The Brutal Reality of Healthcare Tech Hiring in 2026

Maria Sukhareva | AI Realist: Part 3 -Horizons (Digital Twins, Open Weights and Why China Could Win AI | Maria Sukhareva)

Digital Twins, Open Weights and Why China Could Win AI | Maria Sukhareva Are "Digital Twins" the future of medicine, or just another marketing buzzword? In the final part of this deep-dive series, Stuart Miller and Maria Sukhareva (author of The AI Realist) break down the technical reality of world models and why true autonomous agents are farther away than you think. Stuart introduces his 4-Level Maturity Model for AI in healthcare, challenging the industry to move past "dumb dashboards" toward Star Trek-level diagnostics. Meanwhile, Maria explains why China's open-weight models and efficient architectures are currently outpacing the West. What You’ll Learn in This Episode: * The "World Model" Myth: Why models like Sora 2 don't actually understand physics—they just predict video sequences. * Stuart’s 4-Level Maturity Model: How to distinguish between simple data dashboards and a true Level 4 Medical Digital Twin. * The Human Complexity Problem: Why genetics and real-time biological changes make modeling a human body exponentially harder than modeling an engine. * Agentic AI vs. Reality: Why most "autonomous agents" today are just a system prompt connected to a SharePoint folder. * China's AI Advantage: The impact of Huawei chips, open-weight research, and the "Hive Mind" philosophy. * Practical Advice for Business Leaders: Why you should spend three days building your own agent before buying or selling an AI "employee". Episode Timestamps: * 0:00 – What is a true World Model? * 1:38 – Why Sora and video models struggle with real-world physics * 4:04 – Stuart's 4-Level Maturity Model for Digital Twins * 6:20 – The Complexity of Human Genetics: Why DNA isn't fixed * 9:34 – The Marketing Hype: Digital Twins vs. "Digital Randos" * 10:14 – Agentic AI: Reality Check on Automation Levels * 12:00 – The Ethics of Autonomous Agents in Clinical Care * 14:25 – Practical Tips for Sales, Marketing, and Decision Makers * 16:50 – Continual Learning: The next big step for Transformers * 18:13 – Why China is leading in efficient AI research * 21:17 – Conclusion: Staying Optimistic but Skeptical Connect with the AI Realists * Read Stuart Miller on Substack (Haverin): https://haverin.substack.com [ https://haverin.substack.com] * Subscribe to Maria Sukhareva (The AI Realist): https://airealist.substack.com [ https://airealist.substack.com] * Follow Maria Sukhareva on LinkedIn: https://www.linkedin.com/in/msukhareva/ [https://www.linkedin.com/in/msukhareva/ ] * Follow Stuart Miller on LinkedIn: https://www.linkedin.com/in/stuart-miller-haverin/ [https://www.linkedin.com/in/stuart-miller-haverin/]

Maria Sukhareva | AI Realist: Part 2 – Reality (AI 2026: GPT-5, Claude, AI Agents and ROI: Maria Sukhareva on What’s Actually Real)

The Reality of AI: GPT-5 "Flops," Vibe Coding, and the ROI Crisis Is the AI hype cycle finally crashing? In this episode of the Haverin About podcast, Stuart Miller sits down with AI expert and "Realist" author Maria Sukhareva to peel back the curtain on what’s actually happening in the world of Large Language Models (LLMs). From the perceived "flop" of GPT-5 to the rise of "Vibe Coding," we explore why many AI agents over-promise and under-deliver. If you are a business leader wondering where the Return on Investment (ROI) is for AI, or a developer trying to navigate the "snake eating its own tail" in generated code, this deep dive is for you. In This Episode, We Discuss: * The GPT-5 Turning Point: Why Maria believes GPT-5 was an incremental improvement at best and what it means for the "visionary" experts. * The ROI Gap: Why 25,000 "AI agents" at McKinsey might not be as impactful as they sound. * Vibe Coding & Productivity: How AI-assisted coding is the only "transformative" use case right now—and the risk of "boring" code and "purple websites". * Claude vs. ChatGPT: Why Stuart switched to Claude for long-form writing while keeping ChatGPT for research. * Digital Twins in Healthcare: Moving from engineering models to the "House" diagnostician concept for patient care. * The Small Model Debate: Why Maria is a "small model skeptic" but sees hope in Chinese innovations like Minimax. Timestamps: 0:00 – Introduction: The AI Hype Cycle vs. Reality 0:35 – Did GPT-5 Flop? The Shift to AI Skepticism 2:34 – Where is the ROI? Chatbots vs. Useful Agents 4:11 – The "Tulip Investment" Market of the 18th Century 6:19 – What is Vibe Coding? 8:53 – The Snake Eating Its Tail: Model Collapse in Code 11:27 – Why is the Internet Turning Purple? 13:12 – The 5-Model Website Building Experiment 16:18 – Why ChatGPT Leads to "Writing Hell" 18:12 – The Trouble with Prompt Engineering & Attention 20:15 – AI in Healthcare: Interrogating Medical Records 28:20 – The Future of Digital Twins & Master Diagnosticians 34:21 – Large vs. Small Language Models: The Generalization Problem 39:01 – Local AI: Running Minimax on your Desk Connect with Us: * Read Stuart Miller on Substack (Haverin): https://haverin.substack.com [https://haverin.substack.com] * Subscribe to Maria Sukhareva (The AI Realist): https://airealist.substack.com [https://airealist.substack.com] * Follow Maria Sukhareva on LinkedIn: https://www.linkedin.com/in/msukhareva/ [https://www.linkedin.com/in/msukhareva/] * Follow Stuart Miller on LinkedIn: https://www.linkedin.com/in/stuart-miller-haverin/ [https://www.linkedin.com/in/stuart-miller-haverin/] Keywords: GPT-5, AI Agents, Vibe Coding, AI ROI, LLM Comparison, Claude vs ChatGPT, Digital Twins Healthcare, Maria Sukhareva, Stuart Miller, AI Assisted Coding, Mixture of Experts, Small Language Models.

Maria Sukhareva | AI Realist: Part 1 – Origins (Before ChatGPT Made Everyone an AI Expert: Maria's Story)

The Journey of an AI Realist: From Arctic Linguistics to BMW & Siemens Is the current AI explosion just another hype cycle, or is there a deep technical foundation we’re missing? In Part 1 of this Haverin About special, Stuart Miller introduces Maria Sukhareva, the voice behind the popular AI Realist Substack. Maria doesn't just talk about AI—she has lived its evolution. From her early days studying linguistics in the Arctic Circle to building the first NLP departments at BMW and Siemens, Maria provides a "realist" perspective that cuts through the marketing fluff. If you want to understand how translating the Bible led to the creation of Large Language Models (LLMs), or why having 16 GPUs under your desk was once a "luxury," this episode is a must-watch. Key Insights in This Episode: * Linguistics vs. Hype: Why Maria’s background in translation and math makes her a skeptic of "overnight" AI experts. * The Evolution of Attention: How we moved from N-grams and LSTMs to the "Attention is All You Need" transformer era. * The BMW "Dark Corner": The hilarious story of how the NLP team was hidden inside the Blockchain department just to get access to GPUs. * The Cloud Cost Crisis: Why training AI models today costs thousands on the cloud compared to the "free" electricity of the past. * 10,000 Monkeys & Shakespeare: A technical but accessible breakdown of how LLMs use predictive loops to generate output. Timestamps: * 0:00 – Meet Maria Sukhareva: The AI Realist. * 0:54 – Growing up in the Arctic: -40°C and 52 days of vacation. * 2:08 – NLP vs. Neuro-Linguistic Programming: Clearing the confusion. * 4:10 – The Bible Corpus: How ancient texts founded modern Machine Translation. * 5:48 – Hidden in Blockchain: The early NLP days at BMW. * 8:36 – The GPU "License to Print Money": Nvidia and the cost of the Cloud. * 10:19 – From the "Dark Corner" to the Generative AI Spotlight at Siemens. * 13:34 – The Rise of "Instant" AI Experts vs. Technical Reality. * 15:07 – Predictive Loops: Are LLMs just 10,000 monkeys on typewriters?. * 17:06 – How to cut through the Marketing Fluff. Connect with the Guests: * Subscribe to Maria Sukhareva on Substack (The AI Realist): * Follow Maria on LinkedIn: * Follow Stuart Miller on LinkedIn: Keywords: AI Realist, Maria Sukhareva, Stuart Miller, Computational Linguistics, Natural Language Processing, BMW AI, Siemens AI, LLM History, Machine Translation, AI Hype Cycle, Transformer Models, VidIQ SEO.

How to Plan Your Best Sales Year in 2026 | Quota Strategy & SKO Survival

Want 2026 to be the best sales year of your career? Don't wait for it to be handed to you. In this episode, Stuart and Bethany break down exactly how to perform a professional reset for the new year. We cover the "sales math" needed to reverse-engineer your new quota, how to conduct deep-dive account research before you make a call, and the essential "Sales Kickoff (SKO) Survival Guide" to ensure you network effectively without becoming the topic of conversation the next morning. Whether you are an Account Executive or a Sales Leader, this practical guide will help you build the systems and processes to crush your number this year. In this episode, we discuss: 1. The Professional Reset: How to analyze your CRM data to find last year's wins and losses. 2. Path to Quota: Using the 3:1 pipeline ratio to calculate exactly what you need to close. 3. Account Intelligence: Why you need to read the bulletin boards and track LinkedIn activity. 4. SKO Rules: How to network with legal teams and why "nothing good happens after midnight." 5. Managing Up: Aligning your sales plan with your manager's P&L pressures. Resources & Links: 1. Connect with Stuart on LinkedIn: [Insert Link] 2. Connect with Bethany on LinkedIn: [Insert Link] 3. Haverin About Store (SKO Mugs): [Insert Link]

The Brutal Reality of Healthcare Tech Hiring in 2026

In this episode of Haverin About, Stuart and Bethany sit down with Brian Whitehill, Founder and CEO of AccuSource Group, to unpack what’s really happening in the healthcare technology job market — and why so many talented people are struggling to get hired. With more than 20 years of experience building go-to-market teams across health tech, Brian brings a refreshingly honest perspective on recruiting, hiring, and career survival. From the myth of the “Rolodex hire” to why LinkedIn’s Easy Apply has actually made job searching harder, this conversation pulls back the curtain on how hiring decisions truly get made. Together, they explore: 1. Why applying to hundreds of jobs often leads nowhere 2. How applicant tracking systems quietly screen out great candidates 3. The behavioral traits hiring managers say they want vs. what they actually hire for 4. Why “always be recruiting” applies to candidates, not just recruiters 5. Common mistakes companies make when hiring sales leaders 6. The difference between “nice-to-have” and “must-have” health tech solutions 7. How to stand out in an overcrowded, noisy job market This episode is a must-listen for anyone in healthcare technology — especially sales, leadership, and go-to-market professionals — seeking a realistic, practical roadmap to navigate their career in 2026 and beyond. ------------------------------------------------- 00:00 Introduction to Healthcare Technology Recruiting 01:54 Brian Whitehill's Journey in Healthcare Recruiting 03:05 Challenges in Recruiting Top Talent 07:00 Navigating the Job Market: Tips for Job Seekers 12:22 The Importance of Behavioral Qualities in Hiring 18:03 Hiring Sales Leaders: Common Mistakes and Insights 23:23 The Importance of Psychological Assessment in Hiring 25:35 Navigating Leadership Transitions in Growing Companies 28:08 Understanding the Founder’s Curse and Scaling Challenges 31:03 The Reality of Job Security in Sales 34:44 The Value of Networking and Always Being Prepared 36:37 Debunking the Rolodex Myth in Sales 39:44 The Shift from Nice-to-Have to Must-Have Solutions 42:00 Preparing for 2026: Key Considerations for Job Seekers 50:57 Three Golden Rules for Candidates in the Job Market