The Killer Use Case Podcast

Hunter Jensen with Greg Moser and Scott Turman on Building AI Tools, Context, and Scaling Teams

1 h 6 min · 22 de abr de 2026
Portada del episodio Hunter Jensen with Greg Moser and Scott Turman on Building AI Tools, Context, and Scaling Teams

Descripción

In this wide-ranging technical discussion, founders and operators across consulting, logistics, and software development compare how agentic AI is reshaping the way they build software, run operations, and structure daily work. The conversation explores a shift from traditional SaaS tools to rapidly built internal applications powered by LLMs, including ephemeral apps, workflow automation, and agent-driven DevOps pipelines. A major theme is the emergence of persistent memory systems and context management strategies that allow AI agents to operate more effectively over time. The participants also examine the tradeoffs of speed versus control, including security isolation, prompt injection risks, and the growing need for production hardening as “vibe-coded” tools move toward real-world deployment. Along the way, they highlight both the productivity gains and psychological intensity of working in highly agentic, always-on AI environments. Takeaways * Agentic AI has made it possible to build functional internal tools in hours instead of weeks or months. * Many SaaS products are being replaced by quickly built, purpose-specific internal applications. * Latency in LLM interactions is a major bottleneck, driving demand for faster, more local, or embedded solutions. * Speech-to-text integrated directly into workflows can dramatically increase interaction speed with AI systems. * Persistent memory is a key unlock, enabling agents to retain and reuse context across sessions. * Structuring memory into topics or organized files improves reliability and reduces context confusion. * Running multiple subagents in parallel enables high throughput but increases cognitive and coordination load. * Slack-based or chat-based environments are emerging as operational layers for agent collaboration. * Security isolation is critical, especially around credentials, email access, and prompt injection risks. * “Vibe coding” accelerates prototyping but creates a growing need for dedicated production hardening and QA processes. Today's guests can be found at: Greg Moser: Website: https://www.shipcalm.com/ LinkedIn: https://www.linkedin.com/in/gregmoser/ Scott Turman: Website: https://scottturman.com/, https://brightray.com/ LinkedIn: https://www.linkedin.com/in/scottturman/ IMDb: https://www.imdb.com/name/nm14602682/ Your host, Hunter Jensen, can be found online at: Website: https://www.barefootsolutions.com/ LinkedIn:https://www.linkedin.com/in/hunterjensen/ Keywords agentic AI, large language models, persistent memory, context management, speech to text, workflow automation, subagents, DevOps automation, SaaS disruption, internal tools, software development, orchestration, Slack workflows, AI collaboration, security isolation, prompt injection, cloud deployment, Azure, Google Cloud, QA testing, product hardening, vibe coding, automation systems, latency optimization, enterprise AI systems

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6 episodios

episode Greg Grand on AI Sales Coaching, Roleplay Training, and Building Better Sales Teams artwork

Greg Grand on AI Sales Coaching, Roleplay Training, and Building Better Sales Teams

In this episode, Greg Grand, CEO of G Squared Advisors, shares how he integrates AI into sales leadership, coaching, and business operations. Drawing on more than three decades of sales experience, Greg explains how his approach evolved from chasing new AI tools to focusing on solving specific business problems. The conversation explores practical AI applications in sales training, role play coaching, meeting analysis, hiring, workflow automation, and productivity. Greg also discusses the future of AI in sales, why consultative selling remains irreplaceable, and how sales professionals can start using AI today to save time, improve performance, and stay competitive in a rapidly changing market. Takeaways * Greg Grand transitioned into fractional sales leadership after seeing small and mid-sized businesses struggle to scale without experienced sales management. * His breakthrough with AI came when he stopped chasing tools and started identifying business problems first. * AI serves as a brainstorming partner, helping solo consultants and business leaders generate new ideas and challenge assumptions. * Sales role play training powered by AI can provide personalized coaching, grading, and feedback at scale. * AI-driven interview analysis helps evaluate candidates for cultural fit, sales skills, and role suitability. * Meeting transcription and automated summaries save significant administrative time for sales leaders and consultants. * AI is most effective today in preparation, research, training, documentation, and workflow optimization rather than replacing complex sales conversations. * High-value consultative sales skills remain difficult to automate because trust, relationships, and human judgment drive buying decisions. * Entry-level sales development and transactional sales roles face greater disruption from AI than senior consultative sales positions. * The best way to start with AI is to dedicate regular learning time, follow trusted AI educators, and look for opportunities to save time in daily work activities. Today's guest, Greg Grand, can be found at: Website: https://gsquaredadvisors.com/ LinkedIn: https://www.linkedin.com/in/greggrand/ Your host, Hunter Jensen, can be found online at: Website: https://www.barefootsolutions.com/ LinkedIn:https://www.linkedin.com/in/hunterjensen/ Keywords Artificial Intelligence, AI, Sales Leadership, Fractional CRO, Revenue Growth, Sales Coaching, Sales Training, Role Play Training, Sales Enablement, Business Development, Prospecting, CRM Management, Workflow Automation, Meeting Transcripts, Zoom AI, Custom GPTs, Gemini, Claude, Perplexity, ChatHub, AI Agents, Make Automation, Sales Process, Consultative Selling, Sales Strategy, Candidate Assessment, Hiring, Revenue Operations, Productivity, Knowledge Work, Sales Playbooks, Pipeline Management, Lead Generation, B2B Sales, Sales Technology, Business Scaling, Time Management, AI Adoption, Voice AI, Sales Performance, Customer Discovery, Objection Handling, Coaching Frameworks, Automation Tools, LinkedIn Prospecting, Dux-Soup, Sales Operations, Human Connection, Trust Building, Revenue Leadership, AI Workflows, Digital Transformation

Ayer37 min
episode Stephen Arthur on AI Tutors, Student Feedback, and the Future of Higher Education artwork

Stephen Arthur on AI Tutors, Student Feedback, and the Future of Higher Education

In this episode, Hunter Jensen speaks with Stephen Arthur, Director of AI and Analytics at ECPI University, about how artificial intelligence is reshaping higher education. Stephen explains how ECPI moved from early caution around generative AI to building practical AI systems for students, faculty, and administrators. The conversation explores conversational assignments, AI governance policies, curriculum challenges, student adoption, analytics, and the long-term vision of creating AI-powered academic assistants that can support every part of a student’s educational journey. They also discuss the future of work, the impact of AI on careers and universities, and why adaptability and AI literacy will become critical skills for the next generation Takeaways * ECPI University began its AI journey after the release of ChatGPT 3.5 and gradually expanded adoption as model reliability improved. * The university partnered with OpenAI to provide enterprise AI access for faculty and staff before expanding student-facing tools. * ECPI introduced “conversational assignments,” where students interact with AI tutors instead of submitting traditional essays. * AI-driven assignments provide students with real-time feedback and increase engagement with course material. * The university developed a four-tier AI governance framework that defines how students may use AI in coursework. * Stephen Arthur believes AI literacy and prompt engineering will become foundational workforce skills across industries. * ECPI is building AI tools that integrate with Canvas and other student systems to automate academic support and administrative tasks. * AI-powered semantic analysis is helping the university process large amounts of student feedback and operational data more effectively. * The discussion highlights growing concerns around AI-generated job applications, privacy, surveillance, and the future of knowledge work. * Stephen predicts higher education will split into two models: elite intellectual institutions and career-focused schools centered on workforce skills and AI adoption. Today's guest, Stephen Arthur, can be found at: LinkedIn: https://www.linkedin.com/in/stephen-arthur/ Your host, Hunter Jensen, can be found online at: Website: https://www.barefootsolutions.com/ LinkedIn:https://www.linkedin.com/in/hunterjensen/ Keywords Artificial Intelligence, Generative AI, Higher Education, AI Governance, Conversational Assignments, Student Learning, AI Tutoring, OpenAI, ChatGPT, Claude, Canvas LMS, Analytics, Workforce Development, Career Colleges, ECPI University, AI Literacy, Prompt Engineering, Student Engagement, Curriculum Development, Semantic Search, Automation, AI Tools, Knowledge Work, Future of Work, Robotics, AI Strategy, Educational Technology, Cybersecurity Education, Nursing Education, Adaptive Learning, Large Language Models, AI Adoption, Operational Efficiency, Data Analysis, Personalized Learning, AI Assistants, Student Information Systems, Machine Learning, Academic Innovation, AI Ethics, Workforce Skills, AI Integration, Learning Management Systems, Educational Innovation

20 de may de 202657 min
episode Patryk Laurent on Privacy-Safe Video AI and Turning Cameras into Smart Sensors artwork

Patryk Laurent on Privacy-Safe Video AI and Turning Cameras into Smart Sensors

In this conversation, Patryk Laurent, CEO of Scenera, discusses how the company uses edge-based video AI to improve safety, security, and building operations in commercial real estate. He explains how Scenera turns existing cameras into intelligent sensors that can detect events such as falls, loitering, fence climbing, unattended objects, and spills without relying on constant video streaming to the cloud. The discussion also covers edge computing, privacy, AI model tuning, event-based foundational models, low-energy AI, neuromorphic hardware, and the future of smarter, more private IoT systems. Takeaways * Scenera provides a cloud-managed edge AI platform for safety, security, and building intelligence. * The system uses existing cameras to detect important events and send real-time alerts. * Edge processing helps reduce the need to stream full video feeds to the cloud. * Video AI can identify events such as falls, loitering, fence climbing, and unattended objects. * Pose detection can help identify human actions while protecting personal identity. * Scenera uses analytics to find trends across time, weather, traffic, and building activity. * The company fine-tunes models for specific buildings to improve accuracy. * Scenera is developing an event-based foundational model for reasoning about activity in physical spaces. * Low-energy AI and neuromorphic hardware could move more intelligence directly into cameras. * Privacy will be central to the future of camera-based sensors and IoT systems. Today's guest, Patryk Laurent, can be found at: Website: https://pakl.net/ LinkedIn: https://www.linkedin.com/in/patryk-laurent Your host, Hunter Jensen, can be found online at: Website: https://www.barefootsolutions.com/ LinkedIn: https://www.linkedin.com/in/hunterjensen/ Keywords Edge AI, Video AI, Computer Vision, Smart Cameras, Building Operations, Commercial Real Estate, Safety, Security, Fall Detection, Loitering Detection, Object Detection, Pose Detection, Data Lake, Edge Computing, Cloud Managed Edge Platform, Azure, IoT Edge, MLflow, Foundational Models, Event-Based AI, Neuromorphic Hardware, Low-Energy AI, Internet of Things, Privacy, Smart Buildings

6 de may de 202639 min
episode Hunter Jensen with Greg Moser and Scott Turman on Building AI Tools, Context, and Scaling Teams artwork

Hunter Jensen with Greg Moser and Scott Turman on Building AI Tools, Context, and Scaling Teams

In this wide-ranging technical discussion, founders and operators across consulting, logistics, and software development compare how agentic AI is reshaping the way they build software, run operations, and structure daily work. The conversation explores a shift from traditional SaaS tools to rapidly built internal applications powered by LLMs, including ephemeral apps, workflow automation, and agent-driven DevOps pipelines. A major theme is the emergence of persistent memory systems and context management strategies that allow AI agents to operate more effectively over time. The participants also examine the tradeoffs of speed versus control, including security isolation, prompt injection risks, and the growing need for production hardening as “vibe-coded” tools move toward real-world deployment. Along the way, they highlight both the productivity gains and psychological intensity of working in highly agentic, always-on AI environments. Takeaways * Agentic AI has made it possible to build functional internal tools in hours instead of weeks or months. * Many SaaS products are being replaced by quickly built, purpose-specific internal applications. * Latency in LLM interactions is a major bottleneck, driving demand for faster, more local, or embedded solutions. * Speech-to-text integrated directly into workflows can dramatically increase interaction speed with AI systems. * Persistent memory is a key unlock, enabling agents to retain and reuse context across sessions. * Structuring memory into topics or organized files improves reliability and reduces context confusion. * Running multiple subagents in parallel enables high throughput but increases cognitive and coordination load. * Slack-based or chat-based environments are emerging as operational layers for agent collaboration. * Security isolation is critical, especially around credentials, email access, and prompt injection risks. * “Vibe coding” accelerates prototyping but creates a growing need for dedicated production hardening and QA processes. Today's guests can be found at: Greg Moser: Website: https://www.shipcalm.com/ LinkedIn: https://www.linkedin.com/in/gregmoser/ Scott Turman: Website: https://scottturman.com/, https://brightray.com/ LinkedIn: https://www.linkedin.com/in/scottturman/ IMDb: https://www.imdb.com/name/nm14602682/ Your host, Hunter Jensen, can be found online at: Website: https://www.barefootsolutions.com/ LinkedIn:https://www.linkedin.com/in/hunterjensen/ Keywords agentic AI, large language models, persistent memory, context management, speech to text, workflow automation, subagents, DevOps automation, SaaS disruption, internal tools, software development, orchestration, Slack workflows, AI collaboration, security isolation, prompt injection, cloud deployment, Azure, Google Cloud, QA testing, product hardening, vibe coding, automation systems, latency optimization, enterprise AI systems

22 de abr de 20261 h 6 min
episode Scott Turman on AI-Driven Outreach, Authenticity, and Scaling Publishing Without Slop artwork

Scott Turman on AI-Driven Outreach, Authenticity, and Scaling Publishing Without Slop

In this episode, Scott Turman, CEO of BrightRay Publishing, shares his journey as a serial entrepreneur and explains how his company blends traditional publishing with modern AI-driven workflows. The conversation explores how large language models are transforming sales, marketing, and research processes, enabling massive scale while simultaneously creating challenges around trust and authenticity. Scott outlines how BrightRay uses AI for data aggregation, outreach personalization, and media targeting, while deliberately rejecting AI-generated writing in favor of human-authored content. The discussion highlights a growing tension between automation and authenticity, the saturation of digital channels, and why returning to high-touch strategies like direct mail and real human interaction may be the key to standing out in an AI-saturated world. Takeaways * BrightRay Publishing was born from a collaborative book-writing process that evolved into a scalable business model. * AI has significantly improved research and personalization through automated dossier generation and data aggregation. * Tasks that once required teams of researchers can now be scaled to thousands of prospects per day using AI workflows. * Overuse of AI in outreach has led to declining trust, as highly personalized messages are often assumed to be automated. * Saturation of digital channels is pushing marketers back toward traditional methods like direct mail and physical books. * BrightRay enforces a strict no-AI policy for writing book content, prioritizing human authenticity and narrative quality. * AI struggles with long-form storytelling, making human-written content more valuable in publishing. * Advanced AI agents are transforming PR workflows by matching book themes with relevant journalists at scale. * Media outreach success increasingly depends on combining AI insights with real human interaction and relationship-building. * The future of business communication will hinge on authenticity, as audiences and platforms push back against AI-generated “slop.” Today's guest, Scott Turman, can be found at: Website: https://scottturman.com/, https://brightray.com/ LinkedIn: https://www.linkedin.com/in/scottturman/ IMDb: https://www.imdb.com/name/nm14602682/ Your host, Hunter Jensen, can be found online at: Website: https://www.barefootsolutions.com/ LinkedIn:https://www.linkedin.com/in/hunterjensen/ Keywords AI, large language models, publishing, book writing, marketing strategy, personalization, automation, authenticity, direct mail, PR strategy, media outreach, content creation, workflow automation, data research, sales outreach, digital marketing, AI tools, human connection

8 de abr de 202636 min