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Autonomy in telecom sounds like a pure technology race until you look at where operators actually get stuck. It turns out the models aren't the bottleneck. The humans around them are.
We're joined by @Ibrahim Eldeftar, who leads Cognitive Software and Services at Ericsson, to unpack the real path from partial automation to Level 4 autonomous networks, and why the hardest part is often the human system around the tools.
Ibrahim walks us through the two hurdle categories every CSP runs into. The first is the technology foundation: multi-vendor support, scalable AI platforms, data management, deployment at scale. The second is the organizational side: change management, upskilling, new ways of working, and breaking down silos that have been cemented in place for decades. The industry keeps underestimating that second category, even when the AI roadmap looks finished on paper. Ibrahim explains why, and what it actually takes to move an operator forward.
From there we get concrete. rApps and a service management and orchestration platform can replace the fragmented automation stack most operators are living with today, giving teams a common SDK, consistent interfaces, and an ecosystem model where operators build apps themselves or source them from partners. Ibrahim shares real proof points from live networks, including modernizing worst cell hunting with AI anomaly detection and root cause analysis, and taming massive MIMO complexity where the search space is simply too large for humans to tune in any reasonable timeframe.
Then we get into what changes when GenAI and agentic coordination enter the picture on public cloud with AWS. Natural language "talk to the network" interfaces. Orchestrating dozens of RApps at once. A shift toward RApps as a service and SaaS delivery, where operators pay for outcomes rather than software licenses.
Subscribe for more deep dives on telco AI and network automation, share this one with a colleague who's living the automation grind, and leave a review if it landed. And think about this while you listen. What would you automate first if you could truly trust the outcome?

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Identity is where the fight is moving fastest, and RSAC 2026 proved it. Fresh off the show floor, we sit down with Jim Taylor, President, Chief Product and Strategy Officer at RSA Security, to break down what’s truly changing in identity security as AI reshapes both the threat landscape and the defenses enterprises rely on.

We dig into why “sovereign” and “deploy anywhere” identity deployments are suddenly mission critical. Cloud convenience can quietly trade away resiliency and control, and recent disruptions show how quickly authentication outages can become business outages. Jim explains what customers are asking for now: the same identity platform capabilities whether it runs as SaaS, in a private cloud, on-prem, or in highly constrained environments where failure is not an option.

Then we get practical about modern identity attacks beyond phishing. If passkeys and phishing resistant MFA harden the front door, attackers pivot to the session with token theft, adversary-in-the-middle scams, and help desk bypass that exploits people and process. We also explore agentic AI and the rise of non-human identities, including how to inventory agents, set entitlements, and apply identity governance so “mini workers” don’t inherit unlimited permissions.

We close with a grounded take on passwordless authentication as a step-by-step journey and what we hope the industry looks like by RSAC 2027 and 2028. If this helped you rethink IAM strategy, subscribe, share with your security team, and leave a review. What identity risk are you most worried about right now?
The Climb with Cherie Clonan
The Climb is a podcast for people building something meaningful and finding their..
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Agentic AI is no longer a side experiment running in a lab. It’s starting to look like the next operating layer inside the enterprise, and that raises a hard question: do you want a scattered collection of point tools, or a standardized agentic operating system that your teams can actually run?

I sit down with Anurag Gurtu Chief Executive Officer @ AIRRIVED to unpack what “agentic OS” means in practical terms. We get specific about the three pillars that make agentic AI useful at scale: adapting a language model to your enterprise data, adding deep reasoning so it can synthesize and rationalize like a real analyst, and then deploying autonomous agents to take controlled action. We also dig into real enterprise cybersecurity needs across security operations, identity management and governance, risk, compliance, vulnerability management, and the growing challenge of shadow AI.

We zoom out to the messy reality of adoption: too many pilots, too many vendors, and too many tools designed for developers instead of practitioners. Anurag explains why objective-driven automation beats brittle playbooks, why governance and auditability have to be built in, and how fast proof-of-concepts can turn “AI hype” into measurable ROI. We also touch on open source momentum and why Arrived is building in a more secure, governed direction with Etherclaw.

If you’re building an enterprise AI strategy, leading a security program, or trying to prove value beyond demos, this conversation will sharpen how you think about standardization, productivity, and control. Subscribe, share this with a colleague, and leave a review with the biggest hurdle you’re facing in adopting agentic AI.
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AI is everywhere in IT operations right now, but most sysadmins don’t need more buzzwords. We need fewer tickets, cleaner patching, faster deployments, and a clear view of what’s happening across every device. That’s why we sat down with Jaren Nichols, President and COO of PDQ to talk about modern enterprise device management the way admins actually live it: too many endpoints, too many apps, constant updates, and zero tolerance for security gaps.

We get into the real pressure point behind “software sprawl” as every department adopts new tools, including AI-driven apps, and IT inherits the responsibility for uptime, support, and security. Jaron breaks down three practical places AI can help right now: faster how-to research, smarter reporting that surfaces outdated versions and risks, and higher-level support for creating policies and workflows. We also dig into the part that matters most when automation gets powerful: transparency. If you can’t see permissions, execution order, and outcomes, you’re building a black box that will fail at the worst time.

From there, we zoom out to the bigger trends shaping endpoint management and AIOps: the shift toward a single pane of glass, the consolidation of roles across Windows, Mac, networking, DevOps, and security, and why legacy tools won’t disappear as fast as people claim. We close with what the next generation of sysadmins looks like when things go right: more visibility, policy-driven objectives, and faster execution without sacrificing control.

Subscribe for more conversations like this, share the episode with the admin who owns patch Tuesday, and leave a review if it helped. What’s the biggest “this shouldn’t be that hard” moment in your IT environment right now?
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The martech stack used to feel complicated. Then generative AI showed up and turned “complicated” into “constantly changing.” We sit down with Scott Brinker, the analyst behind ChiefMartec, to unpack what’s really happening as marketing teams move from a familiar martech stack to a broader AI ecosystem filled with new tools, copilots, and early stage agents layered on top of the systems we already depend on.

We get concrete about what still anchors modern marketing technology: a system of record for customer data (CRM in many B2B orgs and often a CDP in B2C), a platform for orchestration through marketing automation and messaging, and a web layer like a CMS or DXP. From there, the stack diversifies fast based on industry, maturity, and team bandwidth, which explains why some organizations can experiment aggressively while smaller teams are still holding marketing ops together with sheer willpower.

From a leadership angle, Scott makes a blunt point: you can’t automate what you can’t define. If you want AI automation that protects authentic brand voice, you need clear guardrails, documented standards, and real ownership, not vague “it’s in our culture” assumptions. We also look ahead to a shift that may surprise a lot of marketers, AI used by customers, including AI search behavior and the possibility of inbox agents that reshape email marketing and customer engagement.

If you care about AI strategy, marketing operations, martech governance, and what skills the next generation of marketing leaders will need, this conversation will sharpen how you think. Subscribe, share this with a marketing leader who’s drowning in tools, and leave a review with the biggest AI change you’re navigating right now.
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