Most companies are experimenting with AI. The leaders who win are rebuilding around it.In this episode, Chris Daigle sits down with Jason Eubanks, Co-Founder and CEO of Aurasell AI, to explore why incremental AI experiments aren’t enough—and why go-to-market teams must shift to an AI-native operating model. Jason explains why simply plugging AI into legacy systems won’t change your productivity model, and why companies that fully embrace intelligent automation now will create an advantage competitors won’t be able to close.They discuss how AI-native architecture can double productivity, eliminate CRM busywork, and cut onboarding time for sales teams by 50%. From removing copy-and-paste workflows to automating outreach, enrichment, and follow-up, Jason outlines what happens when AI doesn’t just provide insights—but executes. He also introduces Aurasell’s new GTM operating system that sits on top of existing CRMs like Salesforce and HubSpot, plus an agent builder that enables powerful AI-driven workflows through simple natural language prompts.If you’re looking to unlock real productivity gains—not just incremental improvements—this episode outlines what that shift actually requires.🔎 Find Out More About Jason EubanksLinkedIn: https://www.linkedin.com/in/jasoneubanks/🌐 Learn More About Aurasell AIhttps://aurasell.ai🛠 AI Tools and Resources MentionedAurasell GTM Operating Systemhttps://www.aurasell.aiChat Gpt https://chatgpt.com/ Salesforcehttps://www.salesforce.com/ HubSpothttps://www.hubspot.com Chapters:(00:00) Introduction(01:17) What “AI-native” really means (beyond chat wrappers)(03:02) The productivity gap: why incremental AI adoption fails(06:45) Urgency explained: first movers and 2–3x productivity gains(10:08) Fixing the broken B2B sales productivity model(12:27) Case study: carving out teams to go all-in on AI(15:07) The AI-native GTM platform and unified customer journey(21:26) Cutting onboarding time by 50% with intelligent automation(26:10) Eliminating sales busywork and manual CRM toil(28:46) Agentic workflows: natural language → automated execution