lightspeed, which IPO'd in 2019. This episode is brought to you by: 💖 Gearheart → Book a free consult and get the first 20 hours free 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🚀 Build a SaaS distribution channel through integration partnerships: Zhong partnered with 10+ software companies who each brought 100 restaurants monthly, reaching 80,000 locations across 50 countries faster than any direct sales team could. 🛠️ Launch with a Wizard of Oz MVP before writing code: Deliverect signed up 100 restaurants and manually processed every order before building anything, proving demand without wasting months on unvalidated features. 🤝 Attribute leads to distribution partners to avoid conflict: Zhong always credited partners for deals regardless of how customers arrived, eliminating the channel conflict that destroys most partnership-driven growth programs. ⚡ Enter every market before local incumbents emerge: Deliverect opened 10 offices in one quarter during COVID, betting that being number 1 or 2 early was cheaper than displacing entrenched local competitors later. 💰 Always charge early customers - free users give less feedback: Zhong found that non-paying customers feel guilty requesting help and stay silent, while even $50/month customers actively engage and provide honest product feedback. 🧠 Deep domain expertise creates unfair SaaS distribution advantages: Zhong's 12+ years in restaurant tech meant he had every partner CEO's phone number at launch, turning cold outreach into warm partnership conversations. 🎯 Build the intelligence layer before you become commodity infrastructure: Deliverect is racing to add AI-powered menu optimization and agent commerce because connectivity alone is replicable, but owning the restaurant intelligence layer is a defensible moat. Chapters Introduction What Deliverect does and how it works 80,000 restaurants and approaching $100M ARR How Zhong's father inspired his entrepreneurial journey Building one of the first tablet-based restaurant platforms Where the idea for Deliverect came from Why four co-founders and why distribution beats product The Wizard of Oz MVP - manual orders for 100 restaurants Resources Full show notes: https://saasclub.io/474 Join 5,000+ SaaS founders: https://saasclub.io/email

Joel Griffith's first customer paid $200 a month. His infrastructure cost $50. He was profitable from day one. But it took three years of nights and weekends before his bootstrapped SaaS hit $500K ARR. Then Google Cloud launched a competing product and a startup raised $60M to go after his market. His growth did not flinch - because eight years of content had built a bootstrapped SaaS moat that funding could not replicate. You will learn how to get first customers for a bootstrapped SaaS by teaching on GitHub and Stack Overflow, why a self-funded SaaS content engine that compounds over 8 years outlasts any viral spike, and how to scale a bootstrap operation beyond what you can handle solo by partnering instead of hiring. Joel Griffith is the founder of Browserless, a browser automation platform approaching $4M ARR with under 10 people. Joel is a jazz trumpet player turned engineer who went through five failed B2C ideas before building a profitable SaaS by solving his own pain as a developer. He has never raised a dollar. This episode is brought to you by: 🌎 ThreatLocker → Book a demo 🔑 Key Lessons 🎯 Solve your own pain for bootstrapped SaaS success: Joel failed at five B2C ideas before realizing the problems he understood best were engineering problems - leading to a business that was profitable from day one. 🤝 Get first customers by teaching, not pitching: Joel's first 10 customers came from answering GitHub issues and Stack Overflow questions about browser automation, building trust before mentioning his bootstrapped SaaS. 🚀 Build a content engine that compounds over years: Eight years of blog posts, forum answers, and open source contributions now drive almost all inbound for this self-funded SaaS at nearly $4M ARR. 🏢 Partner to fill skill gaps instead of struggling through them: At $60K MRR solo, Joel partnered with Polychrome for hiring, sales, and legal instead of trying to learn everything himself. 💰 Bootstrapped SaaS beats VC-backed competitors through relationships: When Google Cloud and a $60M-funded startup entered his space, Joel's growth did not change because customers valued direct access to a founder with domain expertise. Chapters Introduction What is Browserless and who is it for Business size: nearly $4M ARR, under 10 people Five failed B2C ideas before finding developer-market fit Three years as a side project before going full-time Running solo to $60K MRR as a one-person bootstrapped SaaS Getting the first 10 customers from GitHub and Stack Overflow First customer: $200/month, profitable from day one Content engine still driving almost all inbound at $4M ARR Partnering with Polychrome to handle operations Competing with a $60M-funded startup and Google Cloud How AI agents created new demand for browser automation Lightning round Resources Full show notes: https://saasclub.io/473 Join 5,000+ SaaS founders: https://saasclub.io/email