In this episode, we take a hard look at how AI is being integrated into cybersecurity—and where the narrative often diverges from reality. The discussion spans offensive and defensive use cases, the structural challenges facing SMBs, and why open-source cyber threat intelligence (CTI) remains a critical foundation despite aggressive vendor marketing.

We also explore the economic pressures shaping today’s security market, including broken pricing models, unrealistic expectations placed on small teams, and the growing gap between compliance optics and real risk reduction. The episode concludes with a forward-looking discussion on applied machine learning, mathematical modeling, and how these approaches can meaningfully support incident responders in the field.

• Practical applications of AI in cybersecurity operations

• Offensive vs. defensive AI tradeoffs

• The SMB security gap and market failure

• Open-source CTI as a force multiplier

• Pricing models and market distortion

• Applied ML and mathematics for real-world incident response

• Product direction and long-term vision

• 00:00 — Introduction and company overview

• 38:10 — Pricing models, market dynamics, and systemic issues

• 39:26 — Future plans, roadmap, and strategic vision

• 52:00 — AI in offensive and defensive cybersecurity operations

• 58:54 — Open-source CTI and applied AI capabilities

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