In this episode of Open Tech Talks, we delve into the critical topics of AI security, explainability, and the risks associated with agentic AI. As organizations adopt Generative AI and Large Language Models (LLMs), ensuring safety, trust, and responsible usage becomes essential. This conversation covers how runtime protection works as a proxy between users and AI models, why explainability is key to user trust, and how cybersecurity teams are becoming central to AI innovation.

Chapters

00:00 Introduction to AI Security and eIceberg
02:45 The Evolution of AI Explainability
05:58 Runtime Protection and AI Safety
07:46 Adoption Patterns in AI Security
10:51 Agentic AI: Risks and Management
13:47 Building Effective Agentic AI Workflows
16:42 Governance and Compliance in AI
19:37 The Role of Cybersecurity in AI Innovation
22:36 Lessons Learned and Future Directions

Episode # 166

He's founded a next-generation AI cybersecurity company that’s revolutionizing how we approach digital defense. With a strong background in enterprise tech and a visionary outlook on the future of AI, Alexander is doing more than just developing tools — he’s restoring trust in an era of automation.

• Website: AIceberg.ai
• Linkedin: Alexander Schlager

What Listeners Will Learn:

• Why real-time AI security and runtime protection are essential for safe deployments
• How explainable AI builds trust with users and regulators
• The unique risks of agentic AI and how to manage them responsibly
• Why AI safety and governance are becoming strategic priorities for companies
• How education, awareness, and upskilling help close the AI skills gap
• Why natural language processing (NLP) is becoming the default interface for enterprise technology

Keywords:

AI security, generative AI, agentic AI, explainability, runtime protection, cybersecurity, compliance, AI governance, machine learning

• AIceberg.ai

Today, I have brought you an expert who has invested millions in startups, and he will share insights on the evolving landscape of startup investments, particularly in the realm of generative AI.

He discusses his journey from entrepreneurship to venture capital, the importance of learning from failures, and the traits that make startups successful. He also offers valuable advice for aspiring founders on how to improve their chances of success.

Chapters

00:00 Introduction to Gabriel Jorsson and Lobster Capital
02:13 The Shift to AI: Observations from Y Combinator
05:40 Investment Strategies: Beyond Y Combinator
06:22 Learning from Failures: Notable Investment Stories
09:06 Key Traits of Successful Startups
10:29 Generative AI: Trends and Insights
11:24 Evaluating Founders: Traits that Matter
11:55 Advice for Aspiring Entrepreneurs

Episode # 165

He is the Founder and Managing Partner at Lobster Capital, with over $40 million invested in more than 100 Y Combinator startups. As a serial entrepreneur with three exits, he has taken a bootstrapping approach to achieving $1M ARR with zero employees, and sold his first startup at the age of 25.

• Website: Lobster Capital
• YouTube: Lobster Capital

What Listeners Will Learn:

• Learn how Gabriel transitioned from running startups to becoming an angel investor and eventually a venture capitalist at Lobster Capital.

• Understand how personal experiences as a founder shape investment decisions.

• Gain perspective on how Y Combinator has increased its focus on AI startups.

• Recognize why AI represents one of the most significant technological shifts of our time and why investors are paying close attention.

• Hear how failed investments are not wasted but instead offer valuable lessons.

• Learn how to extract insights from what doesn’t work to refine strategies and decision-making.

• Discover the common qualities Gabriel looks for in startups: deep understanding of market needs, creativity with limited resources, and resilience.

• Learn why evaluating founders’ commitment, adaptability, and long-term vision is critical for success.

• Understand why startups should anchor their efforts on creating measurable value for customers rather than chasing hype.

• Get practical advice on how value creation improves both user adoption and investor confidence.

• Explore how generative AI is opening new opportunities for innovation.

• Learn why staying updated and flexible is essential to take advantage of the rapidly shifting AI environment.

• Gabriel emphasizes the importance of being a lifelong learner as a founder.

• Discover how continuous adaptation, openness to feedback, and iteration are vital for building enduring companies.

• Lobster Capital

In this conversation, Aarti Anand shares her journey from a traditional 9 to 5 job to becoming an entrepreneur with Kodenyx AI, focusing on how AI and automation can help businesses thrive. She discusses the importance of identifying business patterns, shares success stories of AI implementations, and highlights the challenges organizations face when adopting AI.

Aarti emphasizes the importance of a proactive mindset, the significance of starting small, and the skills necessary for effective AI project management. She also highlights her current business success and future goals, showcasing the potential of AI in transforming business operations.

Episode # 164

Aarti was a product leader for 15 years and one day, decided to let it all go and start Kodenyx AI.

• Website: Kodenyx AI
• YouTube: Aarti Anand

What Listeners Will Learn:

• How to identify common business challenges through conversations with other entrepreneurs.
• AI and automation became tools for creating a desired lifestyle.
• The importance of defaulting to action rather than over-planning.
• Lead generation and time-saving solutions are key selling points for AI services.
• Starting with service allows for the productization of successful solutions.
• Organizations face knowledge gaps and team pushback when adopting AI.
• A proactive mindset is crucial for success in AI projects.
• Fear of change can hinder progress, but the right mindset can overcome it.

Chapters

00:00 Introduction to Aarti Anand and Kodenyx AI
02:45 The Journey from 9 to 5 to Entrepreneurship
05:49 Leveraging AI for Business Automation
08:36 Common Patterns in AI Implementation
11:34 Success Stories and ROI from AI Solutions
14:37 Challenges in Selling AI Solutions
17:31 Strategies for Successful AI Adoption
20:13 Identifying Skills for AI Projects
23:08 Creating a Culture of Innovation
26:10 Future Vision and Business Growth
27:58 Conclusion and How to Connect with Aarti

• Kodenyx AI

In this episode of OpenTechTalks.tv, we dive into the intricate world of conversational AI with Yam, the founder of Parland. Discover the challenges of managing complexity and uncertainty in AI systems, and explore the opportunities that arise with the advent of GPT-4 and beyond.

Yam shares insights on the importance of control in AI development, the role of subjectivity in conversation design, and the potential pitfalls of overhyped expectations.

Join us for a thought-provoking discussion on the future of AI and its impact on the tech industry.

Sound Bites

"I wanted to start my own company at that point."
"How can we introduce more control into GenAI?"
"We felt that things were really overhyped."

Episode # 163

Giorgio Natili is a tech leader, author, and advocate for fearless leadership. With over 20 years of experience, he has led teams at companies such as Amazon, Mozilla, and Capital One.

• Website: Parlant

What Listeners Will Learn:

• A journey from coder to entrepreneur highlights the evolution of AI.
• The challenges in programming languages stem from subjective decision-making.
• Control in generative AI is crucial for building reliable systems.
• Conversational design must consider real user behavior and preferences.
• Market research is essential for understanding user needs in AI.
• Open-source frameworks should focus on specific use cases for better utility.
• Managing complexity in AI conversations requires a clear separation of concerns.
• Mistakes in AI can have significant implications, not just in terms of frequency.
• New developers should seek mentorship and avoid hype-driven decisions.
• Understanding the landscape of AI requires practical experience and community engagement.

Chapters

00:00 Introduction to Jam and His Journey
02:34 The Genesis of Parland and GPT-4 Influence
05:13 Challenges in Programming Language Design
07:59 Exploring Control in Generative AI Systems
10:39 Conversations and User Experience in AI
13:26 Building a Powerful Open Source Engine
14:57 Building Efficient AI Agents
15:53 Challenges in Complex AI Interactions
18:09 Managing AI Safety and Control
21:10 Key Learnings for AI Project Development
22:08 Understanding Uncertainty in AI Development
25:26 Addressing Hallucinations in AI Systems
27:24 Navigating the Learning Journey in AI Development

In this conversation, Giorgio Natili discusses the significance of confidential computing in the realm of AI workflows, emphasizing its role in ensuring data sovereignty and security. He explains how confidential computing can reshape AI usage, particularly in sensitive industries like finance and healthcare. The discussion also touches on the challenges organizations face regarding data privacy and the ethical implications of AI. Natili advocates for a balanced approach where AI complements human expertise rather than replacing it, and he highlights the importance of building secure and compliant AI systems.

Sound Bites

"Data sovereignty is crucial in AI workflows."
"AI cannot replace human beings."
"The expert in the room is the human being."

Episode # 162

Giorgio Natili is a tech leader, author, and advocate for fearless leadership. With over 20 years of experience, he has led teams at companies such as Amazon, Mozilla, and Capital One.

• LinkedIn: Giorgio Natili

What Listeners Will Learn:

• Confidential computing enhances the security posture of systems.
• Data sovereignty is a critical concern for organizations using AI.
• Confidential computing allows for secure AI workflows without data leakage.
• The role of trusted execution environments is vital in protecting sensitive data.
• Organizations often face challenges with compliance and data privacy regulations.
• AI should complement human expertise, not replace it.
• Confidential computing can help organizations navigate complex regulatory landscapes.
• The importance of attestation in ensuring secure AI workflows.
• AI can be powerful when used ethically and responsibly.
• Industry applications for confidential computing include finance, healthcare, and legal sectors.

Join Kashif Manzoor as he welcomes Professor Craig Mattson to discuss the transformative role of generative AI in education. They explore how AI is reshaping teaching methods, the challenges educators face, and the opportunities for personalized learning.

Differences in student experiences over the past decade

• The role of AI in modern classrooms
• Balancing skepticism and optimism towards AI in education
• The importance of process and metacognition in teaching
• Insights from Craig Mattson's book, "Digital Overwhelm"

Session # 161

Guest: Professor Craig Mattson, researcher and educator at Calvin University, shares his insights on the evolving landscape of education and the workplace.

Connect with Craig Mattson:

Website: The Mode Switch Newsletter: Weekly work culture insights

Hashtags: #Education #AI #TeachingMethods #GenerativeAI

Call to Action: Subscribe to OpenTechTalks.tv for more insightful discussions on technology and education.

In this conversation, Jakub shares his insights on the evolution of AI in finance, emphasizing the importance of specialized AI agents and the need for a robust infrastructure. He discusses his transition from corporate life to entrepreneurship, highlighting the challenges and rewards of building a startup. Jakub also offers practical advice on team dynamics, customer acquisition, and learning AI, stressing the significance of being customer-obsessed and the need for continuous learning and adaptation in the fast-paced tech landscape.

Episode # 160

He has over 23 years of experience in IT and finance, excelling in regional leadership roles at Oracle, Microsoft, France Telecom, T-Mobile, and in hedge funds. He combines a strong scientific background from the University of Warsaw and CERN with deep tech expertise. As an entrepreneur, he has successfully launched, scaled, and exited ventures in AI/ML, MLOps, NLP, and e-commerce.

• Website: Quant Journey
• Youtube: Quant Journey

What Listeners Will Learn:

• AI in finance requires specialized agents for better results.
• Building a business around AI is more about organization than technology.
• Startup teams should balance experience with passion.
• Customer obsession is key to success in any business.
• Bootstrapping can lead to faster product development.
• Learning AI should be practical and application-focused.
• Engaging with the community can enhance learning.
• AI can automate many tasks traditionally done by humans.
• Effective leadership inspires and empowers teams.
• The landscape of technology is rapidly changing, making it easier to innovate.

• Quant Journey

The last three weeks' articles on the Generative AI adoption Maturity framework sparked discussion within the AI circle. Thank you for sharing your comments and feedback, and for sparking a few thought-provoking views on this topic.

We have begun a journey to develop a Gen AI Maturity Model or framework as a joint effort with colleagues, friends, and leadership teams from several organizations.

Earlier work:

1. ​Where Are You on the Generative AI Maturity Curve?​
2. ​Generative AI Maturity Framework for Structured Guidance​
3. ​Why Maturity matters and levels of Gen AI Maturity model​
4. ​Mapping Your Generative AI Maturity From Aware to Transformative Part 1​​

We will continue the journey this week, and part 2 covers the transition from Level 4 Integrated to Level 6 Transformative.

Part 1: Session# 158

Part 2: Session# 159

Complete details are available over here: https://www.otechtalks.tv/evaluating-your-generative-ai-maturity-from-aware-to-transformative-part-2/