Cancer care still forces patients and doctors to guess! Learn how functional precision medicine is replacing that uncertainty by testing cancer drugs before treatment even begins.

In this episode of An Hour of Innovation podcast, host Vit Lyoshin speaks with Jim Foote, co-founder and CEO of First Ascent Biomedical, an innovator who is challenging one of the most uncomfortable truths in modern medicine: many cancer treatments are chosen without knowing if they will actually work.

First Ascent Biomedical is a company focused on transforming personalized cancer treatment through functional precision medicine and data-driven decision support.

In this conversation, they explore how functional precision medicine differs from traditional precision medicine and why testing drugs on patients’ live tumor cells changes everything. Jim explains how AI, robotics, and large-scale drug testing help doctors move from trial-and-error to a true test-and-treat approach. The discussion also covers the risks of ineffective or harmful treatments, the economic cost of cancer care, and what must change for this model to become part of standard oncology practice.

Jim Foote is a former technology executive turned healthcare innovator whose work is deeply shaped by personal loss and firsthand experience with cancer care. He is best known for advancing functional precision medicine by combining genomics, live-cell drug testing, and AI-driven analysis to guide treatment decisions. His perspective matters because it connects real clinical outcomes with the technology needed to give doctors and patients clearer, faster, and more humane options.

Takeaways

* Cancer treatment still relies heavily on trial-and-error, even with modern medical technology.

* Two biologically different patients often receive the same cancer treatment based on population averages.

* Precision medicine based on DNA and RNA sequencing still cannot confirm if a drug will work before it’s given.

* Functional precision medicine tests drugs directly on a patient’s live tumor cells before treatment begins.

* Some FDA-approved cancer drugs can be completely ineffective or even make a patient’s cancer worse.

* Testing drugs outside the body can prevent patients from being exposed to harmful or useless treatments.

* AI and robotics enable hundreds of drug tests to be completed in days instead of weeks or months.

* In a published study, 83% of refractory cancer patients did better when treatment was guided by this approach.

* Knowing which drugs won’t work is just as important as knowing which ones will.

* Personalized, test-and-treat cancer care has the potential to improve outcomes while reducing overall healthcare costs.

Timestamps

00:00 Introduction

02:46 The Core Problem in Modern Cancer Care

04:16 Functional Precision Medicine Explained

06:42 How AI, Robotics, and Data Are Changing Cancer Treatment

10:01 How Cancer Drugs Are Tested Before Treatment

13:20 Personalized, Patient-Centric Cancer Care

18:22 Cost, Access, and the Economics of Cancer Treatment

22:19 The Future of Cancer Care and Patient Empowerment

25:21 Real Patient Outcomes and Success Stories

26:50 Why Functional Precision Medicine Is the Future

31:18 Predicting, Detecting, and Preventing Cancer Earlier

34:27 Where to Learn More About Functional Precision Medicine

36:12 Transforming Healthcare Beyond Trial-and-Error

37:27 Regulations, FDA Pathways, and Scaling Innovation

40:09 Why Cancer Is Affecting Younger Patients

41:17 Innovation Q&A

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Connect with Jim

* Website: https://firstascentbiomedical.com/

* LinkedIn: https://www.linkedin.com/in/jim-foote/

* TEDx Talk: https://www.youtube.com/watch?v=CqLCgNxUhVc

Connect with Vit

LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

X: https://x.com/vitlyoshin

Website: https://vitlyoshin.com

Podcast: https://www.anhourofinnovation.com/

Music education is quietly undergoing a massive shift, and most people haven’t noticed yet.

AI tutors are no longer just tools; they’re starting to shape how musicians learn, practice, and improve. But here’s the real question: where does human creativity and mentorship still matter in an AI-driven world?

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with John von Seggern, a longtime musician, educator, and founder of Futureproof Music School, to unpack what’s actually changing, and what isn’t, in the future of music education. John has spent over a decade designing online music education programs and now works at the intersection of AI, creativity, and human mentorship.

In this conversation, they explore how AI is personalizing music education in ways traditional schools struggle to scale. John explains how AI tutors can analyze music, guide students through complex production workflows, and surface the one or two things that matter most at each stage of learning. They also dig into why AI still falls short in mastery, taste, and creative judgment, and why human mentors remain essential. They discuss the hybrid model of AI tutors and human teachers, the future of music production learning, and what this shift means for creators trying to stay relevant in a fast-changing industry.

John von Seggern is a musician, producer, educator, and music technologist who has worked with film composers and contributed sound design to Pixar’s WALL·E. He previously helped lead and design one of the world’s most respected electronic music programs before founding Futureproof Music School, where he’s building AI-powered, personalized music education systems. His work matters because it goes beyond hype, offering a practical, grounded view of how AI can support creativity without replacing the human elements that make music meaningful.

Takeaways

* AI tutors are most effective when they surface only one or two actionable fixes, not long reports that overwhelm learners.

* Music education improves dramatically when AI can analyze your actual work (like mixes), not just answer theoretical questions.

* The biggest limitation of AI in music is that elite, professional knowledge is often undocumented, so models can’t learn it.

* Human mentors remain essential at advanced levels because taste, judgment, and creative intuition can’t be automated.

* Personalized learning paths outperform one-size-fits-all programs, especially in creative and technical fields like music production.

* Generative AI tools are fun, but most professionals prefer AI that assists the process, not tools that generate finished music.

* AI acts best as an intelligence amplifier, helping creators move faster rather than replacing their role.

* The future of music education isn’t AI-only, but a hybrid model where AI accelerates learning, and humans guide mastery.

Timestamps

00:00 Introduction

03:02 How AI Is Transforming Music Education

07:50 Why AI + Human Mentorship Works Better Than Music Schools

11:43 Why Music Education Curricula Must Evolve Faster

15:04 How AI Personalizes Music Learning for Every Student

19:38 Building an AI-Powered Education Business

24:22 What Students Really Say About AI Music Education

26:20 Electronic Music vs Learning Traditional Instruments

27:58 The Future of AI in Music and Creative Industries

30:28 Why Artists Still Matter in AI-Generated Art

32:21 Who Owns Music Created With AI?

36:50 How Creators Can Survive and Thrive Using AI

42:24 Innovation Q&A

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Connect with John

* Website: https://futureproofmusicschool.com/

* LinkedIn: https://www.linkedin.com/in/johnvon/

Connect with Vit

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

* Website: https://vitlyoshin.com/contact/

* Podcast: https://www.anhourofinnovation.com/

Most companies have no idea how risky and expensive their AI systems truly are until a single mistake turns into millions in unexpected costs.

In this episode of An Hour of Innovation podcast, host Vit Lyoshin explores the truth about AI safety, enterprise-scale LLMs, and the unseen risks that organizations must fix before it’s too late.

Vit is joined by Dorian Selz, co-founder and CEO of Squirro, an enterprise AI company trusted by global banks, central banks, and highly regulated industries. His experience gives him a rare inside look at the operational, financial, and security challenges that most companies overlook.

They dive into the hidden costs of AI, why RAG has become essential for accuracy and cost-efficiency, and how a single architectural mistake can lead to a $4 million monthly LLM bill. They discuss why enterprises underestimate AI risk, how guardrails and observability protect data, and why regulated environments demand extreme trust and auditability. Dorian explains the gap between perceived vs. actual AI safety, how insurance companies will shape future AI governance, and why vibe coding creates dangerous long-term technical debt. Whether you’re deploying AI in an enterprise or building products on top of LLMs.

Dorian Selz is a veteran entrepreneur, known for building secure, compliant, and enterprise-grade AI systems used in finance, healthcare, and other regulated sectors. He specializes in AI safety, RAG architecture, knowledge retrieval, and auditability at scale, capabilities that are increasingly critical as AI enters mission-critical operations. His work sits at the intersection of innovation and regulation, making him one of the most important voices in enterprise AI today.

Takeaways

* Most enterprises dramatically overestimate their AI security readiness.

* A single architectural mistake with LLMs can create a $4M-per-month operational cost.

* RAG is essential because enterprises only need to expose relevant snippets, not entire documents, to an LLM.

* Trust in regulated industries takes years to build and can be lost instantly.

* Real AI safety requires end-to-end observability, not just disclaimers or “verify before use” warnings.

* Insurance companies will soon force AI safety by refusing coverage without documented guardrails.

* AI liability remains unresolved: Should the model provider, the user, or the enterprise be responsible?

* Vibe coding creates massive future technical debt because AI-generated code is often unreadable or unmaintainable.

Timestamps

00:00 Introduction to Enterprise AI Risks

02:23 Why AI Needs Guardrails for Safety

05:26 AI Challenges in Regulated Industries

11:57 AI Safety: Perception vs. Real Security

15:29 Risk Management & Insurance in AI

21:35 AI Liability: Who’s Actually Responsible?

25:08 Should AI Have Its Own Regulatory Agency?

32:44 How RAG (Retrieval-Augmented Generation) Works

40:02 Future Security Threats in AI Systems

42:32 The Hidden Dangers of Vibe Coding

48:34 Startup Strategy for Regulated AI Markets

50:38 Innovation Q&A Questions

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Connect with Dorian

* Website: https://squirro.com/

* LinkedIn: https://www.linkedin.com/in/dselz/

* X: https://x.com/dselz

Connect with Vit

* Substuck: https://substack.com/@vitlyoshin

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

* Website: https://vitlyoshin.com/contact/

* Podcast: https://www.anhourofinnovation.com/

AI is becoming a business partner, not just a tool, and soon, your data will literally talk back to you.

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Mustafa Parekh, the founder of Lazy Admin, to explore how personalized AI is transforming the way companies understand and use their data.

Mustafa breaks down how Lazy Admin turns complex Salesforce and CRM information into natural-language insights, visualizations, and strategic recommendations, all in seconds. They talk about the rise of AI assistants, the future of enterprise AI, how AI can learn your internal business language, the challenges of building secure “zero-data-exfiltration” systems, and why the next era of innovation isn’t just about solving problems, it’s about creating better, more human-centered ways of working. Together, they dive into AI ethics, government regulation, AGI risks, job displacement, product development mindsets, and why founders should build Minimum Lovable Products instead of just MVPs.

Mustafa Parekh is a tech entrepreneur, Salesforce consultant, and the creator of Lazy Admin, an AI-powered data insights platform redefining how businesses access reporting and analytics. He is known for pioneering privacy-first architecture in enterprise AI, automating CRM workflows without exposing sensitive data, and helping companies make smarter decisions using real-time insights. His background spans full-stack development, global consulting work, and building impactful SaaS tools across industries.

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI is evolving from a generic tool into a personalized business partner that understands company context.

* AI that learns your internal acronyms, vocabulary, and business lingo delivers dramatically better results.

* Privacy-first architecture like Zero-Data-Exfiltration is becoming essential for enterprise AI adoption.

* Companies waste hundreds of hours on reporting that AI can now generate in seconds.

* The best products aren’t just viable, they’re lovable.

* AI’s biggest impact will come when it merges with robotics and neuroscience, not just software.

* Government regulation may slow down certain AI advancements due to unemployment and economic pressure.

* Open-source AI offers deeper integration, while proprietary models support faster innovation.

* Rapid prototyping and minimizing development time are critical for early-stage founders.

* Marketing, not development, becomes the real challenge after launching a startup.

* Choosing the right customer segment and understanding their pain points is essential for SaaS success.

* The future of business AI lies in human-centered design, technology that enhances people rather than replaces them.

Timestamps

00:00 Introduction

02:53 How Lazy Admin Was Born

08:13 Validating the AI Product Idea

11:02 How Lazy Admin Works

13:02 User Experience & Onboarding

17:18 AI Trends: The Start of the “AI Age”

20:37 The Reality of AI Ethics

23:11 Open Source vs Proprietary AI

24:36 Will AI Replace Jobs?

26:31 Startup Lessons & Founder Mistakes

31:50 Client Success Stories

33:42 Innovation Q&A Round

Connect with Mustafa

* Website: https://lazyadmin.httpeak.com/

* LinkedIn: https://www.linkedin.com/in/mustafaparekh/

Connect with Vit

* Substuck: https://substack.com/@vitlyoshin

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

* Website: https://vitlyoshin.com/contact/

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Booking Assistant: https://appforgelab.com/

AI glasses are evolving faster than anyone expected, but only one company is building them to amplify human agency instead of monetizing your attention.

In this episode of An Hour of Innovation podcast, host Vit Lyoshin explores the future of wearable AI with a guest who is reshaping the entire computing landscape: Bobak Tavangar, Co-Founder & CEO of Brilliant Labs.

They dive deep into why the future of AI must be wearable, open-source, and private by design, and how Brilliant Labs’s team created the first AI glasses built to empower people rather than extract their data.

They discuss the emergence of AI memory, the challenges of building long-lasting hardware, why battery life matters more than most people think, the philosophical risks of “outsourcing our thinking” to AI, and why Big Tech’s approach to wearable AI may be leading us in the wrong direction. Bobak also unpacks how open-source hardware can restore human agency, reconnect people, and potentially re-architect the Internet around the individual.

Bobak Tavangar is a former Program Lead at Apple, a serial founder in computer vision and graph search, and now CEO of Brilliant Labs. He’s a design-first innovator who blends engineering with philosophy, an open-source advocate pushing for transparent, trustworthy AI, and a creator inspired by the Baha’i principle of oneness, building technology that strengthens human connection rather than weakens it.

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI glasses can amplify human agency, not replace it, when built with the right philosophy.

* Brilliant Labs designed the first wearable AI platform that is open-source.

* Privacy is central: the device never stores photos or audio, only encrypted embeddings.

* True innovation in hardware requires painstaking component selection and constant iteration.

* The future of computing must align more naturally with human biology than smartphones do.

* AI should be a thought partner, not a substitute for human thinking.

* Overreliance on AI can lead to cognitive atrophy, according to emerging research.

* Open-source systems are essential for trust, transparency, and user control.

* AI memory has the potential to revolutionize learning, recall, accessibility, and life organization.

* Building AI glasses requires deep integration with factories, not just a software mindset.

* Wearable AI may eventually reduce our reliance on smartphones, but the market will decide, not the company.

* Future AI devices should foster connection and human well-being, not distraction or ad monetization.

Timestamps

00:00 Introduction

03:13 Why He Left Apple: The Case for Open-Source AI Glasses

06:00 Why the Next Big Tech Shift Is AI Hardware

09:06 How Brilliant Labs Built Halo: From Idea to Prototype

11:31 What AI Glasses Can Do Today: Memory, Recall, Real-Time Assistance

14:32 AI Memory Explained: How Glasses Learn From Your Life

17:11 The Hardest Problems in AI Hardware: Battery, Sensors, Design

23:59 Meta vs Open-Source: Competing Visions for AI Glasses

30:53 The Future of Wearable AI: Use Cases, Apps, and Developer Tools

35:08 Privacy by Design: Why Brilliant Labs Stores Zero Images or Audio

40:05 Will AI Make Us Smarter or Weaker? The Human Agency Debate

46:56 What Life With AI Glasses Could Look Like in 5–10 Years

50:56 Will Wearable AI Replace Phones? Early Signals for the Future

54:31 Hard Lessons Learned Building Real AI Hardware

01:00:01 Innovation Q&A Round

Connect with Bobak

* Website: https://brilliant.xyz/

* LinkedIn: https://www.linkedin.com/in/bobak-tavangar-29445012/

* X: https://x.com/btavangar

Connect with Vit

* Substuck: https://substack.com/@vitlyoshin

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Booking Assistant: https://appforgelab.com/

Why do most AI initiatives fail — even at the world’s biggest companies?

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Tullio Siragusa, a business strategist, author, and creator of the EmpathIQ Framework™, to break down the human barriers that undermine AI adoption long before the technology ever hits production.

Vit and Tullio explore why AI fails in most organizations, how outdated command-and-control cultures choke innovation, and why empathy, emotional intelligence, and decentralized decision-making are the real prerequisites for a successful AI transformation.

They discuss Tullio’s EmpathIQ model for building AI-ready organizations, the future relationship between human intelligence and artificial intelligence, and the surprising ways companies can triple productivity without hiring by redesigning how people collaborate.

Tullio Siragusa brings over 30 years of experience across telecom, ad tech, and software engineering, and has helped organizations worldwide transform through human-centered leadership. He’s the founder of Inventrica Advisory, a speaker and strategist specializing in organizational design, culture transformation, emotional intelligence, and AI readiness. His EmpathIQ Framework™ has guided companies toward building empowered, autonomous, and highly productive teams capable of thriving in the age of AI.

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI fails in most companies because of culture, not technology.

* Outdated command-and-control structures suffocate the speed and autonomy AI requires.

* Over 70% of AI projects fail due to human and cultural barriers, not technical ones.

* Only 21% of employees are engaged, a massive hidden productivity leak.

* Empowered, decentralized teams dramatically increase innovation and output.

* The EmpathIQ Framework™ can triple a company’s capacity without adding headcount.

* Empathy is a strategic advantage, not a soft skill, and it boosts revenue and performance.

* AI amplifies whatever culture it enters, making organizational design a critical success factor.

* Emotional intelligence will become the biggest competitive edge in the AI era.

* Customers buy based on emotional needs first, not just transactions; empathy wins in sales.

* Fixing culture first is essential before rolling out any meaningful AI transformation.

* AI agents can mimic empathy, but they can’t replace human curiosity, wisdom, or intuition.

* Leaders who ignore emotional intelligence risk building companies that sound cold, clinical, and interchangeable.

Timestamps

00:00 Introduction

05:33 Why AI Fails: The Human Challenge Behind Adoption

07:30 Organizational Design: The Bottleneck in AI Success

10:45 Employee Engagement Crisis: The 21% Problem

13:26 Empathy as a Core Business Strategy

16:25 Measuring AI Success Beyond Technology

24:48 EmpathIQ Framework Overview

26:35 Force Field Analysis Explained

28:27 Collaborative OKRs for Cross-Team Alignment

31:16 Neuroscience-Based Leadership Coaching

33:58 Self-Management & Decentralized Organizations

37:49 Empathy in Action: Elevating Transactions

48:07 Emotional Intelligence as a Competitive Edge

58:20 Integrating Acquisitions with Empathy & Decentralization

Connect with Tullio

* Website: https://tulliosiragusa.com/

* LinkedIn: https://www.linkedin.com/in/tulliosiragusa/

* X: https://x.com/tulliosiragusa

* Other: https://linktr.ee/tulliosiragusa

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Booking Assistant: https://appforgelab.com/

AI that isn’t replacing doctors, it’s helping them save lives, cut costs, and bring humanity back to healthcare.

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Zach Evans, Chief Technology Officer at Xsolis, a leading AI and data analytics company transforming the way hospitals and insurance providers work together.

Zach and Vit dive into how artificial intelligence is removing friction in healthcare, reducing administrative waste, and improving collaboration between hospitals, payers, and clinicians. They explore how predictive analytics and generative AI are being used to accelerate decisions, prevent costly billing errors, and free up doctors to focus on patient care. Zach also shares how his team built Dragonfly, Xsolis’s AI-powered platform that streamlines clinical workflows, enhances cybersecurity, and helps hospitals save millions every year.

As CTO, Zach Evans leads the engineering and product strategy behind Xsolis’s data-driven solutions. With nearly a decade of experience in healthcare technology and digital transformation, he’s helped scale the company from a small startup to a national leader serving hospitals across the US. Zach is passionate about building human-centered AI systems that empower clinicians, improve patient outcomes, and redefine how healthcare organizations operate.

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI isn’t replacing doctors, it’s helping them make faster, better decisions.

* US hospitals spend up to 25% of their revenue on administrative tasks.

* Dragonfly, Xsolis’s AI platform, uses data to reduce friction between hospitals and insurance companies.

* Predictive analytics can determine patient status (inpatient vs. observation) with 99% accuracy.

* Generative AI now drafts clinicians’ initial patient reviews, saving hours of manual work.

* Keeping a “human in the loop” ensures AI supports, not replaces, healthcare professionals.

* Hospitals can resolve claim decisions within hours instead of weeks or months.

* Agentic AI is being developed to automate repetitive tasks like medical forms and data entry.

* Healthcare data is among the most valuable information on the black market, making cybersecurity critical.

* Moving from reactive to proactive security helps prevent attacks before they happen.

* AI is helping hospitals save millions by cutting denied claims and reducing administrative waste.

* The next wave of healthcare innovation is ambient AI, enabling doctors to talk to patients instead of screens.

* Every dollar saved on admin costs can be reinvested into patient care and clinical improvements.

Timestamps

00:00 Introduction

03:01 Understanding Healthcare Friction and How AI Solves It

05:21 AI-Driven Reimbursement: Streamlining Hospital and Insurance Payments

10:55 Cybersecurity in Healthcare: Protecting Patient Data with AI

17:12 Generative AI in Healthcare: New Innovations Changing Medicine

23:34 Dragonfly by Xsolis: An AI Platform for Healthcare Efficiency

26:36 Optimizing Hospital Workflows with Predictive Analytics and AI

28:19 AI for Length-of-Stay Management: Improving Patient Flow

32:33 Future of Healthcare Technology: From Automation to Intelligence

36:54 Data Symmetry in Healthcare: Aligning Hospitals and Insurers

37:48 Leadership and Innovation: Scaling a Healthcare Tech Team

42:49 AI’s Real Impact on Healthcare Professionals and Clinicians

45:34 Restoring Human Connection: How AI Improves Patient–Doctor Relationships

Connect with Zack

* Website: https://www.xsolis.com/

* LinkedIn: https://www.linkedin.com/in/zachevans/

* X: https://x.com/ZachEvans

* Other: https://zachevans.io/

Connect with Vit

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Spiros Xanthos, Founder and CEO of Resolve AI, to explore how artificial intelligence is transforming the world of DevOps, observability, and software reliability.

Spiros shares how Resolve AI is building autonomous AI agents that act like site reliability engineers, capable of troubleshooting incidents, detecting root causes, and even generating pull requests to fix issues before they escalate. The conversation delves into how AI automation is redefining what it means to be an engineer, the evolving trust relationship between humans and AI, and the technical challenges of creating systems that are smart enough to operate in complex production environments. Spiros also opens up about his entrepreneurial journey as a serial founder, his lessons from building multiple startups, and why Resolve AI is the hardest and most rewarding company he’s ever built.

Spiros Xanthos is a serial entrepreneur, technologist, and innovator in the observability and AI DevOps space. Before founding Resolve AI, he co-founded Omnition, which was acquired by Splunk, and Log Insight, which was acquired by VMware. He’s also one of the co-creators of OpenTelemetry, the open-source standard for telemetry data that powers modern observability systems. Today, as CEO of Resolve AI, Spiros leads a team that’s pioneering AI-driven reliability engineering, combining deep observability expertise with cutting-edge AI research to build self-healing software systems.

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI is moving beyond code generation; it’s now running and maintaining production systems.

* The biggest challenge in AI DevOps isn’t data, it’s reasoning across code, logs, and systems.

* Trust is earned; AI systems must prove reliability through transparency and evidence.

* AI can make safe, reversible changes autonomously, reducing human fatigue and error.

* The hardest part of building Resolve AI was teaching AI to reason like an engineer.

* Spiros believes AI won’t replace engineers; it will create more of them by automating repetitive work.

* The role of engineers will shift from coding to directing and orchestrating AI agents.

* Many current DevOps tools were built for humans; the next generation must be agent-first.

* Founders should practice radical transparency to build trust and alignment in their teams.

* Psychological safety and risk-taking are essential for innovation in AI startups.

* Even without a product, talking to users and showing prototypes accelerates validation.

* The future of software is self-healing, intelligent, and AI-managed systems.

* Every product in the next decade will have an AI-first version or be replaced by one.

Timestamps

00:00 Introduction: AI and the Future of Software

05:08 Resolve AI vs Other AI Tools

07:36 Human Oversight in AI Decisions

09:12 Building Trust in AI Systems

10:53 Challenges in AI Development

14:19 Future of Software Engineering with AI

16:53 Unsolved Gaps in AI and DevOps

18:12 Industry Views on AI Automation

19:50 Lessons from Serial Entrepreneurship

23:01 Competing for AI Talent

23:54 Inside Fast-Moving AI Startups

25:52 Customer-Driven AI Product Development

27:46 Engaging Users Without a Product

29:49 Choosing the Right Startup Idea

32:18 Key Lessons for AI Entrepreneurs

34:26 Building Strong AI Teams

36:11 Funding and Growth in AI Startups

37:28 Future of AI in DevOps

39:08 Opportunities in the AI Revolution

41:51 Final Advice for Entrepreneurs

Connect with Spiros

* Website: https://resolve.ai/

* LinkedIn: https://www.linkedin.com/in/spiros/

* X: https://x.com/spirosx

Connect with Vit

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/