How Do You Build AI Products That Are Compliant Before It’s Too Late?

In this special episode of the Inverted podcast, host Dario Salice sits down with Dexter Awoyemi, an independent AI systems architect working at the intersection of AI, regulation, and product design. Together, they explore what it really means to build AI systems responsibly—before compliance becomes a painful afterthought.

Dexter introduces his philosophy of “clarity before code”, arguing that teams should start with intent, risk classification, and human oversight rather than jumping straight into models and frameworks. The conversation dives deep into the EU AI Act, including how turning complex regulations into executable knowledge graphs can help product and engineering teams reason about their obligations without reading hundreds of pages of legal text.

You’ll hear a candid discussion about:

➡️ Why human-in-the-loop is a non‑negotiable requirement for AI systems—and how it affects UX, auditability, and accountability

➡️ Common mistakes teams make when applying AI to complex reasoning and regulatory interpretation

➡️ How compliance, security, and product teams can collaborate earlier instead of acting as late-stage gatekeepers

➡️ What product teams should focus on first: risk classification, observability, and designing for failure modes

➡️ Why AI regulation, much like GDPR, is likely to become the global default—and why early compliance is not wasted work

This episode is especially valuable for product managers, engineers, and founders building AI-powered products in regulated or soon-to-be-regulated environments who want to avoid expensive rewrites, organizational friction, and downstream risk.

If you’re interested in real-world security strategies, AI security, zero trust, and the evolving challenges facing media organizations, this episode is a must-listen.

Connect with the hosts and guests with comments on the video or on LinkedIn to continue the conversation!

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