Join your hosts, Anton Chuvakin and Timothy Peacock, as they talk with industry experts about some of the most interesting areas of cloud security. If you like having threat models questioned and a few bad puns, please tune in!
What is the state of the art of “agentic SOC” in 2026? Can you describe the most agentic SOC you've seen so far?
In your experience, what are the main measurable benefits of AI agents in a SOC and for IR?
Imagine a 2030 SOC, what do humans do?
How you judge if a client SOC is ready for AI and agents? What is the "Ouch" moment where most organizations realize their data isn't ready for that level of autonomy?
Should we be more afraid of "AI hallucinations" or "Human fatigue" in the SOC?
If a team has an agentic teammate making its own decisions based on emergent reasoning, how do you audit its "thought process"?
Everyone loves to talk about "Time Saved," but in an agentic SOC, we care about "Decision Quality." What is the one metric PwC uses to prove that a SOC agent deployment is actually reducing risk?
We often hear about "human-agent teaming." Are they still looking at alerts, or are they just approving "Action Plans" generated by the AI?
Most people do not associate grocery wholesale and retail with cutting edge technology and threat models. Can you produce the receipts for why this isn’t a story of dry goods but rather a very meaty topic with beefy adversaries?
How are you as the CISO enabling C&S’s journey into AI and LLM driven work? Securing AI is a bit harder than securing classic analytics tools, right?
In addition to securely rolling out AI, how is your defense team using AI to secure C&S? Are you into the era of agentic triage and response? What metrics for AI is your D&R lead surfacing up to you?
You have AI in the business process that - if failed - will leave people hungry. How do you approach AI resilience?
How do you approach resilience in general? Is cloud part of your resilience strategy?
You worked at Citigroup for a long time. What’s it like having grocery margin budgets for security instead? How does your thinking change? Does this shift your build/buy/outsource for security?
If your IoT stack falls over, you’ve got literal ice cream melting in a warehouse. How do you balance your investments in cyber risk with physical operational risk? Should I be scared of forklifts?
Is AI just an emerging technology or something bigger, deeper and different? Is this another emerging technology or a fundamental shift?
How to effectively govern something that is rapidly changing at unprecedented velocity? We navigated the governance of the Internet and SaaS. What makes AI governance fundamentally different from the "Classic IT" or Data Governance models of the past?
As we move toward Agentic AI, the line between tool and teammate blurs. Should we be governing AI agents through the lens of Technical Controls or Human Resources and behavioral contracts?
What if we hand even more responsibility to AI? Where are the tipping points as we shift from assistance to autonomy?
How to avoid unintended, negative consequences when setting policy, contrasting risk-based vs. rights-based regulation and regulatory expectations
Give us some practical takeaways for a defensible AI program - if an organization had to defend its AI program to a regulator or a judge tomorrow?
Any closing loops for our 2023-2025 Cloud Next observations?
We are seeing that AI security is not an island ... what does that tell us about the difference between cloud and AI adoption?
What does “ragged edge of AI adoption” mean for security?
Why do people want agents in their SOC? Do they know what gets better?
What are the most notable and fun announcements?
With patching speed, are we looking at something which can be overcome by engineering and courage? Or are we looking at something that is truly an impossibility?
Why is the "Secure-by-Design" movement gaining so much momentum now, and is it a response to the failure of "bolted-on" security, or just a natural evolution of cloud maturity?
In a future Secure-by-Design world, is identity the only perimeter that actually matters anymore? Or is this a cliche?
As we move toward a world of autonomous agents, how does our approach to machine identity need to change? Are we just talking about more complex Service Accounts, or do we need a fundamental shift in how we authorize "intent"
What is your advice to people who want to move fast and cannot wait for Secure by Design / Default AI to be decided by consensus or IETF, NIST or OASIS committee?
We love the argument that modern AI agents are effectively repeating the mistakes of 1960s payphones - mixing the data plane and the control plane. What is your rebuttal? How do we build "Agentic Security" that doesn't fall for 60-year-old traps?
Customers are torn between their Zero Trust implementations and their AI adoption. Is Zero Trust now "legacy," or is it the prerequisite for everything we’re trying to do with AI agents?
Is there Zero Trust for AI? Is this a fake buzzword or technical reality?
Is Network Detection and Response (NDR) coming back after being shoved to the side by EDR a bit? Is this for real?
What's the value proposition of NDR in 2026, because some people still don't understand it? How does NDR apply to the world of WFH, cloud/SaaS, encryption, high bandwidth, etc?
Is the value of NDR the same, or different, when it comes to public (or private) cloud?
How does NDR fill visibility gaps that identity and agent-based solutions cannot?
What does NDR offer that built-in cloud security tooling (as of right now) does not? Would you call NDR a key cloud security control?
“10X SOC” sounds great. But for an organization stuck in "SIEM 1.0" with poor data quality and manual workflows, is “AI-native MDR” a "leapfrog" opportunity or a recipe for disaster?
We’ve seen the rise of "Decoupled SIEM" and security data lakes. Does a "Modern SIEM" even need to exist if an MDR platform has an agentic layer doing the heavy lifting?
You’ve argued for AI-native over AI-bolted-on. For an end user, what are the tangible differences of using "AI inside a legacy SIEM" versus using an "AI-native separate product"?
What is the one task you thought AI would handle by now that still requires a senior human analyst to step in?
If a CISO is using an AI MDR, "Mean Time to Detect" (MTTD) starts to look like a vanity metric because the machine is instant. What is the new golden metric for an AI-powered SOC? Is it "Time to Context," "Reduction in Human Toil," or something else?
How do you help a skeptical SOC Manager—who has been burned by false positives for a decade—trust an autonomous agent to perform a "containment" action at 3:00 AM?
We just saw a security tool (Trivy) get used to pop an AI infrastructure tool (LiteLLM) to eventually pop end users. Have we reached the point where our security tooling is actually our largest unmanaged attack surface?
Why now? Software supply chain security had the perennial vibe of “not top concern” for most organizations, right?
TeamPCP pushed malicious code to existing GitHub tags. We’ve been screaming about pinning versions to SHAs for years, but clearly, nobody is listening. Is it time to admit that 'convenience' is the primary enemy of supply chain security?
The Axios incident showed a victim compromised in under two minutes. In a world of auto-updating dependencies, is the concept of a human-in-the-loop for software updates officially dead, or do we need to look very hard at version pinning and such?
With XZ Utils case, we saw a long-game social engineering attack. Beyond just 'watching npm closely,' what are the realistic architectural safeguards for an org that knows they can't audit every line of an update?
We’ve spent the last three years talking about SBOMs (Software Bill of Materials) like they were a pill for supply chain health. But if the scanner producing the SBOM is the one that's compromised, isn't the SBOM just a signed receipt for your own house being on fire?
What is the one practical thing they can do to ensure their CI/CD isn't a credential-exfiltration-as-a-service platform?
