Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Oleg Danyliuk, CEO of Duanex and CTO of Insyghtful.ai. Oleg combines nearly two decades of enterprise software experience with a deep focus on AI-driven automation and real-time insights, helping businesses scale efficiently while keeping human judgment in the loop.

Oleg shares his journey from a Java developer in Ukraine to leading distributed engineering teams across continents, building high-load banking systems, ticketing platforms, and enterprise service buses. He discusses founding Duanex in 2016 to provide clients with high-value automation solutions, emphasizing transparency, delivering real outcomes, and prioritizing client relationships over short-term revenue.

The conversation explores how Oleg applies enterprise-grade rigor to AI agent development. He walks through his work deploying AI for lead validation at Duanex and developing Insyghtful.ai, a platform that reads the emotional temperature of sales calls in real-time, providing actionable guidance to reps while balancing speed, latency, and usability. Oleg explains the challenges of working with incomplete or messy data, handling human-AI collaboration, and managing distributed teams under extreme conditions, including operating with developers in active war zones in Ukraine.

Oleg also shares insights on scaling AI responsibly: start small, focus on meaningful impact, avoid automating everything, and use external APIs like OpenAI’s Gemini to test quickly before committing to full custom models. He emphasizes that AI should augment human intelligence rather than replace it, highlighting the ongoing need for maintenance, monitoring, and cultural context when interpreting emotional signals in conversations.

For founders, technical leaders, and AI enthusiasts, Oleg’s advice is clear: focus on solving high-value problems incrementally, maintain transparency with clients, and continuously validate your models in production to ensure real-world efficacy.

Key Takeaways:

1. Start small with AI automation—test single steps before scaling
2. Use APIs for low-cost experimentation before building custom models
3. Real-time AI requires low latency (sub-second) for actionable insights
4. AI augments humans; it does not replace nuanced human judgment
5. Distributed engineering teams can maintain high performance even under extreme conditions with proper infrastructure and human connection
6. Data quality is an ongoing effort, not a one-time cleanup
7. Transparency with clients builds long-term trust and drives referrals

Connect with Oleg Danyliuk:

1. LinkedIn: https://www.linkedin.com/in/oleg-danyliuk
2. Company: https://duanex.com

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Alessandro Pireno, a fractional CTO and CPO, board advisor, and AI, data, and go-to-market leader who helps early-stage startups scale. Alessandro has led product engineering and sales engineering teams at Snowflake and Surreal DB. His unique path spans applied physics, engineering, product leadership, and sales, giving him a 360-degree perspective on building, selling, and scaling technology.

Alessandro shares insights from his experience helping startups navigate technical product commercialization, particularly in the AI infrastructure space. He explains common pitfalls, including products that technically excel but fail to align with customer value or economic impact. He highlights how startups can distinguish between “nice-to-have” features versus core value drivers, emphasizing the importance of translating technical capabilities into measurable outcomes for customers.

The discussion explores the critical role of sales engineers in driving adoption, not just demos, and how cross-functional collaboration between sales and engineering teams accelerates success. Alessandro also dives into key differences between CIO and CISO perspectives, how AI has reshaped executive priorities, and why understanding the true customer pain is more valuable than superficial feature adoption.

He shares real-world examples of when beautiful UX or “pretty packaging” can mislead buyers, stressing that delivering the right solution—even if it looks less polished—creates real value and long-term trust. He also emphasizes the importance of leveraging proprietary data effectively as a competitive advantage in AI product development.

For technical leaders—CTOs, VPs of engineering, and founders building AI or data-driven products—Alessandro’s principle is clear: stress-test assumptions, focus on delivering measurable impact, and use cross-functional experience to bridge the gap between engineering, product, and sales.

Key Takeaways:

1. AI adoption alone does not guarantee differentiation; understand real customer impact
2. Translate technical features into measurable business value, not just performance metrics
3. Strong collaboration between sales engineers and sales teams accelerates adoption
4. CIOs often focus on cost optimization, while CISOs prioritize risk management
5. Proprietary data is the “crude oil” that makes AI-powered products unique
6. Avoid prioritizing aesthetics over function when delivering solutions
7. Early-stage startups benefit from fractional leadership with a cross-functional lens

Connect with Alessandro Pireno:

1. LinkedIn: https://www.linkedin.com/in/apireno
2. Website: https://pireno.com

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Abukari Einus, Co-Founder & CEO of FoodQwik. Abukari has built across multiple domains, from healthcare systems at First Line 24, decentralized finance at NorthStar, to robotics at Three Farm State Farming.

The conversation explores Abukari’s journey shipping full-stack systems, smart contracts, automated deployments, and managing Linux servers while solving real-world problems in emerging markets. They discuss how FoodQwik uses AI to personalize food recommendations for dietary and allergy needs, creating a more mindful and health-conscious food ordering experience in Ghana.

Abukari shares lessons learned from building in highly regulated and technical domains like healthcare and DeFi, emphasizing accountability, automation, and iterative user feedback. He also highlights the operational and logistical challenges of running a food tech platform in Northern Ghana and how his team overcomes them to ensure timely delivery.

The discussion touches on AI-driven personalization, the importance of conversational interfaces in food tech, and how FoodQwik differentiates itself from general ordering platforms by focusing on users with niche dietary needs. Finally, Abukari offers advice for builders in emerging markets: keep shipping, iterate with users, and embrace automation to scale effectively.

Key Takeaways:

1. Building technology in emerging markets requires iterative user feedback and adaptability
2. AI can tailor food ordering to dietary, allergy, and health needs
3. Accountability and security lessons from DeFi and healthcare transfer to consumer tech
4. Automation is critical for small teams with limited margins for error
5. Operational logistics are a key challenge in scaling food delivery in Africa
6. Differentiation comes from focusing on niche needs and user experience

Connect with Abukari Einus:

1. LinkedIn: https://linkedin.com/in/abukari-einus-913721177
2. GitHub: https://github.com/blackdante101

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Terry O’Daniel, CISO, advisor, and investor with experience at Amplitude, Instacart, Netflix, Salesforce, and Yahoo!.

The conversation explores Terry’s journey from hands-on engineering to executive security leadership, emphasizing how security can enable business rather than act as a blocker. Terry shares how automation and embedding security directly into development pipelines have transformed the way teams operate, allowing them to focus on meaningful outcomes instead of repetitive tasks.

They dive into DevSecOps, continuous threat exposure management (CTEM), and the evolution of enterprise security practices. Terry explains why traditional compliance-driven approaches are insufficient for modern software delivery and how organizations can prioritize threats, reduce noise, and adopt continuous, operationalized security practices.

The discussion also covers the role of AI in security, from simulating attack scenarios to intelligent vulnerability prioritization, and how these innovations are helping companies maintain resilience while scaling operations.

Finally, Terry reframes security as a driver of customer trust and business growth, showing how strong security practices can accelerate adoption, meet enterprise expectations, and become a competitive advantage.

Key Takeaways:

1. Security as a business enabler, not a blocker
2. Automating repetitive tasks to focus on high-impact work
3. Embedding security early in development pipelines
4. Continuous Threat Exposure Management (CTEM) in practice
5. Using AI for threat simulation and vulnerability prioritization
6. Prioritization strategies for large volumes of security alerts
7. Building customer trust through security excellence

Connect with Terry O’Daniel:

1. LinkedIn: linkedin.com/in/terryodaniel
2. Website: terryodaniel.com

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Thomas Stiehm, a seasoned technology leader and former CTO at Covaras, with nearly two decades of experience driving DevOps, DevSecOps, and large-scale cloud transformation initiatives.

The conversation explores how Thomas’s early experience during Y2K shaped his perspective on software longevity, risk, and the hidden assumptions in system design. He shares insights from leading global engineering teams, scaling agile practices across distributed organizations, and building high-performance systems that support millions of users.

They discuss DevOps culture, the evolution into DevSecOps, and how organizations can integrate security into fast-moving pipelines without slowing down innovation. Thomas also breaks down how AI and large language models are transforming software development, particularly in automating test creation and improving developer productivity.

The episode closes with Thomas’s perspective on the future of AI in engineering, emphasizing the importance of test automation, security-first thinking, and building confidence to move fast without breaking critical systems.

Key Takeaways:

1. How Y2K shaped modern thinking around system risk and longevity
2. Scaling DevOps and agile across global, distributed teams
3. Integrating security into DevSecOps without slowing delivery
4. Using AI and LLMs to accelerate testing and development
5. Why test automation is critical for speed and reliability

Connect with Thomas Stiehm:

1. LinkedIn: https://linkedin.com/in/stiehm

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Lin Sun, a leader in cloud-native open source and AI infrastructure. Lin is part of Open Source at solo.io, a core maintainer of Istio, kgateway, and kagent, a member of the Istio TOC and Steering Committee, a CNCF TOC member and Ambassador, and an international speaker.

The conversation explores the rise of AI agents running on Kubernetes and how open source infrastructure is evolving to support agentic workloads in production. Lin shares lessons from her journey as an IBM Master Inventor to shaping some of the most widely adopted cloud-native projects in the ecosystem.

They discuss Istio, service meshes, AI agent security, and why running agents is fundamentally different from running traditional microservices. Lin also breaks down the importance of open standards, community governance, and sustainability as AI adoption accelerates across enterprises.

The episode closes with insights on leadership in open source, contributing at scale, and what builders need to understand to prepare infrastructure for the next generation of AI systems.

Key Takeaways:

1. How AI agents change Kubernetes and cloud-native design
2. Securing and operating AI agents in production
3. The role of open source governance in AI infrastructure
4. Lessons from leading Istio and CNCF communities

Connect with Lin Sun:

1. LinkedIn: https://linkedin.com/in/lin-sun-a9b7a81

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Kisa Brostrom, Chief Technology Officer at Boodle AI. Kisa’s career spans analyzing weather data in Oklahoma, predicting gas turbine failures at Rolls-Royce, building healthcare AI models, and now leading Boodle Box, a generative AI platform for higher education.

Kisa shares her journey from self-teaching programming and machine learning to executive leadership, emphasizing building high-performing teams and balancing strategic vision with hands-on problem-solving. She discusses challenges in automation, model reliability, and human-in-the-loop AI, as well as how Boodle Box equips students to use generative AI responsibly while democratizing access to cutting-edge technology.

The episode also explores team culture, adoption, and leadership perspective, highlighting how to maintain trust, ethical practices, and innovation in high-velocity tech environments.

Key Takeaways:

1. Building AI teams that deliver results
2. Human-in-the-loop AI for ethical, trustworthy systems
3. Staying connected to ground-level operations as a tech leader
4. Educating the next generation on responsible AI use

Connect with Kisa Brostrom:

1. linkedin.com/in/kisabrostrom

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Abhinav Agarwal, founder of a stealth startup, AI researcher at the Stanford Center for AI in Medicine and Imaging, and former CTO at KOS. Abhinav is the creator of Argus, the world’s first truly non-invasive continuous glucose monitor, and a leader in responsible healthcare AI.

They discuss his latest venture, Clear Health, which develops wearable technology to continuously track 100+ biomarkers for women’s health—completely non-invasive, without blood draws or needles. Abhinav explains why most existing solutions still fall short, and how Clear Health uses optical sensors, edge AI, and multimodal data fusion for personalized hormone tracking.

The conversation covers fertility planning, IVF, perimenopause, menopause, and athletic performance, highlighting how inaccurate period tracking apps fail most women. Abhinav also shares lessons from high-stakes healthcare AI projects, emphasizing trust, transparency, and human-in-the-loop decision-making.

Key Takeaways:

1. What “non-invasive” really means in healthcare technology
2. How personalized hormone tracking transforms women’s health
3. Balancing AI automation with human oversight
4. Ethical and trust-focused AI design principles

Connect with Abhinav Agarwal:

1. linkedin.com/in/agarwalaabhinav
2. wearclair.com
3. instagram.com/hereandabhi

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Aby Rao, Deputy CISO and cybersecurity leader with over two decades of experience across identity security, cloud and enterprise security, GRC, and AI risk management.

Aby shares how his background in identity and cloud security shaped his approach to responsible AI adoption. The conversation focuses on AI governance, model risk management, and the secure adoption of generative and agentic AI, including why enterprise-wide ownership and human-in-the-loop controls are critical as automation accelerates.

He also offers practical advice on translating AI risk into business language, aligning security with product and engineering teams, and building future-ready security programs that enable innovation without sacrificing trust.

Key Takeaways:

1. Why identity remains central to AI security
2. What effective AI governance looks like in practice
3. Securing generative and agentic AI without slowing the business
4. Communicating AI risk to executives and boards

Golden Nugget:

“You can’t secure what you don’t understand. Start with the technology, then build the guardrails.”

Connect with Aby Rao:

1. LinkedIn: linkedin.com/in/abyrao

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.

Episode Summary:

In this episode of Automate or Die Trying, host Wil Ramos sits down with Joshua Copeland, CISO, Professor, Best-Selling Author, Speaker, Startup Advisor, and Board Member, also widely known as the #UnpopularOpinionGuy in cybersecurity.

Joshua shares his 25-year journey across military, federal, state, and commercial cybersecurity environments, from Air Force communications and nuclear cybersecurity missions to leading enterprise security programs and advising startups and boards. He explains how operating in zero-fail military systems shaped his philosophy around resilience, accountability, and building fearless teams.

The conversation dives into what actually makes security programs effective, why many organizations confuse compliance with security, and how automation and AI should be used to eliminate noise, not judgment. Joshua challenges industry norms around certifications, vanity metrics, and tool sprawl, arguing that resilient systems are built on strong foundations, clear ownership, and empowered people.

Finally, Joshua offers practical advice for CISOs and technology leaders navigating rapid change, emphasizing business alignment, human-centered security, and leadership courage over checkbox security theater.

Key Takeaways:

1. Why compliance is a baseline, not a cybersecurity strategy
2. What resilient systems actually look like in real organizations
3. How automation and AI should reduce burnout, not replace thinking
4. The danger of security theater and metric-driven decision-making
5. How to build fearless, accountable security teams

Golden Nugget:

“The next tool won’t save you. Resilient systems are built by people who understand risk, own outcomes, and aren’t afraid to challenge bad assumptions.”

Connect with Joshua Copeland:

1. LinkedIn: linkedin.com/in/joshuacopeland

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Automate or Die Trying empowers leaders to adopt AI securely, move faster with confidence, and transform the future of work.