AI Automation Podcast

From Idea to SaaS in 10 Days Using AI – Fast-Building, Validation, and Scaling Smart

In this episode, Sean Weisbrot — entrepreneur, global traveler, and host of the We Live to Build podcast — shares how he used AI to go from idea to post-MVP SaaS product in under two weeks. Sean dives into his entrepreneurial journey, from his early years in China to building a multimillion-dollar blockchain consultancy, then launching (and losing) a tech startup. Now, he’s back with a new venture: an AI-powered expense management platform built almost entirely using Lovable and ChatGPT. We unpack how he validated the idea, rapidly built and iterated on the product, and scoped a roadmap that includes QuickBooks integration, subscription management, and AI-driven vendor negotiations. Sean also reveals his go-to-market strategy—built around his podcast guest network of 7- and 8-figure business owners—and his philosophy on pricing and scaling in a SaaS world reshaped by AI. Timestamps:  00:00 – Using ChatGPT to shape a go-to-market strategy 01:00 – Sean's journey from China to blockchain to AI 02:30 – Lessons from a $15M consulting business 04:00 – How the podcast became a product research engine 05:40 – Validating a SaaS idea with 7-figure founders 07:00 – Why time and cost-saving are today’s real value drivers 09:00 – Building an AI-powered expense management tool in 10 days 12:00 – Real-time walkthrough of the product 17:00 – Budget tracking, need-based categorization, and action plans 20:00 – QuickBooks integration and AI-assisted development 24:00 – Go-to-market via podcast relationships 26:00 – Pricing strategy and future feature tiers 28:00 – AI’s role in evolving SaaS and future vendor management Key Points: * Rapid SaaS development: Sean built a working expense management platform in ~10 days using AI tools like Lovable and ChatGPT. * Deep validation: His podcast interviews with high-revenue founders doubled as user research and lead generation. * Unique positioning: Aimed at bootstrapped businesses doing $5M–$30M/year—not venture-backed startups. * AI-first roadmap: Current features include budgeting, categorization, and forecasting; future plans include fraud detection, subscription/vendor management, and AI-led procurement. * Lean go-to-market: Focuses on building trust and cutting sales cycles by nurturing guest relationships into client relationships. Notable Quotes: “The AI can code as fast as I can think.”  “If you’re building SaaS and don’t include AI, you’re already behind.”  “My guests are my go-to-market.” Guest Links: * Website: https://www.welivetobuild.com [https://www.welivetobuild.com] * YouTube: https://www.youtube.com/channel/UCRxmA5Mnz8sWx5mYD6l5HMA [https://www.youtube.com/channel/UCRxmA5Mnz8sWx5mYD6l5HMA] * LinkedIn: https://www.linkedin.com/in/seanweisbrot [https://www.linkedin.com/in/seanweisbrot]

AI-Driven CRM: Revolutionizing No-Code Automation

In this episode of the AI Automation Podcast, host Michael is joined by Matthias Frank — automation strategist and CRM workflow expert. Together, they dive into the powerful world of CRM automations and how AI is reshaping the speed and strategy of lead conversion. Matthias reveals a plug-and-play automation system that any business with a structured CRM can implement—regardless of platform. Whether you're using Notion, ClickUp, Airtable, or another system, these insights will help you enrich leads, respond instantly, and build smarter workflows. The conversation also explores the future of no-code tools, the declining uniqueness of platforms like Zapier and Make, and why understanding your manual process is key before scaling with AI. Timestamps:  00:00 – The struggle of no-code automation tools in the AI era 00:35 – Introduction to Matthias Frank 01:30 – Why CRMs need automation today 03:00 – Tool-agnostic workflows: Notion, ClickUp, Airtable 04:45 – The power of AI-built custom workflows 06:00 – Blueprinting and transferring automations 07:55 – API-first thinking and tool lock-in myths 09:00 – Real-world lead enrichment and email automation 11:45 – Using AI to qualify leads and draft personalized replies 14:00 – Automating follow-ups with AI agents 15:30 – Speed-to-response: Why it drives $180K+ in business 16:40 – AI’s role in identifying sales-ready leads 17:50 – Final thoughts: Build manual first, then automate Key Points: * How AI is disrupting the no-code automation space * Building workflows that adapt to any CRM or platform * AI-enhanced lead enrichment and auto-replies * Matthias' plug-and-play automation framework for early-stage founders * Real examples of AI increasing sales velocity and closing rate Top Quote: "Don’t use a chainsaw if you can’t swing an axe." – Matthias Frank Guest Links: 1. https://matthiasfrank.de/ 2. https://www.linkedin.com/in/matthiasfrankprofile/ 3. https://twitter.com/MFreihaendig 4. https://www.youtube.com/channel/UCW305WqEev0aujh9Aq-eNSQ

The Zapier-Powered Trash Empire: Building a Business with Automation

In this episode of the AI Automation Podcast, host Michael Greenberg sits down with Spencer Scott, also known as Twitter's Favorite Trash Man, to explore how he built an ultra-efficient, AI-powered trash collection business from the ground up. With nearly everything running through Zapier, ChatGPT, and Google Sheets, Spencer reveals the exact automations and growth strategies that allowed him to scale Lone Star Trash with almost no customer support team. From capturing lost leads via missed-call follow-ups to creating a CRM inside Google Sheets that dynamically pulls Stripe billing data, this episode is a blueprint for automating a small business into a revenue machine. Spencer’s unique combo of blue-collar grit and no-code systems thinking is a masterclass for indie hackers, SaaS founders, and operators alike. Timestamps: (0:00) - Why Zapier replaced customer support  (0:20) - The #1 thing your funnel must capture: email  (0:45) - Intro to Spencer Scott & Lone Star Trash  (1:11) - From Facebook post to $15K in 10 days  (2:05) - Operating a trash business: bins, trucks, margins  (3:05) - Adding automations early: RingCentral & Zapier  (4:00) - Choosing the right phone system via Zapier compatibility  (5:15) - How one missed-call text flow drove $50K in revenue  (6:40) - Anatomy of the missed-call Zap  (7:30) - SMS follow-up converts elderly callers into paid customers  (8:15) - Why they use incognito mode for manual signups  (9:00) - Building a signup flow with ChatGPT  (10:40) - Why capturing email first is the golden rule  (11:35) - The full funnel: email → address → bins → merch → notes  (12:45) - Stripe Checkout + custom thank you page  (13:20) - Referral engine: 60% of growth from viral shares  (14:10) - Their CRM: a real-time, Stripe-powered Google Sheet  (15:00) - How Apps Script flags active vs. inactive customers  (16:00) - Auto-routing & GPS tagging for trash pickups  (17:00) - The follow-up flow for abandoned signups  (18:20) - Personalized subject lines = sky-high email open rates  (19:00) - No dev background? No problem: Spencer's no-code mindset  (20:00) - Why Google Sheets is better than most CRMs for small biz  (21:00) - Spencer’s software stack: Zapier, ChatGPT, IGPT, Cursor (22:00) - $50K ARR from one missed-call Zap Key Points: * Automated Missed Call Follow-Up: Spencer’s Zapier flow catches missed calls, sends an immediate personalized text, and links to a signup page—resulting in 7–15 new customers/month. * No-Code Signup Funnel via ChatGPT: Email-first logic, Stripe integration, merch add-ons, and dynamic thank-you pages. Each step saves data for later follow-up if the user bounces. * Referral-Driven Growth: A single CTA on the thank-you page drives users to a referral system offering t-shirts and free trash service. This generated over 60% of their customers early on. * CRM in Google Sheets: With Apps Script and Stripe APIs, Spencer tracks active billing, flags unpaid users, and triggers routing software—all from a spreadsheet. * Email Sequences for Abandoned Signups: Zapier checks if someone signed up within 3 days. If not, it sends a 3-part email drip—complete with personalized subject lines featuring their home address. * Routing & GPS Integration: Customer routes are auto-generated via tags in the CRM and sent to drivers. The system also captures GPS timestamps to prove pickups. Notable Quotes: “There’s only one thing you need from a signup form: the email. Everything else is optional. Without the email, you’re empty-handed.” – Spencer Scott “I built this whole thing in Zapier and Google Sheets. We don’t really have support – the automation is the support.” “Google Sheets is the best software ever made. Fight me.” Guest Links: Website: * https://www.hellomedian.com/ Twitter: * https://twitter.com/AKASpencerScott LinkedIn: * https://www.linkedin.com/in/scott2ss Host Links: Website: * https://www.3rdbrain.co/ * http://gentof.tech/ LinkedIn: * https://www.linkedin.com/in/gentoftech/

The End of Human Research? AI's Takeover of Podcast Prep

In this episode, we explore two innovative agentic research tools tailored for specific business processes. The first tool focuses on podcast guest research, allowing hosts to gather detailed information about potential guests using their social media profiles. The host demonstrates the simplicity of the tool by inputting their own details and showcases how it generates comprehensive insights, including past podcast appearances and relevant topics. The second tool is a journalistic research bot designed to answer the fundamental questions of who, what, when, where, why, and how. Both tools are built and demoed by the sponsoring team at Third Brain, offering exciting new ways to enhance research efficiency for podcast creators and journalists alike. Tune in to learn how these tools can transform your research process! Timestamps: (0:00) - Intro (0:10) - Overview of Agentic Research Tools (0:45) - Podcast Guest Research Tool Demo (1:18) - Analyzing the Generated Content (3:45) - Journalistic Research Bot Overview (4:21) - Clarifying Questions and Report Generation (6:02) - Report Format and Citations Discussion Check it out on Youtube: https://youtu.be/7xqgKLa8QaQ Host Socials: https://www.3rdbrain.co/ https://www.linkedin.com/in/gentoftech/ http://gentof.tech/

The AI Liberation: Freeing Brilliant Minds from Mundane Tasks

In this episode, I chat with Matthias, a Notion consultant and automation enthusiast. We delve into the innovative workflows Matthias has created within Notion to streamline the management of investors and reporting partners. Matthias shares his journey from being a lawyer to discovering the creative potential of Notion, likening it to playing with Lego building blocks. He discusses how this powerful software provided him with the agency to build and create, ultimately leading him to turn his passion into a business. Tune in to explore the intersection of Notion and automation, and gain insights on enhancing your project management strategies. Timestamps: (0:00) - Intro (0:10) - Matthias's Journey to Notion Consulting (1:00) - The Magic of Notion and Agency (2:15) - Building Automations for Asset Managers (4:44) - Organizing Data in Notion (7:04) - Layering Automation and AI (12:29) - The Power of Structured Data and Reporting Key Points * Introduction & Background: * Matthias Frank, a Notion consultant and automation enthusiast, explains how he transformed his career by leveraging Notion. * His journey began when he discovered that Notion’s “building blocks” offered him the agency to create structured systems without requiring a technical background. * Two-Phase Approach to Data Management: * Phase 1: Data Organization * Start by manually organizing raw data (documents, meeting transcripts, reports) into Notion’s databases. * Emphasize creating a clear structure using Notion’s database building blocks. * Phase 2: Automation & AI Integration * Once data is structured, integrate automation tools (like Circleback with webhooks) to process transcripts, extract key information, and generate reports. * Automate repetitive tasks such as meeting note summarization and action item extraction, saving considerable manual effort. * Automation Tools & Techniques: * Use meeting recorders (e.g., Circleback, Fireflies) with robust API/webhook support for seamless data extraction. * Apply Notion AI to enhance searchability and generate Q&A insights from enriched, structured data. * Combine qualitative (narrative meeting notes) with quantitative data (financials, KPIs) for comprehensive reports. * Benefits of the Process: * Frees up time by automating mundane data entry and summarization tasks, allowing teams to focus on high-value activities. * Ensures clarity and accessibility of critical information, leading to better-informed decisions and faster company progress. * Highlights the importance of first achieving quality structured data before layering in complex AI automations. Insights * Validation Before Full Automation: * Starting with manual processes allows teams to understand and fine-tune their data structure before committing to full-scale automation. * Integration Flexibility: * Leveraging tools with open APIs (like Circleback) is essential for creating flexible, robust workflows. * This approach can be scaled and tailored based on specific business needs (e.g., investor reporting or internal meetings). * Empowering Non-Technical Users: * Notion democratizes database creation, making it accessible for non-coders to build systems that previously required specialized knowledge. * Combining AI with Structured Data: * AI is most effective when it has access to well-organized, high-quality data. * The real value of AI comes from its ability to enhance data analytics and decision-making rather than generating creative ideas from scratch. Host Socials: https://www.3rdbrain.co/ https://www.linkedin.com/in/gentoftech/ http://gentof.tech/ Guest Socials: https://matthiasfrank.de/ https://www.linkedin.com/in/matthiasfrankprofile/ [https://www.linkedin.com/in/matthiasfrankprofile/] https://twitter.com/MFreihaendig https://www.youtube.com/channel/UCW305WqEev0aujh9Aq-eNSQ