AI with Bry Podcast

In this episode of AI with Bry, we explore how artificial intelligence is reshaping healthcare delivery, clinician experience, and proactive care models through the lens of a clinician entrepreneur in geriatric and behavioral health.

AI is changing not just documentation and automation, but how care is delivered, how clinicians interact with patients, and how systems shift from reactive to proactive models. The challenge is not adoption—it is designing systems that reduce friction, improve outcomes, and keep patients and clinicians at the center.

This episode reframes AI through geriatric care, caregiver strain, administrative burden, and the opportunity to close gaps in continuity and access.

Guest: Joe Harrison

Joseph Harrison is a nurse practitioner, clinician entrepreneur, and Founder & CEO of Avail Healthcare, a clinician-built medical group delivering proactive in-home and virtual care for seniors and underserved adults.

He has experience in mobile care, Medicare Advantage, and geriatric mental health, leading teams supporting patients with dementia, depression, anxiety, and chronic conditions. He also serves as volunteer clinical faculty at UCSF.

At Avail Healthcare, he builds care models focused on aging in place and caregiver support, grounded in the quintuple aim: patient experience, provider experience, outcomes, equity, and sustainability.

We explore how AI is reshaping real-world healthcare delivery.

Joe explains that geriatric systems are structurally reactive, requiring patients to come to care instead of care coming to them. This drives higher cost, fragmentation, and missed early intervention.

AI enables a shift toward proactive care through remote monitoring, AI-assisted triage, and continuous communication, improving early detection and reducing emergency utilization.

A major theme is administrative burden. AI scribes now document visits in real time, reducing charting, improving accuracy, and giving clinicians more time with patients.

Joe notes that 15–20% of healthcare costs are administrative, creating major system-wide friction. AI reduces this load for both clinicians and patients.

We also explore the caregiver crisis, with 1 in 4 adults acting as caregivers. AI helps generate care plans, coordinate resources, and reduce coordination burden.

Another key insight is the rise of clinician entrepreneurs. AI tools now allow non-technical clinicians to design workflows, analyze data, and build systems using natural language interfaces.

Joe emphasizes that governance, infrastructure, and privacy must scale alongside innovation to protect patients and providers.

Core theme: AI should not only improve efficiency—it should improve human care.

What You’ll Learn:

• Why healthcare is reactive and how AI enables proactive care

• How AI transforms geriatric and behavioral health delivery

• Role of AI scribes in reducing burnout

• Why 15–20% of healthcare costs are administrative

• How AI improves documentation and billing accuracy

• The caregiver crisis and AI support systems

• How remote monitoring reduces ER visits

• Why clinician experience affects outcomes

• AI agents as virtual team members

• Rise of clinician entrepreneurs using AI tools

• Non-technical building via AI interfaces

• Importance of governance and privacy

• Alignment with the quintuple aim

Resources:

Avail Healthcare https://www.availhealthcare.co

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The future of healthcare AI will not be defined by automation alone, but by whether systems reduce friction, support clinicians, and bring care closer to those who need it most.

Learn, leverage, and lead.

In this episode of AI with Bry, we explore how artificial intelligence is reshaping healthcare, infrastructure thinking, and human-centered technology through the lens of a veteran technology leader and medtech advocate.

AI is transforming not just software, but how industries think about scale, resilience, and human experience. The real challenge is alignment between innovation, trust, and human need—not capability alone. This conversation reframes AI through decades of infrastructure leadership, personal medical recovery, and keeping humans at the center of advancement.

Guest: David Jones

David Jones is a veteran technology executive with 40+ years across telecommunications, regulatory systems, networking infrastructure, and large-scale data centers. He has built companies from startup stage to billion-dollar platforms through multiple private equity cycles and acquisitions.

After surviving a life-threatening infection resulting in the loss of his right hand and part of his forearm, he shifted into medtech innovation, prosthetics, and patient-centered systems. He now supports early-stage founders through the Pearl Innovation Center in Charlotte, focused on healthcare, AI, and human recovery.

His perspective connects enterprise infrastructure with lived patient experience in complex healthcare systems.

We explore decades of technology evolution and connect it to healthcare transformation and prosthetic innovation.

David emphasizes that leadership requires adaptability, trust, and aligning strategy with system design before scaling execution.

A key theme is that AI is accelerating all layers of technology but not always improving outcomes.

In healthcare, AI improves documentation, billing, and workflows but often shifts rather than reduces workload, increasing administrative burden.

Without intentional design, AI can optimize metrics instead of patient experience.

The conversation moves into prosthetics and medtech innovation. After losing his hand, David became deeply involved in prosthetic systems, sensor integration, and AI-enabled biomechanics.

Modern prosthetics are increasingly AI-driven systems using sensors, machine learning, and feedback loops to translate muscle signals into movement.

However, innovation is limited by cost, market size, and awareness of what is currently possible. Upper-limb prosthetics remain significantly underserved despite advances in robotics and wearables.

Through the Pearl Innovation Center, David supports ecosystem development for medtech founders navigating high complexity.

Core leadership insight: technology must serve human continuity, not replace it. Trust is built through listening, not automation.

AI accelerates systems, but it cannot replace empathy, context, or human attention.

What You’ll Learn:

• AI accelerates infrastructure but doesn’t guarantee better outcomes

• Leadership requires aligning strategy with system design

• Data centers function as utility ecosystems

• AI increases productivity but can increase clinical workload

• System design determines patient outcomes

• Prosthetics are becoming AI-driven biomechanical systems

• Upper-limb prosthetics remain underdeveloped

• Sensor fusion + ML reshape human-device interaction

• Market size influences medtech innovation

• Ecosystem support is critical for founders

• Trust remains foundational

Resources (full links available on show page):

Pearl Innovation Center (Charlotte MedTech Ecosystem)

Wexford Connect Labs

Watch & Follow AI with Bry (all platforms available here):

Full episodes: https://bry.net/ai

The future of AI in healthcare and infrastructure will not be defined by speed alone, but by how well we keep humans at the center of increasingly intelligent systems.

Learn, leverage, and lead.

In this episode of AI with Bry, we explore what happens when clinical expertise meets entrepreneurial execution in the age of AI.

AI is lowering the barrier to building, but access alone is not the advantage. The real edge comes from proximity to real problems and the willingness to solve them. This conversation reframes AI in healthcare not as external disruption, but as innovation from within—when clinicians closest to the pain points become the builders.

Guest: Daniela Dennis

Daniela Dennis is an emergency medicine resident and Founder of Payscope MD, an AI platform that helps physicians understand and optimize employment contracts. She also hosts the Resident Founder podcast and is author of What Med School Didn’t Teach Me About Money.

As a first-generation college graduate, she works at the intersection of medicine, entrepreneurship, and AI, focused on reducing information asymmetry and empowering physicians with tools they were never given in training. She is not theorizing about problems—she is building while living them.

We explore a major shift in healthcare: builders emerging from inside the system.

Daniela explains how Payscope MD originated from firsthand frustration with physician contracts—complex language, high legal costs, and lack of transparency at critical career moments. AI became the bridge to simplify and unlock understanding.

A key insight: AI is only as strong as the data it learns from. In healthcare, much of that data is fragmented or locked in systems and contracts, creating opportunity for domain experts to build better tools through real-world exposure.

We also discuss how AI is already transforming clinical workflows—documentation, dictation, radiology, and patient monitoring. While efficiency gains matter, the biggest impact is time: giving clinicians back attention for patients.

Daniela emphasizes that AI is not replacing physicians—it is augmenting them. But it introduces new challenges as patients increasingly rely on AI-generated medical information, increasing the need for clinician interpretation and guidance.

On the builder side, the barrier to entry has dropped significantly. With modern AI tools, clinicians without technical backgrounds can now prototype, validate, and launch products. This is enabling a new wave of physician entrepreneurs.

We also explore how physicians must shift from passive adoption to active participation—building tools, shaping workflows, and educating patients. Leadership in healthcare is expanding beyond clinical care into creation and communication.

AI in healthcare will not be defined only by institutions or external startups. It will be shaped by clinicians who choose to engage, build, and lead.

What You’ll Learn:

• AI lowers the barrier to building, not the need for insight

• Clinicians are becoming builders within the system

• Healthcare data gaps create opportunity for domain experts

• AI improves workflows and returns time to patients

• Patients are influenced by AI-generated medical information

• Human oversight remains critical in medical decisions

• Entrepreneurship is now more accessible to physicians

• AI tools enable rapid prototyping (“vibe coding”)

• Trust and credibility are evolving in healthcare

• Leadership now includes building and educating with AI

Resources:

Payscope MD: https://www.getpacescope.com

Resident Founder Podcast

LinkedIn: https://www.linkedin.com

Instagram: https://www.instagram.com

Watch & Follow AI with Bry:

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The future belongs to those who build from lived experience. Learn, leverage, and lead.

In this episode of AI with Bry, we explore how artificial intelligence is reshaping healthcare through the lens of nurse practitioner entrepreneurs.

AI adoption in healthcare is not just about technology. It is about empowering the people closest to patients with the tools, systems, and leverage needed to deliver better care. This conversation reframes AI as a grassroots transformation driven by practitioners building sustainable, patient-centered businesses.

Guest: Lynn Rapsilber

Lynn Rapsilber is Co-Founder and CEO of the National Nurse Practitioner Entrepreneur Network (NNPEN), a community that provides nurse practitioners with business education, advocacy, and resources often missing from clinical training.

With extensive experience in patient care and healthcare leadership, Lynn helps NPs build, scale, and sustain independent practices. Her work bridges entrepreneurship, policy, and care delivery, helping clinicians step into ownership and reshape healthcare from within.

We discuss a major challenge in healthcare today: the people closest to patients are often the least equipped with modern business tools.

Lynn explains how nurse practitioners are becoming entrepreneurs without formal business training and how organizations like NNPEN help close that gap. AI is now accelerating that evolution.

One of the biggest barriers to adoption is fear. Clinicians worry about complexity, cost, and losing the human connection with patients. Lynn reframes AI as a support system, not a replacement.

We explore how AI is already improving healthcare through virtual assistants, front-desk automation, clinical decision support, documentation, billing workflows, and AI-powered medical scribes. These tools reduce administrative burdens and allow providers to focus more on patient care.

Lynn also shares how AI supports personalized care through real-time protocols, remote monitoring, and data-driven insights that enable earlier intervention and better chronic disease management.

On the business side, AI helps solo practitioners operate with the capabilities of larger organizations through automation, reporting, and operational efficiencies that support sustainable growth.

We also discuss trust, privacy, data ownership, education, and leadership. Lynn highlights how NNPEN is creating a collaborative ecosystem where practitioners share resources, gain visibility, and increase collective influence.

AI is not replacing healthcare providers. It is giving them the leverage to reclaim their role.

What You'll Learn:

• AI adoption starts with education and trust

• NPs are building businesses without formal business training

• AI reduces administrative burden and restores patient focus

• Medical scribes provide rapid ROI

• Personalized care improves through data and insights

• Solo practices can scale with AI-powered systems

• Cost barriers are decreasing

• Data ownership and privacy matter

• Ecosystem thinking creates leverage

• Healthcare transformation will happen from the ground up

Resources:

NNPEN: https://www.nnpen.org

NP Practice Directory: https://www.npdirectory.org

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The future of healthcare will not be built solely in hospitals or boardrooms. It will be shaped by empowered practitioners using technology to deliver better, more human care.

Learn, leverage, and lead.

In this episode of AI with Bry, we explore leadership at the intersection of artificial intelligence and revenue growth.

AI is accelerating execution across every function. But speed without structure creates chaos. The real work for leaders is not just adopting tools—it is defining processes, embedding repeatable systems, and ensuring that human judgment drives meaningful outcomes as machines multiply capacity.

This conversation reframes AI adoption as a people and execution challenge, not just a technical one.

Guest Introduction

Rich Makover

Full Name: Rich Makover

Rich is a Fractional Chief Revenue Officer and Managing Partner at Tech CXO. He works with companies across consumer goods, beauty, jewelry, and technology to build scalable revenue engines. With decades of experience at KPMG, Avon, and Citizens Watch Group, Rich now embeds investor-grade repeatable execution into growth-stage and PE-backed companies. He is also a certified executive coach and former D1 Penn State lacrosse captain, translating high-performing team principles from the locker room to the boardroom.

His perspective matters because he operates at the intersection of strategy, people, and process. Rich helps organizations turn founder intuition into disciplined, repeatable revenue execution while leveraging AI to multiply team effectiveness.

Core Conversation Summary

We unpacked a central tension facing revenue organizations today: speed versus adoption.

Rich emphasized that AI is not about replacing relationships—it’s about enabling teams to perform at scale with clarity, preparation, and confidence. When adoption is structured into workflows, AI improves meeting prep, lead qualification, proposal creation, and handoffs to customer success. Without intentional integration, tools fail to stick.

One of the biggest challenges in AI adoption is critical mass. Early adoption by a few key team members drives momentum, while isolated usage leads to stalled implementations. Leadership through example—walking the walk—drives adoption and builds trust.

We explored repeatable systems versus accidental success. Embedding AI into defined processes increases usage, accountability, and measurable results. Rich shared real-world examples where AI increased meetings, streamlined proposals, and freed leaders to focus on coaching talent rather than manual tasks.

On leadership, Rich highlighted that AI accelerates execution but does not replace judgment. Experienced leaders use AI to amplify their perspective, speed planning, and enhance team performance. Younger team members may over-rely on AI, so balancing automation with critical thinking is essential.

Ultimately, AI adoption on the revenue side is about process, culture, and leadership, not just shiny tools. The leaders who succeed are those who structure systems that allow teams to perform repeatedly under pressure.

What You Will Learn in This Episode

• AI Adoption Is A People And Execution Challenge
• Critical Mass, Not Perfection, Drives Adoption
• Repeatable Systems Outperform Accidental Success
• AI Enhances Preparation, Proposal, And Hand-Off Processes
• Leadership By Example Accelerates Tool Integration
• Experienced Judgment Multiplies AI’s Value
• Balancing AI Usage With Critical Thinking Avoids Risk
• Structured Workflows Increase Stickiness And ROI
• AI Reveals and Reinforces Team Culture, It Doesn’t Replace It
• Collaboration And Coaching Drive Sustainable Revenue Growth

Resources, Tools and Platforms Mentioned

Tech CXO

https://www.techcxo.com

LinkedIn

https://www.linkedin.com/in/rich-makover

Fractional Edge Newsletter

Link in show notes

Watch and Follow AI with Bry

Full episodes and show notes

https://bry.net/ai

YouTube

https://www.youtube.com/@aiwithbry

Instagram

https://www.instagram.com/aiwithbry

Facebook

https://www.facebook.com/profile.php?id=61575757332333

TikTok

https://www.tiktok.com/@aiwithbry

The future belongs to leaders who structure systems, multiply their team’s capacity, and embed execution into culture.

In this episode of AI with Bry, we explore leadership at the intersection of artificial intelligence and moral architecture.

AI is accelerating execution across every function, but speed without intention creates fragility. The challenge for leaders is not adopting tools—it is defining values, building governance into systems, and ensuring human judgment remains central as machines gain leverage. This reframes AI adoption as a people and philosophy challenge, not just technical transformation.

Guest: Cristina DiGiacomo

Cristina DiGiacomo is Founder of 10P1, Chief Philosophy Officer, and member of the AI Council at C-Suite Network. With 25 years in technology and digital strategy, she embeds ethical architecture directly into AI systems through leadership alignment, moral frameworks, and executable code-level constraints.

She works at the intersection of human values and machine capability, designing systems ethics upstream before optimization pressure defines outcomes.

We explore the tension of speed vs governance. Cristina argues these are not opposites—upfront clarity accelerates execution by reducing noise, risk, and misalignment.

A key misconception is that AI safety can be added after deployment. In reality, values are always embedded in systems, intentionally or not. Without ethical guardrails, optimization pressure fills the gap.

We also discuss open-source AI systems and constraint layers. Even when safeguards exist, they can be overridden—making the human decision a matter of character and shifting hiring toward moral intelligence.

Cristina introduces systems ethics: embedding checkpoints, principles, and moral architecture directly into workflows as accelerators, not bureaucracy.

AI also expands human capability. It strengthens synthesis, pattern recognition, and structured thinking. It does not replace judgment—it expands perspective.

We explore how AI improves decision-making through better options, counterarguments, and scenario planning, leading to clearer thinking rather than more noise.

On leadership, Cristina reframes disruption: healthy change surfaces new leaders, capabilities, and collaboration. The key question is not whether change creates friction, but whether leaders interpret it as failure or growth.

AI is not coming for us—we are shaping how it is deployed. Collaboration, not fear-driven competition, will define outcomes.

This episode helps leaders embed ethical clarity into execution and lead through technological change without fear-based narratives.

What You’ll Learn:

• AI adoption is a people + philosophy challenge

• Speed and governance reinforce each other

• Systems ethics must be embedded upstream

• Optimization pressure defines outcomes if ignored

• Moral intelligence matters in hiring

• Constraint layers require human character

• AI expands decision-making capacity

• Information synthesis is a key leverage point

• Organizational friction can signal healthy evolution

• Collaboration drives resilience

Resources:

10P1: https://10p1.co

C-Suite Network: https://c-suitenetwork.com

LinkedIn: https://www.linkedin.com/in/cristinadigiacomo/

Watch & Follow AI with Bry:

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YouTube: https://www.youtube.com/@aiwithbry

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The future belongs to leaders who embed values into execution. Learn, leverage, and lead.

In this episode of AI with Bry, we explore how leaders move beyond AI experimentation and into real execution, especially in high stakes environments like technology diligence, private equity, and mergers and acquisitions. AI is no longer a novelty inside organizations. It is a force multiplier. But like any powerful tool, it requires judgment, context, and experience to generate real value.

I am joined by Greg Smith, a fractional CTO and technology strategist who serves as Managing Partner in the Product and Technology Practice at TechCXO. Greg leads fractional CTO, CIO, CPO, and CISO engagements while advising private equity and venture capital firms on technology diligence. With decades of experience as an operator, founder, and executive, Greg brings a practical lens to AI adoption, leadership, and organizational transformation.

Greg and I unpack what organizations are still misunderstanding about AI. We discuss why top down AI mandates often fail and why grassroots adoption inside teams produces more durable results. We explore how AI is reshaping the tech diligence lifecycle by accelerating information gathering, improving insight extraction, and compressing reporting timelines, while still requiring seasoned judgment in the middle of the process. AI can surface patterns and highlight risks, but it cannot replace wisdom, contextual interpretation, or accountability.

We also dive into how investors are using AI to evaluate companies and why overreliance on automated reports creates false confidence. AI can make technology assessments feel accessible, but it cannot fully interpret architectural nuance, team capability, product maturity, or leadership readiness. We discuss the shift from entry level analytical roles toward higher leverage, product minded technical leadership and how development bottlenecks are moving upstream into product strategy and planning. As AI accelerates execution, clarity of thinking becomes the new constraint.

Whether you are a founder, executive, private equity partner, or technology leader, this episode will help you rethink how AI fits into diligence, innovation, and long term value creation. The mindset shift is clear. AI is not a replacement for leadership. It is an amplifier of it.

What You Will Learn in This Episode

Why Grassroots AI Adoption Outperforms Top Down Mandates

How AI Accelerates Tech Diligence Without Replacing Judgment

Why Information Gathering And Reporting Are Ideal AI Use Cases

How Investors Risk False Confidence From Automated AI Reports

Why Wisdom And Context Still Outperform Pure Prediction Engines

How AI Is Compressing Development Timelines And Shifting Bottlenecks

Why Developers Must Become More Product Minded To Stay Relevant

How To Evaluate AI Claims Inside Portfolio Companies

Why Continuous Innovation Becomes The New Competitive Moat

How Leaders Can Remove Fear And Drive Responsible AI Adoption

Connect with Greg Smith

TechCXO https://www.techcxo.com

LinkedIn https://www.linkedin.com/in/fractionalcto/

Resources, Tools and Platforms Mentioned

AI Models and Assistants

ChatGPT https://chat.openai.com

Claude by Anthropic https://www.anthropic.com/claude

Research and Knowledge Tools

NotebookLM by Google https://notebooklm.google.com

Development or Execution Tools

OpenAI API https://platform.openai.com

Microsoft Azure AI https://azure.microsoft.com/en-us/products/ai-services

Industry or Concept References

Tech Diligence

Fractional CTO Leadership

SOC 2 Compliance

Watch and Follow AI with Bry

Full episodes and show notes https://bry.net/ai

YouTube https://www.youtube.com/@aiwithbry

Instagram https://www.instagram.com/@aiwithbry

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The future belongs to leaders who move from insight to execution. Learn, leverage, and lead.

In this episode of AI with Bry, we explore how AI is fundamentally reshaping research, product strategy, and execution. The conversation moves beyond surface level experimentation and into what happens when AI shifts from being an efficiency tool to becoming a true force multiplier. Organizations are no longer asking whether they should use AI. The real question is how fast they can integrate it without losing clarity, culture, or control.

I am joined by Danny Mendoza and the team from Escape Velocity, a group working at the intersection of innovation, capital, and execution. Alongside Danny are Michael Heiser and Elijah Gutman, who bring deep experience in product strategy, AI systems, and venture acceleration. Together, they are helping founders move from idea to execution faster than ever before.

We unpack what organizations are misunderstanding about AI today, why overwhelm is often the first barrier to adoption, and how leaders can shift from analysis paralysis to rapid experimentation. This episode dives into the recent leap from basic automation to agentic systems that can pilot software, build product roadmaps, and execute research workflows autonomously.

We also explore how AI is compressing development timelines from months to weeks, replacing traditional research teams, reshaping capital deployment in investment banking, and redefining what talent looks like. This is not about replacing people. It is about amplifying execution and unlocking new levels of speed and access that were previously reserved for massive enterprise budgets.

Whether you are a founder, executive, investor, or builder, this episode will challenge you to rethink how you plan, execute, and lead in a world where AI is replacing research and accelerating every stage of the product lifecycle.

What You Will Learn in This Episode

• Why AI overwhelm is the first barrier organizations must overcome
• How NotebookLM can instantly accelerate research and learning
• What changed with Claude Code and why it signals a major shift
• What Model Context Protocol means for product strategy
• How AI can build multi year product roadmaps autonomously
• Why research heavy industries like investment banking are ripe for AI acceleration
• How AI is democratizing access to enterprise level consulting
• Why development timelines are compressing dramatically
• How leaders can reduce AI theater and focus on real execution
• Why talent definitions are shifting in the AI era
• How to rethink planning in a world where execution happens in days

Connect with Danny Mendoza and Escape Velocity Team

• Escape Velocity: https://www.escapevelocity.us/
• Danny Mendoza LinkedIn: https://www.linkedin.com/in/danny-mendoza-hx/
• Michael Heiser LinkedIn: https://www.linkedin.com/in/michael-heiser-45458b13b/
• Elijah Gutman LinkedIn: https://www.linkedin.com/in/elijah-gutman/

Resources, Tools and Platforms Mentioned

AI Models and Platforms

• ChatGPT https://chat.openai.com
• Claude https://claude.ai

Research and Learning

• NotebookLM https://notebooklm.google.com

AI Development and Agentic Tools

• OpenClaw https://openclaw.ai/
• ElevenLabs https://elevenlabs.io
• Claude Code https://www.anthropic.com/claude

Meeting and Knowledge Tools

• Granola https://granola.ai
• Otter https://otter.ai
• Fireflies https://fireflies.ai

Organizations Mentioned

• Escape Velocity https://www.escapevelocity.us/
• Umergence https://www.umergence.com/
• 1 Million Cups https://www.1millioncups.com
• Y Combinator https://www.ycombinator.com
• 3M https://www.3m.com

Watch and Follow AI with Bry

• Full episodes and show notes https://bry.net/ai
• YouTube https://www.youtube.com/@aiwithbry
• Instagram https://www.instagram.com/aiwithbry
• Facebook https://www.facebook.com/profile.php?id=61575757332333
• TikTok https://www.tiktok.com/@aiwithbry

The future belongs to the leaders who move from research to execution. Learn, leverage, and lead.

In this episode of AI with Bry, we explore the widening gap between strategy and execution as AI accelerates how work gets done across organizations. While AI promises speed and efficiency, leaders are increasingly wrestling with a deeper question. Is moving faster actually making work better, or simply making everything louder, busier, and more disposable? This conversation examines how leaders can use AI to execute with clarity without surrendering judgment, creativity, or trust.

I am joined by Michael Baer, fractional Chief Marketing Officer and Chief Growth Officer at TechCXO. Michael brings an operator first perspective shaped by decades of experience helping leadership teams translate strategy into real world outcomes. Rather than treating AI as a buzzword, Michael focuses on how leaders can use it responsibly to support thinking, decision making, and execution without replacing the human work that actually drives value.

Michael and I unpack why AI’s first answer is rarely the best answer and why strong leadership still requires probing, challenging, and refining outputs rather than accepting speed at face value. We discuss how AI systems are designed to please users, why repeated prompting matters, and why good work sometimes requires intentional inefficiency. From writing and creativity to marketing performance, leadership decision making, and healthcare adoption, this episode highlights where AI helps and where leaders must slow down.

We also explore how AI is reshaping creative workflows through image generation, curriculum design, and coaching frameworks. Michael shares how he uses AI to build structured programs, workshops, and strategic exercises that would previously have required large teams or months of work. At the same time, we confront the risks of AI generated content saturation, declining trust, and the growing need for leaders who can think beyond automation.

Whether you are a founder, executive, marketer, or healthcare leader navigating AI adoption, this episode will help you rethink AI as an execution amplifier rather than a strategy replacement, and why leadership judgment has never mattered more.

What You Will Learn in This Episode

• Why AI’s first response is rarely the right one
• Why repeated prompting and human guidance still matter
• How efficiency can undermine creativity if left unchecked
• Why good writing and original thinking stand out more than ever
• How AI is changing marketing performance and audience trust
• Why leaders must separate value creation from AI hype
• How AI can support coaching, workshops, and curriculum design
• Why healthcare adoption requires trust, not just automation
• How AI impacts jobs while increasing demand for strategic leadership
• Why judgment, not speed, is the real leadership advantage
• 
  

Resources, Tools and Platforms Mentioned

AI Models and Platforms

• ChatGPT https://chat.openai.com
• OpenAI https://openai.com
• Claude https://claude.ai
• Anthropic https://www.anthropic.com

Creative and Media Platforms

• Spotify https://www.spotify.com
• Nano Bananas https://nanobanana.io/

Organizations and Technology References

• TechCXO https://www.techcxo.com
• Xerox
• IBM Selectric Typewriter

Watch and Follow AI with Bry

• Full episodes and show notes https://bry.net/ai
• YouTube https://www.youtube.com/@aiwithbry
• Instagram https://www.instagram.com/aiwithbry
• Facebook https://www.facebook.com/profile.php?id=61575757332333
• TikTok https://www.tiktok.com/@aiwithbry

Remember, the future does not wait. Learn, leverage, and lead.

In this episode of AI with Bry, we explore how leaders can turn AI from a noisy buzzword into real operational leverage. As AI accelerates product development, compresses timelines, and reshapes how teams work, the difference between success and chaos comes down to leadership, structure, and clarity. AI does not replace judgment. It amplifies it. And without the right controls, it can just as easily magnify confusion as it can performance.

I am joined by Paul King, Principal at Tech CXO, where he works hands on with founders, CEOs, and executive teams to bring operational discipline, scalable systems, and execution clarity to growing organizations. Paul has spent his career helping companies move from ambition to reality, making him uniquely positioned to cut through AI hype and focus on what actually works inside real teams.

Paul and I unpack what leaders often misunderstand about large language models, why AI is not “thinking” but still incredibly powerful, and why context and control matter more than speed. We explore real examples of hallucinations, fabricated features, and misleading outputs, not as reasons to avoid AI, but as reasons leaders must stay engaged and intentional. This conversation dives into how AI fits into product development, architecture decisions, testing, and quality assurance, and why the role of developers is shifting from writing code to guiding, validating, and structuring systems.

We also discuss how effective AI leverage goes far beyond small productivity gains. From autonomous coding agents and parallel development to better visibility for executives and stronger accountability across teams, this episode shows how AI can transform how organizations operate when leaders rethink processes instead of just installing tools. Paul shares why companies that refuse to engage with AI will fall behind, and why those that only use it as a chatbot are leaving massive value on the table.

Whether you are a founder, executive, or technology leader trying to navigate AI adoption without losing control, this episode will help you think more clearly about leverage, leadership, and how to build organizations that can move faster without breaking themselves in the process.

What You Will Learn in This Episode

• Why AI is not thinking and why that distinction matters
• How hallucinations happen and how leaders should manage them
• Why context and framing determine AI output quality
• How AI is changing the role of developers and engineers
• Why leverage is about systems, not shortcuts
• How leaders can gain real visibility into product development
• Why junior and senior talent must learn AI differently
• How autonomous agents accelerate development cycles
• Why small productivity gains are not real AI leverage
• How leadership decisions determine whether AI creates growth or chaos

Resources, Tools and Platforms Mentioned

AI Models and Platforms

• ChatGPT https://chat.openai.com
• Claude https://claude.ai
• Gemini https://gemini.google.com

Developer and Coding Tools

• Claude Code https://www.anthropic.com/news/claude-code
• GitHub Copilot https://github.com/features/copilot
• Cursor https://www.cursor.sh

Advisory and Leadership

• Tech CXO https://techcxo.com

Watch and Follow AI with Bry

• Full episodes and show notes https://bry.net/ai
• YouTube https://www.youtube.com/@aiwithbry
• Instagram https://www.instagram.com/aiwithbry
• Facebook https://www.facebook.com/profile.php?id=61575757332333
• TikTok https://www.tiktok.com/@aiwithbry

Remember, the tools will keep changing. Strong leadership never goes out of style. Learn, leverage, and lead.