Cybersecurity has never been more critical, yet organizations still struggle to explain its real value in business terms. Security teams process millions of alerts, deploy dozens of tools, and spend billions globally, but breaches continue to happen.

In this episode of The CTO Show with Mehmet, serial tech entrepreneur Mike Armistead, CEO and Co-Founder of Pulse Security AI, joins Mehmet to explore how AI agents and context-driven systems could fundamentally reshape cybersecurity leadership.

Mike shares lessons from four decades in technology, from the rise of personal computers and early internet companies to today’s AI wave. The discussion dives into why cybersecurity tools have historically failed to communicate value to business leaders, how attackers are already using AI to their advantage, and why the next generation of cybersecurity platforms must translate technical signals into clear business risk insights for executives and boards.

The conversation also explores the concept of “context graphs,” agentic AI systems, and the idea of a modern security system of record designed specifically for CISOs.

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About the Guest

Mike Armistead is a serial technology entrepreneur and cybersecurity innovator with decades of experience building category-defining companies.

He is currently the CEO and Co-Founder of Pulse Security AI, a company focused on helping security leaders translate complex cybersecurity signals into meaningful business risk insights using AI and agentic systems.

Earlier in his career, Mike co-founded several successful technology companies including Response Software and Fortify Software, contributing to major advancements in application security and AI-driven security operations.

With more than 40 years in technology, Mike has witnessed multiple platform shifts including the rise of personal computing, the internet, cloud computing, and now the AI revolution.

Connect with Mike: https://www.linkedin.com/in/mike-armistead-1164715/

Episode Highlights

• Mike’s journey through multiple technology waves and startup successes

• Patterns that repeat across major technology revolutions

• Why cybersecurity markets became fragmented with dozens of specialized tools

• The role of context graphs and agentic AI systems in future security platforms

• How attackers are evolving their strategies using AI

• Why organizations must rethink cybersecurity prevention strategies

• Advice for founders looking to build companies in emerging technology categories

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Timestamps

00:00 – Introduction and welcome

01:00 – Mike Armistead’s background and technology journey

03:00 – Patterns across major technology waves

07:00 – Why cybersecurity tools struggle to communicate business value

10:30 – The fragmentation problem in cybersecurity technology stacks

13:30 – Translating cybersecurity signals into business risk

16:30 – Context graphs and the role of AI agents

20:00 – Should humans remain in the cybersecurity decision loop?

23:00 – Where AI will have the biggest impact in cybersecurity

27:00 – What a modern security “system of record” could look like

31:00 – AI-powered attackers and the new cybersecurity arms race

35:00 – Prevention vs detection in modern cybersecurity strategy

41:00 – Advice for founders building cybersecurity companies

47:00 – Where to learn more about Pulse Security AI

49:00 – Closing remarks

Resources Mentioned

• Pulse Security AI: https://pulsesecurity.ai/

As AI rapidly reshapes how software is built, technology leaders face a growing tension between speed and security. Development cycles are accelerating thanks to generative AI tools, while cybersecurity teams are struggling to keep pace with new risks introduced by AI-generated code, autonomous agents, and evolving cloud architectures.

In this episode, Mehmet speaks with Ben Wilcox, CTO and CISO at ProArch, about how modern technology leaders balance innovation with risk management. The conversation explores the convergence of engineering and security leadership, the maturity gap in DevSecOps adoption, the implications of AI-assisted development, and the governance challenges organizations must address as AI becomes embedded in enterprise applications.

Ben also shares insights on secure-by-design engineering practices, the changing role of CTOs, and why AI governance and visibility will become critical priorities in the near future.

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About the Guest

Ben Wilcox is the Chief Technology Officer and Chief Information Security Officer at ProArch, where he leads technology strategy, cybersecurity initiatives, and enterprise architecture efforts. With more than two decades of experience across infrastructure, cloud technologies, and software development, Ben has built a career at the intersection of engineering and security.

Over the years, he has helped organizations modernize their technology stacks while maintaining strong security and governance practices. His work focuses on secure cloud architectures, DevSecOps transformation, and helping businesses safely adopt emerging technologies such as AI.

Connect with Ben on LinkedIn:

https://www.linkedin.com/in/ben-wilcox/

Learn more about ProArch:

https://www.proarch.com

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Key Takeaways

• The traditional divide between engineering and security teams is fading as organizations increasingly merge CTO and CISO responsibilities.

• AI-assisted development is dramatically increasing the speed of software creation, creating new challenges for security teams.

• DevSecOps adoption remains immature in many organizations despite widespread awareness of the concept.

• Secure-by-design engineering requires clear guardrails and well-defined development pathways for teams.

• AI-generated code should be treated like work produced by a junior developer or intern and still requires human review.

• AI governance and visibility will become a major priority as organizations deploy AI agents across business processes.

• CTOs must develop both technical foresight and strong business alignment to guide organizations through rapid technological change.

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What You Will Learn

In this episode:

• How organizations can balance rapid development with cybersecurity requirements

• Why DevSecOps still struggles to deliver on its promise

• The risks and realities of AI-generated code in modern development

• How secure-by-design engineering works in practice

• The architectural considerations when integrating AI into enterprise applications

• The governance challenges created by AI agents and evolving LLM ecosystems

• The skills future CTOs need to remain relevant in an AI-driven technology landscape

Timestamps

00:00 Introduction and guest welcome

01:00 Ben Wilcox’s background and career journey

03:00 The challenge of combining CTO and CISO responsibilities

06:00 Balancing development speed with cybersecurity risk

07:30 AI-driven development and the new security challenges

10:00 What “secure by design” really means in engineering

14:30 DevSecOps adoption and maturity challenges

18:00 AI adoption in organizations: productivity vs product integration

22:00 AI-generated code, intellectual property, and governance risks

27:00 Architecture considerations for AI-driven systems

32:00 Data sovereignty, cloud strategy, and AI infrastructure

34:00 Skills the next generation of CTOs must develop

40:00 Emerging trends in AI governance and security

45:00 Where to connect with Ben Wilcox

Enterprise transformation rarely fails because of strategy. It fails because of execution, and one of the most complex parts of execution is data migration.

In this episode, Mehmet speaks with Dominik Wittenbeck, CTO at SNP, about the real mechanics behind SAP transformations and why data migration is often the most underestimated phase of enterprise modernization.

They explore how organizations approach SAP migrations, the risks of underestimating data transformation projects, and why Selective Data Transition (SDT / Bluefield®) is becoming a preferred strategy for many enterprises.

The conversation also dives into how AI is beginning to reshape large-scale IT transformation projects, from presales and planning to testing and root cause analysis. Dominik shares practical insights on how AI can augment consultants rather than replace them, helping organizations manage increasingly complex system transformations with greater speed and accuracy.

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About the Guest

Dominik Wittenbeck is CTO at SNP Schneider-Neureither & Partner SE with over 20 years of experience in SAP-centric enterprise transformations. His focus is Selective Data Transition (SDT / Bluefield®) and scaling scarce migration expertise through structured methods and AI-supported orchestration.

Connect with him on LinkedIn:

https://www.linkedin.com/in/dominik-wittenbeck-61a64669/

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About SNP

SNP is a global software and consulting company specializing in data transformation, system landscape modernization, and SAP migrations. With its Kyano® platform, SNP enables complex transformations in a structured, rule-based, and scalable way.

More:

https://www.snpgroup.com/

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Key Takeaways

• Data migration is often the most underestimated element of digital transformation projects.

• Selective Data Transition (SDT / Bluefield®) offers a middle ground between greenfield implementations and full system conversions.

• AI can significantly accelerate presales, documentation, and root cause analysis in complex IT transformations.

• Automation and AI are augmenting consultants rather than replacing them, enabling teams to manage more projects at scale.

• Structured transformation platforms and methodologies are becoming essential as enterprise change accelerates globally.

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What You Will Learn

• Why SAP migrations remain one of the most complex enterprise IT initiatives

• The differences between greenfield, brownfield, and selective data transition approaches

• How AI is being used today in data migration planning and execution

• The hidden risks that organizations face when migration projects are underestimated

• How enterprises can scale transformation expertise despite the shortage of experienced consultants

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Episode Highlights (Chapters)

00:00 Introduction and Dominik’s background

01:00 Why data migration expertise is scarce

05:00 Why migration projects often scare IT teams

09:00 Misalignment between IT and business in transformation projects

14:00 What Selective Data Transition (Bluefield®) means

18:00 The biggest risks when data migration is underestimated

21:00 Where AI is already helping transformation teams

27:00 How AI improves project handovers and knowledge transfer

30:00 Ensuring deterministic and auditable data transformations

33:00 Using AI for root cause analysis in migration projects

36:00 MCP servers, agents, and AI orchestration

38:00 AI-powered testing and validation

41:00 The knowledge loss problem in consulting projects

45:00 The future of AI in enterprise transformation

48:00 Will AI replace consultants? Dominik’s perspective

52:00 Staying relevant in the age of AI