AI Automation Podcast

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 managementKey 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.comYouTube: https://www.youtube.com/channel/UCRxmA5Mnz8sWx5mYD6l5HMALinkedIn: https://www.linkedin.com/in/seanweisbrot

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 automateKey Points:How AI is disrupting the no-code automation spaceBuilding workflows that adapt to any CRM or platformAI-enhanced lead enrichment and auto-repliesMatthias' plug-and-play automation framework for early-stage foundersReal examples of AI increasing sales velocity and closing rateTop Quote: "Don’t use a chainsaw if you can’t swing an axe." – Matthias FrankGuest Links: 1. https://matthiasfrank.de/2. https://www.linkedin.com/in/matthiasfrankprofile/3. https://twitter.com/MFreihaendig4. https://www.youtube.com/channel/UCW305WqEev0aujh9Aq-eNSQ

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 ZapKey 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/AKASpencerScottLinkedIn:https://www.linkedin.com/in/scott2ssHost Links:Website:https://www.3rdbrain.co/http://gentof.tech/LinkedIn:https://www.linkedin.com/in/gentoftech/

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 DiscussionCheck it out on Youtube: https://youtu.be/7xqgKLa8QaQHost Socials:https://www.3rdbrain.co/https://www.linkedin.com/in/gentoftech/http://gentof.tech/

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 ReportingKey PointsIntroduction & 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 OrganizationStart 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 IntegrationOnce 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.InsightsValidation 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://twitter.com/MFreihaendighttps://www.youtube.com/channel/UCW305WqEev0aujh9Aq-eNSQ

In this episode, we welcome Malcolm Peace to discuss the implementation of AI and automation in unique business contexts. He shares insights from his experiences, highlighting not just the technological advancements but also the accompanying HR issues that arise from these integrations. The conversation explores the intricacies of protecting business interests while navigating the complexities of human resources. Malcolm's case study provides a fresh perspective, showcasing how AI is being utilized in ways that differ from the typical digital agency narratives. Join us as we delve into the fascinating intersection of technology and human factors in today's business landscape.Timestamps:(2:12) - Blue collar industrial business challenges.(4:46) - Data management challenges in manufacturing.(10:35) - Cost breakdown in business.(12:50) - ERP system implementation challenges.(16:05) - System adoption in businesses.(18:48) - AI issues vs. HR issues.(24:02) - Different viewpoints in organization.(25:05) - Employee utilization and performance analysis.(28:36) - Employee accountability in project management.(32:28) - Mobile task management efficiency.(35:10) - Automation and AI in business.(40:11) - Accountability through data-driven decisions.Key Topics & Highlights:Company Background:SortRight International: A long-established manufacturer specializing in shrimp sorting machinery.The business’s 73-year history sets the stage for a discussion on adapting traditional practices to modern challenges.The Digital Transformation Journey:Transitioning from manual tracking using Google Sheets and sticky notes to implementing a custom-built ERP system.Leveraging tools like Airtable and Slack to communicate ideas, exchange feedback, and build a scalable digital platform.Data-Driven Decision Making:The importance of capturing accurate production, labor, and inventory data to drive real-time decisions.Developing a “SortRight App” that ties together production, HR accountability, and inventory management.HR and Operational Challenges:Balancing AI automation with the human element, including addressing HR issues that arise from changes in workflow and accountability.The evolution of roles and responsibilities, with a focus on optimizing supervisor and employee performance through clear metrics.Implementation and Iteration:The iterative process: testing new systems, refining processes, and ensuring continuous improvement in operations.Real-life examples of challenges—such as miscommunications on task assignments—and how they are tackled with improved data and oversight.Future Outlook:Ongoing projects include integrating advanced timesheet management and further automation to drive efficiency.Reflections on the potential of digital transformation to protect and grow traditional blue-collar businesses for decades to come.Guest Socials:Malcom Peace on X: https://x.com/peace_malcolmLinkedIn - https://www.linkedin.com/in/malcolmpeaceWebsite - https://tsetserra.com/

In this episode, I chat with Brandon White, co-author of the Digital Operations Playbook, about a transformative automation case study from one of their past clients. The client, a large multi-location franchise owner, successfully automated 90% of their finance and accounting operations—saving over 30 hours per week of manual labor.We break down how AI-driven automation replaced a cumbersome manual process that required employees to email cash receipt images, transcribe data into spreadsheets, and manually input it into QuickBooks. By implementing a streamlined AI-powered workflow using OCR, Google Drive, and automation tools, the business drastically reduced operational inefficiencies, eliminated the need for monthly "Receipt Tuesdays," and saw a significant financial impact.Timestamps:(00:00) – Introduction to the episode(00:45) – Case study overview: Franchise owner with 50+ locations(02:30) – The finance department's manual process before automation(05:15) – Breakdown of inefficiencies and pain points(07:30) – Implementing AI automation with OCR and Google Drive(09:15) – Financial impact: Saving 30+ hours per week(10:30) – Cost of automation vs. savingsKey Points:The Problem: A disorganized, labor-intensive cash reconciliation process involving emailed receipts, manual data entry, and time-consuming audits.The Solution: AI-powered automation with a unified email inbox, OCR technology, and automated data extraction and input into QuickBooks.The Impact: A full-time employee's workload was eliminated, allowing finance staff to focus on more strategic tasks.Cost vs. Savings: The AI automation cost was minimal (under $20 in operating costs) but resulted in tens of thousands of dollars in annual savings.Scalability: This solution is applicable to multi-location retail, QSR (Quick Serve Restaurants), and other businesses struggling with finance and accounting automation.Notable Quotes:"This automation effectively replaced over 30 hours of manual labor per week." – Brandon C. White"Once we implemented this, the head of finance filled our backlog with more automation requests." – Michael"For businesses at scale, reconciling daily transactions manually is unsustainable. AI automation changes everything." – Brandon C. WhiteGuest Socials:Brandon C. White on X: @BrandonCWhiteTrevally - Your Contacts in the Cloud - https://trevally.io/LinkedIn: Brandon White - https://www.linkedin.com/in/brandonwhite

In this episode, Will Green, founder of CopyRoad and direct response marketing expert, shares how AI is transforming copywriting workflows. Will discusses his custom automation system that streamlines proofreading and editing, making writers significantly more efficient while saving both time and money. If you’re in the business of creating content, this episode breaks down why AI-driven editing might soon replace traditional copy editors.Timestamps:00:00 – Introduction and Will Green’s background02:10 – How AI boosts writing productivity07:25 – Automating proofreading and editing workflows12:45 – Cost savings: AI vs. human copy editors18:30 – Custom-built AI tools for direct response marketing23:00 – Will AI fully replace copy editors?Key Points:AI efficiency: Automating proofreading can cut turnaround time from days to minutes.Cost comparison: AI editing tools can save thousands of dollars per project.Direct response focus: Will’s automation system follows strict copywriting rules to drive sales effectively.Custom workflows: Insight into Will’s personalized editing tools for faster content production.Notable Quotes:“AI won’t replace writers yet—but it can make them 50 times more efficient.” – Will Green“I’ve saved up to $15,000 per copy package just by automating editing.” – Will Green“This automation catches 95% of mistakes human editors still miss.” – Will GreenGuest Socials:🌐 CopyRoad - https://www.copyroad.com/🐦 Will Green on X (Twitter) - https://x.com/thecopyroad 💼 Will Green on LinkedIn - https://www.linkedin.com/in/copyroad/