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What if your next high-performing hire never sleeps, knows your stack, and ships secure environments in hours? We dive deep with Chris Chapman CTO of MacStadium to map the shift from brittle automation to agentic AI running on fleets of Macs, where outcomes replace step-by-step scripts and digital employees take on repeatable, high-value work. Chris opens the hood on Orca, their software-defined Mac platform, and shares how customers virtualize thousands of machines to train agents, spin up secure developer workspaces, and deploy specialized small language models that thrive on Apple silicon.

We explore why early movers gain an edge: building agents around their policies and workflows instead of bending to generic tools. That means using standards like MCP and A2A for reliable tool use, embracing hybrid architectures that keep sensitive data sovereign, and bringing compute to the data rather than hauling data to the cloud. The result is practical speed: fleets that scale on demand, agents that verify progress at checkpoints, and environments that remain auditable and compliant. Add the efficiency of Apple silicon—high performance per watt, unified memory, and strong on-device inference—and you get meaningful cost control without sacrificing capability.

Security stays front and center. We unpack a security-by-design approach where agents inherit guardrails, act on alerts, remediate drift before rollout, and document every change. We also talk shop about the road ahead: M5-based clusters for training and inference, deeper graphics and AI integration in Orca, and Apple’s unique edge-to-cloud continuity that unlocks multimodal workflows from Vision Pro and iPhone to Mac mini clusters. If you’re weighing how agentic AI will reshape roles, budgets, and delivery, this conversation offers a clear blueprint: encode goals, codify guardrails, and let agents do the heavy lifting while your team moves upstream to architecture and strategy.

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What if your crypto wallet felt as safe as your bank account? We sit down with Crypto Insurer BDIC Insurance Founder and CEO Jeffrey Glusman to unpack a bold plan to bring deposit insurance to digital assets and unlock mainstream confidence. Instead of chasing whales, the model targets the everyday holder with clear, affordable coverage tiers, vetted wallets, and a focused list of insurable coins. The goal is to turn fear, uncertainty, and doubt into transparent rules and reliable protection that stands up when it counts.

We dig into how coverage works, what’s actually insured, and why solvency signals matter—sovereign fund commitments, bank guarantees, and established carriers. Exchanges are watching closely. With regulators weighing in and users demanding safety, supplemental insurance could become table stakes. Using the Bybit hack as a reality check, Jeffrey explains how an insured framework could have reimbursed most losses, protected AUM, and kept trust intact. Insurance can’t stop every breach, but it can turn catastrophic events into recoverable ones.

Education plays a starring role. We break down hot versus cold wallets, key custody, tokenization, and the small habits that prevent big losses. Jeffrey shares a painful personal phishing story and a recent large-scale fraud involving a spoofed bank and forged policies—then maps out the steps that stop most attacks: a dedicated wallet device with no SIM, no socials, no SMS 2FA; SIM locks at the carrier; $1 test transfers; and on-chain verification. Finally, we talk go-to-market: why Hong Kong and Pan-Asia come first, why Latin America is primed, and how a utility token and partner exchanges could kick off a domino effect toward industry-wide normalization.

If you care about crypto adoption, user protection, and credible risk management, this conversation brings clarity and a practical path forward. Subscribe, share with a friend who trades, and leave a review with your take: should exchanges be required to offer deposit-style insurance?

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Most AI pilots impress in a demo and stall in production. We wanted to unpack why. Joseph Kim is the President and CEO of Druid AI joins us to break down the real blockers to AI readiness and the playbook that moves teams from wow to working systems. We talk candidly about market hype, sobering stats on failed deployments, and the ingredients that make enterprise agents safe, accurate, and compliant at scale.

We start with first principles: define the business case, choose the right capability for the job, and decide if AI is even necessary. Joe draws a clean line between generative tasks and agentic tasks, explaining why a passable answer is fine for search but dangerous for automated actions. He shows how Druid engineers fidelity with background subroutines that pre-check identity, history, and likely intent, so the first response is accurate and the downstream steps are auditable. That control layer—complete logs, policy dials, and compliance hooks—turns black-box models into systems you can govern and certify.

From there, we tackle data hygiene, hallucination traps, and how to measure success beyond vanity metrics. Joe lays out a practical path: start small with a high-value workflow, track NPS, deflection rates, and accuracy, then expand into adjacent use cases. For enterprises running dozens of agents from different vendors, we dig into orchestration. Druid’s Conductor acts as a control plane that routes tasks, mediates context, and prevents lock-in, so you can swap components without burning time and budget. We close with a grounded take on the AI bubble: yes, excitement inflates expectations, but the durable gains will mirror the early internet—messy at first, transformative over time.

If you’re ready to turn experiments into outcomes, this conversation will help you align technology with ROI, design for compliance, and scale with confidence. Subscribe, share with a teammate who owns an AI pilot, and leave a review with the one blocker you want us to tackle next.

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What happens when agents can talk to agents—securely, asynchronously, and at scale? We sit down with Edward Funnekotter Chief Architect and AI Officer from Solace to unpack the architecture behind an open agent mesh and why event-driven design is the key to turning AI hype into dependable workflows. Instead of a single chatbot, imagine a network of specialized agents that advertise their skills, discover each other, and coordinate like a high-functioning team. They fetch data from Salesforce and support systems, compile a customer health report, rank the urgent accounts, and hand you the three actions that matter.

We get practical about where to start. Dynamic dashboarding and interactive analysis are low-lift, high-impact wins, and they translate smoothly into scheduled reports and triaged alerts. Using an event broker lets you subscribe to only the events you need, template them into agent requests, and run parallel tasks without disturbing existing integrations. The philosophy is simple and powerful: make LLMs do less. Reserve the model for judgment and planning, then let deterministic tools handle transformations, queries, and updates. You’ll cut latency and cost while improving reliability.

Security isn’t an afterthought. We dig into prompt injection, data leakage, and how to enforce tainted-context policies so confidential data never escapes to public tools—and external data never triggers risky internal actions. Lineage and audit trails make decisions explainable. We also explore the role of standards like A2A and MCP, why big-tech sponsorship accelerates adoption, and how open-source on-ramps paired with enterprise hardening create trust. Looking ahead, we see an AI org chart that mirrors the human one: layered roles, clear responsibilities, and shared context running on faster, cheaper infrastructure that prioritizes answer quality over raw speed.

Ready to build with confidence instead of cobbling in the shadows? Listen now, subscribe for more conversations at the edge of AI and architecture, and leave a review with the first agent workflow you’d deploy.

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The fastest way to lose a security battle is to wait for it to start. We pull back the curtain on a proactive strategy to break the attack chain—disrupting reconnaissance, lateral movement, and exfiltration—by uniting offensive testing with integrated blue team defenses that actually prove what works. John Grancarich Chief Strategy Officer Fortra, joins us to explain how red and blue can operate on a single vision that prioritizes the real prize: protecting data wherever it lives.

We dig into the AI-fueled threat surge—hyper-personalized phishing, deepfake-driven social engineering, and automated vulnerability discovery—and get specific on how to respond. John walks through a three-part AI model security of AI to safeguard gen AI pipelines from prompt injection, data leakage, and shadow tools security from AI to detect AI-powered threats with behavior-led models and security with AI to augment SOC teams by automating triage and enrichment. The result is a realistic path to faster incident response, fewer false positives, and more time for human judgment.

Data sits at the center of the story. John shares why Fortra acquired Lookout’s cloud security business and how capabilities like CASB, secure web gateway, and ZTNA now pair with endpoint and network controls to create a unified data security approach. With consolidated discovery, classification, and policy enforcement through one console, teams can spot risk sooner and stop exfiltration with less friction. We also talk culture: practical awareness programs, phishing simulations, and the simple discipline of slowing down before clicking. Finally, we look ahead to a unified platform that brings red and blue together, a new DSPM rollout, and the bold goal of enabling the 10x security engineer.

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What makes a brand unforgettable in a world drowning in content? We sit down with cybersecurity veteran and writer Tony Bradley to unpack how thoughtful analysis, consistent execution, and credible placements can move a company from invisible to influential. Tony traces his path from IT and security operations to bylines at PCWorld, TechTarget, TechSpective, and Forbes, explaining why he stopped chasing the news hype cycle and instead built a reputation around “day-two” insights that endure beyond the headline.

We dig into the most common visibility mistake—one-off content—and how to replace it with an integrated cadence that actually compounds. Tony shares a rare, practical look at what journalists say yes to: context tied to a timely story, a ready-to-use quote, and speed. No hoops, no delays. From there, we tackle the new reality of earned media in the LLM era. With ChatGPT, Claude, and Gemini shaping how people discover answers, quotes and features on credible outlets do more than drive clicks—they train the systems that now mediate attention. The more your voice appears across respected publications, the more likely AI is to surface you as a trusted source.

Still, scale without soul is noise. Tony shows how analogies translate complex security concepts for any audience and why genuine thought leadership requires a point of view, not a summary. We explore the craft of ghostwriting executive content that sounds like the executive, not the writer, and the discipline it takes to avoid repeating the same safe takes on agentic AI and identity security. We also walk through a pragmatic stance on AI: leverage it as a force multiplier for research, editing, and distribution, while keeping human judgment on narrative, nuance, and trust.

If you care about cybersecurity storytelling, PR strategy that works, and how to be cited where AI looks first, this conversation is your field guide. Subscribe, share with a teammate who handles comms, and leave a review with your biggest earned-media challenge—we might tackle it next.

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Noise is the enemy of good defense. We sit down with Jawahar Sivasankaran President of Cyware to unpack how a threat-centered architecture, powered by agentic AI and rich collaboration, can turn scattered data into clear, prioritized action. Rather than adding yet another dashboard, the strategy puts high-fidelity intelligence at the core of the SOC so every control—detection, response, and exposure management—makes smarter moves, faster.

We trace the evolution from a classic TIP to unified cyber risk intelligence, where enrichment, STIX-based normalization, and context from compromised credentials, domain sightings, and digital risk protection reshape triage. You’ll hear why many enterprises still drown in alert fatigue, how agent frameworks outperform simple LLM wrappers, and what it takes to route Tier 1 work to autonomous agents so analysts can focus on adversary mapping, hunting, and enterprise risk decisions. The result: measurable reductions in mean time to detect and respond, plus clearer board reporting on actors, TTPs, and shifting exposure.

Trust and speed also come from the community. We dig into bidirectional sharing with ISACs and focused sector hubs, and how downstream organizations with limited staff can turn shared intel into executable actions, not just headlines. We explore the twin pillars of AI for security and security for AI—covering model and agent risks, governance, and the practical wins of AI-driven SOC transformation. Finally, we look ahead at strategic partnerships and a platform approach that pushes beyond legacy TIP capabilities to meet how attackers operate today.

If you’re ready to cut the noise, put intelligence in the driver’s seat, and let agents handle the grind, this conversation offers a clear blueprint. Subscribe, share with your team, and leave a review with your biggest alert-fatigue challenge—we’ll tackle it in a future show.

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The lock icon is not a comfort blanket. It’s a contract. We sit down with Chris Hickman, Chief Security Officer at Keyfactor, to unpack what digital trust really means when every person, device, app, and service needs a verifiable identity. From the browser to the factory floor, PKI and certificate management quietly power secure connections, and when they fail, the business feels it fast. Chris pulls back the curtain on the policies, processes, and automation that keep identities reliable at scale—and why “crypto agility” is no longer a buzzword but a survival trait.

Quantum is no longer a sci‑fi subplot; it’s a timeline. With NIST guiding the retirement of RSA and ECC by 2030–2035 and global regulators aligning, organizations face an infrastructure‑level migration. Chris lays out a practical path: start with a full cryptographic inventory, assess risk to long‑lived data vulnerable to harvest‑now‑decrypt‑later attacks, standardize on TLS 1.3, and pressure vendors for post‑quantum roadmaps. We also tackle an accelerating reality: publicly trusted certificates shrinking toward 47‑day validity. Without automation, renewal cycles explode, toil multiplies, and outages become inevitable—making the ROI for certificate lifecycle management crystal clear.

Regulation and sovereignty add another layer. We cover DORA in the EU, evolving PCI requirements, and regional flavors of cryptographic standards that challenge compatibility. Then we look ahead to agentic AI, where identity at machine speed pushes PKI to new limits. The takeaway is simple: strong foundations—inventory, governance, and automated issuance and renewal—enable resilience, while brittle manual processes crack under pressure. If you lead security, architecture, or compliance, this conversation gives you a blueprint to build trust that lasts through quantum shifts, regulatory change, and AI scale.

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Want proof that better IT experience can be engineered, not wished into existence? From the floor at Gartner, we sit down with Lakeside to explore how a lightweight, 29‑year-old agent design built for scarcity is suddenly perfect for today’s edge. When compute, memory, and network were expensive, the team designed a platform that sips resources, keeps data close to the device, and structures it cleanly. That constraint-driven approach unlocks speed, privacy, and resilience for modern fleets spread across remote and hybrid work.

We dig into how first‑party endpoint telemetry becomes actionable insight: structured SQL tables that AI can query without guesswork, a built-in server that responds to natural language, and clear answers to everyday pain like “Why is Outlook slow?” Instead of sifting through noisy logs or waiting on remote sessions, IT can see patterns, correlate changes, and resolve issues before they cascade. The payoff shows up in the metrics executives care about—lower MTTR, fewer escalations, and help desk costs cut by up to 50 percent. Just as important, employees feel the difference in fewer slowdowns and faster recovery.

There’s a practical path to proactive support: detect drift early, isolate risky cohorts, and push targeted fixes across the fleet. By keeping much of the data local and imposing a consistent structure, Lakeside shortens the path from question to answer while preserving performance on the endpoint. That makes scale manageable and ROI visible, which resonates with the “bosses of the bosses” walking the Gartner halls. If you’re wrestling with sprawl, inconsistent tooling, or elusive root causes, this conversation shows how to turn devices into their own best administrators and turn IT data into durable advantage.

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Patch Tuesday shouldn’t feel like roulette. We sat down at Gartner Symposium with Egan from NinjaOne to explore a simple, disciplined idea: beat IT misery with speed, clarity, and trustworthy automation. Guided by decades in the DoD and intelligence community, Egan frames endpoint management as an operational craft where time-to-value, clean data, and risk-aware decisions matter more than shiny features. That lens drives concrete outcomes—deployments that go live in days, ROI signals within 24 hours, and onboarding that turns new admins productive in days instead of months.

We dig into pragmatic AI that actually helps the person doing the work. Patch sentiment intelligence aggregates global signals so teams can prioritize, stage, or defer updates with confidence, reducing outages and ticket spikes while maintaining security. Under the hood, AI-assisted asset data curation cleans messy inventories, improving patch targeting, vulnerability accuracy, and compliance reporting. When the data is right, every downstream action—from rollout plans to rollback analysis—gets faster and safer.

We also break down a partner-first go-to-market built for scale. Starting in the MSP world and expanding across mid-market, enterprise, and public sector, NinjaOne relies on certified services partners for deployment and operations. That rigor creates predictable rollouts, preserves institutional knowledge, and aligns incentives so customers see results quickly. The payoff is practical: fewer tools to manage, less training overhead, and a clearer path to automation that junior and senior admins alike can trust. If your team is under pressure to do more with less, this conversation offers an actionable blueprint for stability and speed.

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