Prompt injection and jailbreaks aren’t “edge cases” anymore—they’re the frontline threats shaping how we build Responsible AI. In this episode, we unpack the security reality of generative AI and large language models, and why trust must be engineered from day one.

Using guidance inspired by NIST and OWASP, we break down how prompt injection works—when malicious inputs manipulate model behavior to trigger data exfiltration, leak sensitive context, or drive unauthorized tool/actions in agentic workflows. Then we dive into real-world defenses discussed by leaders like Microsoft, Google, and OpenAI: automated red teaming, instruction hierarchies, and real-time prompt shields designed to isolate untrusted data and reduce attack surface.

You’ll learn why modern GenAI security needs a multi-layer approach: probabilistic detection paired with deterministic controls like sandboxed environments, strict permissions, and human-in-the-loop approvals for risky actions. Finally, we zoom out to the Responsible AI toolkit—continuous monitoring, transparency methods like watermarking, and collaborative bug bounty programs—to keep systems resilient as threats evolve.

If you build, deploy, or rely on LLMs, this episode is your roadmap to safer agents, stronger governance, and AI you can actually trust.

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#ResponsibleAI #AIsecurity #LLMSecurity #GenAISecurity #PromptInjection #Jailbreak #OWASP #NIST #AIRiskManagement #RedTeaming #PromptShield #SecureByDesign #AgenticAI #ToolUseSecurity #DataExfiltration #Sandboxing #HumanInTheLoop #AIGovernance #BugBounty #Watermarking

AI search is reshaping how we find information—and the business models behind it are rewriting the rules of trust. In this episode, we break down the AI Search Wars between Google, OpenAI’s ChatGPT, and Perplexity, and the high-stakes tension between monetization and accuracy.

You’ll hear how Google’s AI Overviews are expanding globally while blending sponsored ads into summaries, why ChatGPT is leaning into real-time web search plus merchant checkout and a subscription-first strategy, and how Perplexity has tested advertising concepts like sponsored follow-up questions—then pivoted toward premium subscriptions to protect credibility.

We also dig into the core risk: when AI systems chase revenue or speed, hallucinations and misinformation can spike—so what does it take to keep AI answers reliable, transparent, and accountable?

If you care about the future of search, ads in AI summaries, and whether AI can stay objective while getting paid, this episode is for you.

#AISearch #SearchWars #GoogleAI #AIOverviews #ChatGPT #OpenAI #PerplexityAI #GenerativeAI #AIAdvertising #AdTech #SubscriptionEconomy #TrustInAI #AIEthics #Misinformation #AIHallucinations #FutureOfSearch #TechPodcast #DigitalMarketing #SEO #ProductStrategy

OpenAI has launched a limited advertising pilot in ChatGPT—and it raises big questions about trust, privacy, targeting, moderation, and regulation.

In this episode, we break down what’s publicly documented: where ads appear in the UI, who sees them (and who doesn’t), how contextual vs. personalized ad selection works, what “answer independence” means, and what controls users have (hide/report, “About this ad,” ad data deletion, Temporary Chats, and the Ads-Free option with lower limits).

We also explore the key business unknowns (pricing and auction mechanics), the safety perimeter around sensitive topics, and the regulatory angles shaping conversational ads. If you’re a user, advertiser, policymaker, or product leader, this is your practical, evidence-based guide to the new era of ads inside AI chat.

#ChatGPT #OpenAI #AIAdvertising #ConversationalAI #AdTech #DigitalAdvertising #Privacy #DataPrivacy #Personalization #ContextualAdvertising #AIGovernance #TechPolicy #Regulation #TrustAndSafety #Misinformation #ScamPrevention #UserExperience #ProductStrategy #MarketingStrategy #AITrends