The Hidden Blind Spots of AI: A CTO’s Perspective

Show Notes

As AI accelerates software development, security can no longer operate as a gate at the end of the pipeline.

In this episode of Secure by Design, Bill Weinberg sits down with Adi Kavaler to explore how AI is fundamentally changing engineering velocity and why security must evolve alongside it.

The conversation dives into the real‑world impact of AI‑first development: faster time to market, cross‑functional feature teams, and the breakdown of long‑standing friction between builders, developers, and security.

Rather than slowing innovation, embedded security and intelligent triage enable teams to ship faster and safer.

This session also examines the limits of today’s AI tools: from missing context to production blind spots, and why human oversight, guardrails, and multi‑model validation remain essential.

The result is a pragmatic look at how modern organizations can balance speed, quality, and trust while navigating AI‑generated code at scale.

• AI dramatically increases engineering velocity, but only when security is embedded from day one
• Friction between development and security disappears when teams operate as a single feature unit
• AI‑assisted triage helps eliminate noise and prioritize the vulnerabilities that truly matter
• Consolidated, normalized data is essential for effective AI‑driven security decisions
• AI‑generated code still requires human context, validation, and accountability
• Using multiple AI models and guardrails improves confidence—but comes with cost tradeoffs
• AI excels at pre‑production security, while post‑production reasoning still needs careful oversight