"In the rush to engineer cutting-edge AI, don't forget the user; it's not just about creating technology for the sake of it, but about how it genuinely improves our work experience."

Michael Machado, who led the development of Salesforce Anywhere, Salesforce AI research, and  Einstein Voice at Salesforce, now leads DevRev with a modern approach to product management that fuses design, engineering, and AI to shape the future of work. We discuss Agent OS (AI-powered operating systems designed for autonomous agents) and how to bring customers and product developers closer.

This episode is perfect for startup founders, product managers, AI enthusiasts, and anyone looking to modernize business workflows. It’s especially useful for teams aiming to integrate AI into their products, streamline customer support, and adopt a design-first approach for a competitive edge. If you’re curious about the future of work and how cutting-edge platforms like DevRev are shaping it, this one’s for you.

Connect with Michael Machado:

LinkedIn
2022 San Francisco CTO Summit: 
Michael Machado on Legacy Support Tools vs AI
Michael's Journey from CRM > Dev CRM
Effortless 2023 Conference 

DevRev:

Linkedin and Website
Instagram
Youtube

References:

Unreasonable Hospitality
Einstein Voice

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Is the future of healthcare being shaped without doctors? Dr. Sven Jungmann dives into the growing role of AI in medicine, the ethical dilemmas, and why many physicians feel left behind in this tech revolution.

We explore the reality of physician shortages, an aging population, and how AI could ease the pressure—but only if doctors get involved. With many eager to adopt AI, the barriers are glaring: no access to resources, poor collaboration with developers, and a widening knowledge gap.

Who’s driving this change—tech or medicine? And what happens when ethical considerations fall through the cracks? Dr. Jungmann and Tina Yazdi dig into the messy intersection of healthcare and AI, exposing both the promise and pitfalls.

Key points:

• How AI is reshaping healthcare workflows and redefining the roles of doctors and nurses.
• The disconnect between physicians and developers that’s slowing innovation.
• Why ethical AI development demands healthcare professional involvement.
• The opportunities AI presents for reducing burnout, boosting efficiency, and improving care.

Will AI be the saving grace of healthcare—or just another tech-driven misstep? Tune in to rethink the future of medicine.

Connect with Dr. Sven Jungmann

• Website
• Linkedin
• Instagram

Published Work

• Books by Dr Jungmann
• Sifted
• Medical Literature

Episode References:

• Design Thinking
• Biomedical Informatics
• Algorithmic Bias (Clinical)
• Fosbury Flop
• Breath Analysis Technology
• Physician Availability Crisis

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Are traditional healthcare models ready for the disruptive innovations of entrepreneurs like Dr. Sven Jungmann?

With extensive medical expertise and entrepreneurial vision, Dr. Jungmann co-founded Halitus to develop state-of-the-art breath analysis devices. Using AI/ML and digital health, Dr. Jungmann is bridging healthcare and tech.

We cover:

• Dr. Sven Jungmann's shift from traditional medicine to entrepreneurship
• How Halitus is building scalable breath analysis by combining AI/ML with medical hardware
• The need for multidisciplinary healthcare innovation to reduce risk
• How data and technology help healthcare become more patient-centric and efficient
• Unexpected fundraising challenges for hardware-based innovation
• "Gold standards" for AI-driven diagnostics
• Who will and won't benefit from AI
• Regulatory and market challenges facing healthcare innovators

Connect with Dr. Sven Jungmann

• Website
• Linkedin
• Instagram

Halitus and more

• Halitus
• Speedinvest
• capitalmind investec
• Wellster Healthtech
• CASC

Published Work

• FightBack NOW
• Beyond the Bedside: A doctor’s guide for careers outside the hospital
• Wie gesund wollen wir sein?
• Sifted
• Medical Literature

Episode References:

• Forward + Adrian Aoun
• Dr. Wiktor Szczudlinski
• Galen on olfaction
• CT Scans for Lung Disease

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

'AI-First' has replaced 'Data-Driven'. AI technology must be integrated into systems, teams, tools, and products to survive. But what about the legal and compliance?

Ramakrishnan has been at the forefront of AI adoption for enterprises, having held executive and advisory roles at Element AI and Perpetua Labs. Currently, he's co-founder and CEO at Armilla AI, which is pioneering insurance for organizations that train, develop and deploy AI systems:

• The real decision makers behind AI initiatives
• Top-down regulations vs. bottom-up ethical AI
• Black box AI systems + best practices for model testing
• "Ground truths" for compliant and ethical systems
• Existing frameworks for compliance
• Contingencies and repairing trust

More:

• Karthik Ramakrishnan
• AI Maturity Framework
• Leadership in Insurance Podcast
• Navigating Code Quirks & Corporate Quandaries
• 2024 Predictions: Regulation, Risk, and Innovation

References:

• Lawsuits - Air Canada, Cigna, State Farm
• AI is changing cybersecurity
• Red teaming: Guide to testing AI models
• Kathy Baxter + Salesforce: AI Ethics Maturity Model
• EU AI Act
• Automation In History
• Chief AI Officer
• Existing Standards
  • NIST
  • ISO/IEC 42001
• Responsible AI (RAI)
  • McKinsey

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Join us to dive into the world of AI infrastructure  with Wes Cummins, CEO and Chairman of Applied Digital. Prior to founding the company he also founded and led 272 Capital LP and led B. Riley Asset Management as President. 

Applied Digital (Nasdaq: APLD) designs, develops and operates next-generation datacenters across North America to provide digital infrastructure solutions to the rapidly growing high performance computing (HPC) industry.

Discover the distinctions between traditional and high-power density data centers, and learn how competition for electricity is shaping the industry.

Explore the diverse customer personas in the AI infrastructure market, from hyperscalers to Gen.AI startups, and gain insights into the future of compute for AI. Wes also shares valuable tips for companies venturing into GPU compute and finding the right partners. 

• We Cover:
  • Why do AI infrastructure demands necessitate high-power density data centers, and how do they differ from traditional ones?
  • What's driving the escalating demand for compute power in the AI market, and how does it fuel competition for electricity?
  • Who are the key customer personas shaping the AI infrastructure landscape, from hyperscalers to Gen.AI startups and enterprise giants?
  • What are the diverse purchasing options for AI infrastructure, ranging from ownership to cloud services, and what choices exist for GPU compute?
  • What are the common pitfalls to avoid when venturing into GPU compute, such as accessibility issues and hardware management challenges?
  • How can you effectively locate GPU compute companies, whether through online searches or exploring smaller vendors alongside major cloud providers?
  • What does the future hold for data centers as the gatekeepers of AI compute deployments, and why is there a growing focus on their power consumption?

Connect with Wes Cummins here:

Linkedin 

Applied Digital 

Episode References:

• Nvidia’s H100 – What It Is, What It Does, and Why It Matters
• kW, MW and GW: How electricity units work and how to convert them
• The State of Digital Assets Data and Infrastructure: 2023 Edition Sponsored by Amberdata
• Nvidia H100s shipped 2023
• Hugging Face: The platform where the machine

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Ben Parr is a tech industry veteran with a career spanning from award-winning author to influential editor at CNET and Mashable. He's also the co-founder of Octane AI and the driving force behind the AI Analyst, a decade-long voice at the intersection of tech, business, media, and society. 💼🚀📱

🎙️ Looking for daily strategies on how to integrate AI into your life and work? Then this episode is for you. Ben shares his take on where we are in the story (these tools are the worst they will ever be right now), the mindset for success (using AI vs being AI-first), and why the changes in this past year are comparable (or outpacing) the mobile revolution.

Key takeaways from our conversation with Ben:
📦 AI's Impact on E-commerce: AI plays an increasingly important role in e-commerce. For example, companies like Octane AI are already being used to enhance customer experiences through product recommendations and personalized interactions.
🧠 Embracing an AI-Native Mindset: The concept of being "AI-native" or having an "AI-first" mindset is crucial for individuals and organizations. You need to integrate AI into everyday workflows and tasks to stay competitive and adapt to the evolving technological landscape.
🌍 Global AI Competition: You cannot ignore the geopolitical aspects of AI development, such as the competition among countries and companies to maintain leadership in AI. This includes potential risks and challenges associated with global AI competition.
🚀 AI Across Industries: AI's influence extends across various industries, including social impact, governance, ethics, sustainability, finance, healthcare, education, and government.
💥 The importance of personal brand in the age of AI: Personal branding is key in this evolving AI landscape, and it can set you apart for long-term success.
📚 Stay Curious, Stay Ahead: It’s essential to invest in continuous learning and stay informed about AI trends and tools. Ben recommends daily experimentation with AI technologies to adapt to the changing AI landscape effectively.

Connect with Ben here:

• BenParr.com
• Ben Parr on Linkedin
• The AI Analyst Newsletter
• CoWorking with AI on Maven 
  • In this course Ben teaches you the fundamentals of incorporating AI into your work: tips, tricks, tools and optimizations that will save your company and career
• Captivology
  • In this book Ben examines the psychological phenomena that captivate our attention

Episode References:

• Octane AI
• Subscribe to the AI Analyst here
• Generative AI Cheat Sheet
• AI Code of Ethics
• EvenUp La

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Engineers and data leads engaged in grassroots AI projects or tackling challenges related to AI headcount, budget, and ROI expectations might find this episode particularly resonates. Hadrian's Klaas Meinke and Jasper Insinger join us to share their experiences in founding AI projects at Hadrian, collaborating across functions, and achieving business ROI in AI deployments.

Klaas, an aerospace engineering graduate from TU Delft, made a significant transition from astronomy research to Hadrian. Recognizing the transformative potential of AI and big data, he has been an integral part of Hadrian for almost a year, working as an AI machine learning engineer and data scientist.

Jasper, a TU Delft electrical engineering graduate, brings his unique background to the conversation. With hands-on experience in solar car engineering and a remarkable win in the Sasol Solar Challenge, he smoothly transitioned into cybersecurity, becoming a founding member of Hadrian's data team.

Key Takeaways:

1. Mindset: Maintaining the right mindset is crucial role. Technical expertise alone is insufficient, and success hinges on a positive and critical mindset
2. Taking Ownership: Underscoring the importance of assuming ownership of one's work and refraining from attributing blame to others, teams should focus on proactively seeking opportunities for improvement and drive positive change
3. Prioritizing Continuous Improvement: The conversation consistently highlights the value of ongoing advancement, stressing the significance of identifying areas for improvement, actively seeking feedback, and striving to enhance output
4. Embracing Feedback and Constructive Critique: Examples are shared of how soliciting feedback from peers, embracing criticism, and fostering self-critique have played a pivotal role in deploying and validating critical AI deployments
5. Promoting Teamwork and Collaboration: The discussion indirectly underscores the importance of teamwork and collaboration. The focus on seeking feedback and self-improvement supports a collaborative approach to problem-solving and skill development

Episode References:

• South Africa's Sasol Solar Challenge
• Dutch Team's Sasol 2022 Win
• Hadrian.io
• More from Klaas: How Generative AI is Shaping Cybercrime

Connect with Klaas and Jasper here:

• Klaas on Linkedin
  • Klaas on How Generative AI is Shaping Cybercrime

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Joseph Reeve from Amplitude Analytics' AI R&D team explores the world of building intelligent digital products using AI and ML. In our conversation we cover:

1. Data Governance: Discussion on the importance of data governance, including proactive and reactive strategies. Proactive governance involves planning data collection, while reactive governance focuses on fixing data issues after they occur.
2. Interdisciplinary Collaboration: Highlighting the interdisciplinary nature of AI projects and the significance of collaboration among different roles to achieve success.
3. AI in Digital Products: Delving into the role of AI in the future of digital products, emphasizing integration into every feature for personalized experiences.
4. Key Takeaways: Exploring lessons learned from their journey, such as the importance of trust in data, robust data governance, and rapid iteration.
5. Team Structure: Describing the team at Amplitude, consisting of product engineers and machine learning scientists, and their unconventional formation from a data governance sub-team.
6. Collaboration: Emphasizing the importance of shorter feedback loops, tight collaboration, and a clear product roadmap in achieving success.
7. Large Language Models: Discussing the introduction of Large Language Models (LLMs) internally, with a focus on smaller features that garnered more adoption.
8. Stakeholder Management: Addressing the challenges of managing stakeholders and effectively communicating the scope and impact of AI projects within the organization.

Overall, the conversation provides insights into building intelligent digital products with a strong focus on data governance, collaboration, and the evolving role of AI in the digital product landscape.

Episode References:

• Iteratively on Product Hunt (Acquired by Amplitude Analytics)
• Sustaining vs Disruptive Innovation (HBR)
• Passive vs Active Data Governance
• Target Fixation Problem
• PageSpeed Insights
• What is Prompt Engineering?
• What is Prompt Architecture?
• Amplitude Analytics x Iteratively Acquisition
• More about Amplitude Analytics

Connect with Joe here:

• Joseph Reeve on Linkedin

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

You can view screen-share from Paul on Youtube here

In this episode, Keeper's Founder and CEO Paul Koullick explores the transformative impact of AI for tax preparation software. He discusses the limitations of rules-based systems and how AI, as exemplified by Keeper, simplifies tax preparation with machine learning.

Paul also delves into the changing perception of AI, from being a novelty to a valuable tool for various industries, emphasizing its broader applications in user interfaces and product development.

Additionally, the podcast addresses the role of AI in job markets, emphasizing its potential to enhance productivity rather than replace jobs. Paul provides practical advice for job seekers assessing AI technology in companies and offers insights into personal AI use cases, including travel planning and customer support.

Tune in for a comprehensive exploration of AI's evolution, impact, and practical implications in various domains.

Episode References:

• Choosing between a rule-based vs. machine learning system
• GPT 3 vs. 4: Know The Difference
• CLIPPY
• Ask an AI Account Research Paper (Keeper)
• More Whitepapers on Keeper
• More about Keeper

Connect with Paul here:

• Paul Koullick on Linkedin
• Paul Koullick on Medium
  
  

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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Amin's journey into the world of artificial intelligence (AI) began around 2006 when he became captivated by the potential of neural networks to learn from data. He noticed that AI experienced periods of intense hype followed by quieter moments.

Amin delved into AI by building neural networks from scratch in C. This hands-on experience enabled him to understand AI models thoroughly and create complex applications.

In his industry work, Amin applied AI knowledge to real-world applications.

In business discussions, Amin highlights the challenge of balancing quick wins and long-term investments when adopting emerging tech like AI.

Amin identifies five pillars that companies should consider when evaluating AI investments:

1. Investment in Data Infrastructure: Focusing on data governance and infrastructure to enable smarter applications.
2. Data Collection, Processing, and Storage: Establishing best practices for data collection, labeling, and reliable model training.
3. Cleaning Data and Validation: Recognizing the challenge of data cleaning, validation, and labeling, particularly as GDPR regulations emphasize ethical data usage.
4. Ethical Framework for Data Usage: Ensuring transparency and compliance with data privacy regulations like GDPR.
5. Creating an AI Supporting Ecosystem: Building an ecosystem that goes beyond technology, fostering organizational cultures that understand AI's value and prioritize trust and transparency.

Amin also emphasizes the need for companies to develop a clear AI roadmap aligned with their business objectives and integrate AI into their products and services strategically. While the AI hype can be beneficial in motivating companies to adopt AI, the associated risks lie in not having a well-defined plan or understanding of how AI can genuinely add value. To become AI-ready, companies must prioritize the business value of AI over its "coolness factor" and invest in the right talent to guide their AI initiatives.

Episode References:

• Turbo Pascal
• Neural Networks
• Machine Learning
• Jürgen Schmidhuber
• LSTM's
• Vanishing Gradient Problem
• GDPR (EU's Data Protection Laws)
• Gradient Boosting Machines (GBMs)
• Graphcore AI
• Geoffrey Hinton

Connect with Amin here:

Enjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us.

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🔥 Subscribe for weekly drops
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🎙️ The AI-First Business Podcast

AI isn’t coming—it’s already built. This is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.

Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.