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Networks don’t “run themselves” by magic, they do it by stacking the right data, platforms, and automation logic until the network can sense trouble, reason about options, and act safely. We sit down with Rodrigo from Ericsson to unpack what autonomous networks really mean in practice: self-healing, self-optimizing, and self-configuring capabilities that reduce operational effort for communication service providers while improving quality of service for all of us using mobile networks every day.

From there, we get concrete about how you scale automation beyond isolated point solutions. Rodrigo explains how an open service management and orchestration (SMO) approach, rooted in O-RAN concepts, creates a common platform where multiple automation apps can run side by side. Think R apps for RAN automation, a growing ecosystem, and the governance needed to make AI-driven changes trustworthy. We talk about why trusted, granular, low-latency data matters so much, and why “built for AI” is more than a slogan when you’re operating a live 5G network.

The big news is the move from radio automation into core network automation, introducing C apps and the kinds of high-impact use cases operators care about most: anomaly detection, root cause analysis, proactive fixes, capacity forecasting, and premium experience. We also dig into agentic AI and why it changes the game from automating single tasks to automating entire workflows, with human guardrails, permissions, and runtime knowledge to keep reliability high.

If you care about 5G, RAN automation, core network automation, SMO, O-RAN, or agentic AI for network operations, this conversation is for you. Subscribe, share this with a colleague, and leave a review with the one network workflow you wish could be fully automated.

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A major deal just landed in cloud communications: CallTower is acquiring Momentum Telecom. We sit down with William Rubio right after the news to explain what CallTower actually does as a managed service provider, why this acquisition matters, and what customers and partners should expect next. If you’ve ever wondered why the communications industry keeps consolidating, or how providers stitch together Microsoft, Cisco, and Zoom into something businesses can actually run, this conversation puts real clarity around it. 

We also get honest about the problem most teams are living with: too much choice and too much complexity. Unified communications, contact center platforms, CRM integrations, compliance needs, and even legacy requirements like analog lines can turn a “modern stack” into a support nightmare. We talk about why a one-stop shop model can cut the time wasted on vendor finger-pointing, and why experienced support and solution architects matter when the environment is both global and regulated. 

Then we zoom in on AI with a practical lens. The biggest wins are showing up in contact centers through interactive virtual agents, agent assist, analytics, and transcription that turns messy call notes into clean summaries fast. We also explore where AI is heading in UC: personal-assistant style workflows that can schedule, message, and route calls without the usual back-and-forth. The thread that ties it together is outcomes over features: efficiency, productivity, lower costs, and happier employees who are less burned out by broken processes. 

If you care about telecom consolidation, CCaaS, unified communications, AI in customer experience, and the evolving role of channel partners, hit play. Subscribe, share this with a teammate, leave a review, and tell us: what part of your communications stack would you simplify first?

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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Resumes are getting easier to generate and harder to trust and that is forcing HR teams to rethink how hiring works from the ground up. We sit down with Navneet “Nav” Singh the Chief Marketing Officer (CMO) at Eightfold AI. Nav from Eightfold to explore what happens when AI agents enter talent acquisition, not as a gimmick, but as a skills-first system designed to match people to roles based on capability, potential, and learnability. If you care about the future of work, hiring fairness, or scaling recruiting without burning out your team, this conversation gets specific fast. 

Nav breaks down how Eightfold built a deep skills engine, including a massive skills catalog and career trajectory data, then used it to power vertical AI for HR. We talk about why verticalized intelligence matters even in a world full of powerful general-purpose models, and how this approach can improve outcomes like retention and promotability. You will also hear real examples of AI interviewer agents helping companies move from application to hire in days, opening interview access on evenings and weekends, and giving every candidate a consistent shot to show what they can do. 

We also dig into internal mobility and workforce planning, including how a talent marketplace can uncover hidden strengths inside an organization and keep people growing instead of leaving. On the tech side, we discuss how AI can live alongside legacy HR systems like Workday, SAP, and Oracle as a “system of intelligence”, plus what changes when resume-only hiring collides with impersonation, fake candidates, and AI-written applications. If you find this useful, subscribe, share it with a hiring leader, and leave a review with your biggest question about AI agents in HR.

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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Everyone is flipping on Microsoft 365 Copilot and AI agents, and then realizing they can’t answer a basic question: what data can those agents actually reach? We sit down with Rick from Veeam to unpack the messy reality behind “safe AI at scale” and why AI success starts with data resilience, not demos. When agents can search, summarize, move, and delete content at machine speed, the cost of unclear permissions and unmanaged data sprawl spikes overnight.

We dig into ROT data (redundant, obsolete, or trivial) and why it shows up in every organization, even the ones that think they’re clean. Rick explains how “toxic combinations” form when obsolete content mixes with sensitive data or when excessive access meets automated workflows. The result can be a disaster within a disaster: a security incident plus exposed data that should never have been available in the first place. We also talk practical mitigation strategies like archiving to lower cost, reduce exposure, and prevent bad inputs from tainting AI outputs.

From there, we zoom out to day two operations: what happens when auditors show up, when an AI agent goes rogue, or when someone needs to restore what got deleted. Rick shares what Veeam is building around intelligent resilience operations for Microsoft 365, why context-rich visibility matters, and how Veeam fits alongside Microsoft’s expanding native governance and security roadmap. We wrap with a preview of the VeeamON Global Launch Virtual Event on October 15, including the vision and product updates the team will share.

If you’re rolling out Copilot, building agents, or just trying to keep Microsoft 365 under control, subscribe, share this with your admin team, and leave a review with the one AI risk you’re most worried about.

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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AI is forcing a hard reset in telecom, and it’s not just about models or GPUs. The real shockwave hits the CIO’s mandate: reinvent IT fast enough to enable enterprise AI while still keeping the lights on across sprawling legacy stacks. We sit down with TM Forum leader and veteran CIO Willie Stegmann to break down why this moment feels different from past digital transformation and cloud migrations, and why boards are pushing for measurable impact rather than more pilots.

We get specific about the economics: AI doesn’t come for free, and many executive teams are telling CIOs to self-fund it. That turns AI into both the goal and the lever, using automation inside IT to create budget headroom for broader customer experience and business transformation. From there, the conversation moves into what actually blocks scale in real operators: culture, process change, leadership intent, and the very human question of “what happens to my job?”

We also unpack where momentum is building right now, from autonomous networks and intent-based operations to customer contact centers and the rise of AI agents as “machine customers.” Composable IT comes up as a practical path forward, decoupling systems of record from systems of engagement so operators can move faster without dangerous rip-and-replace projects. Finally, we zoom out to the bigger industry landscape, including 5G reality checks, early 6G signals, and satellite connectivity disruptions that could rewrite coverage economics.

If you care about telecom IT modernization, autonomous enterprise strategy, and the future of the CIO role, listen now, then subscribe, share this with a colleague, and leave a review with your biggest takeaway.

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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Speed used to be the headline for broadband. Now the real question is tougher: did your internet actually feel reliable all day, on every device, in every room? We talk with Janelle Morse from SCTE, an industry insider helping shape Tech Expo 26 in Atlanta, about why the broadband world is pivoting toward end-to-end customer experience and what that means for operators, engineers, and anyone building modern networks.

We break down the event’s theme, “convergence powered, experience protected,” and why convergence is no longer a buzzword. Fiber, HFC, DOCSIS, Wi-Fi, wireless broadband, and even satellite increasingly have to operate as one coordinated system. That pushes the industry toward cloud-native architectures, more virtualization, and more intelligence at the edge, because the network boundary now extends into the connected home where “my Wi-Fi is my internet” becomes the customer’s reality.

AI is the accelerant. Instead of vague promises, we get into concrete use cases like network diagnostics, predictive service assurance, fault detection, and optimization, plus the next step: autonomous networks and self-healing operations that can sense issues, predict failures, and take action before customers ever notice. We also talk about how Tech Expo is structured, what to prioritize when you attend, why the expo floor matters, and how workforce skills and upskilling fit into an AI-driven future.

If you care about broadband innovation, network reliability, and what’s next for customer experience, hit play, share it with a colleague, and subscribe for more. If you’ve got a strong opinion on fiber vs DOCSIS or where AI should help first, leave a review and tell us what you’re seeing.

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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100G Ethernet quietly crossed a line from “carrier-only” to “normal enterprise,” and the operational fallout is real: bigger links mean bigger outages, higher stakes, and far less room for sloppy assumptions. We sit down with NetAlly CEO Jeff O’Mara and Product Lead Thomas Doumas to break down why 100G networking is showing up in enterprise environments now, how AI-driven demand is accelerating the bandwidth curve, and what network teams need to do differently when the speed jumps beyond 10G.

We get specific about what actually gets harder at 25G, 40G, and 100G. Auto-negotiation habits that feel natural at lower speeds often do not apply, so both ends of the link can require careful hard-coded settings, with many possible port modes and only a few that will work. Add the “fussy” world of fiber optics at 100G, where connector cleanliness and tiny physical issues can become real failures, and you can see why misconfiguration and optical problems dominate modern troubleshooting.

We also unpack NetAlly’s approach to AI-assisted troubleshooting through what they call Ally Intelligence: guided, field-tested workflows that turn broad complaints into checkable root causes, without relying on generic chat outputs. Then we talk economics and accountability, including how to validate that a 100G service or upgrade is performing to spec, reduce guesswork, and shorten “time to innocence” when the network gets blamed. We close with the upgrade reality of old and new running together, classic landmines like spanning tree, and what comes next as the industry heads toward 400G.

If you want practical, enterprise-focused guidance on testing, troubleshooting, and validating high-speed networks, hit subscribe, share this with your network team, and leave a review. What’s the hardest part of supporting 100G where you work?

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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Your AI budget isn’t blowing up because someone asked too many questions. It’s blowing up because AI agents turn one request into a chain reaction of inference calls, and the infrastructure underneath can’t deliver fast tokens efficiently at scale. We sit down with Vasanth Mohan from SambaNova to get specific about what changes when AI moves from “chat” to “do,” and why enterprises suddenly feel latency, throughput, and cost as operational constraints.

We break down the difference between training and AI inference, then zoom into the agentic reality: swarms of agents, model tiering, and the constant balancing act between tokens per second per request and tokens per second per chip. You’ll hear how model size drives memory pressure, why batching affects your bill, and how to decide when “fast enough” is actually costing you productivity, especially for coding workflows and other tight feedback loops.

Then we go hardware-deep in plain language. Vasant explains SambaNova’s reconfigurable dataflow unit (RDU), why mapping dataflow graphs to silicon can change performance, and how disaggregated inference splits prefill from decode. We also talk about GPUs working alongside other chips, extending the life of existing deployments, and why energy efficiency and air-cooled data centers matter for sovereign AI and global rollouts. We close with a reality check on benchmarks, “benchmaxing,” and why private evals and testing on your own workloads are the only trustworthy path.

If you care about enterprise AI, AI agents, inference optimization, and the real economics of tokens, hit subscribe, share this with a builder on your team, and leave a review with the toughest inference problem you’re trying to solve.

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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Enterprise tech is having a weird moment: innovation is real, but so is the noise. AI shows up in every pitch, “leading” is used in every sentence, and buyers who actually have budgets and deadlines are stuck asking the same question: what’s genuinely worth my time? I’m joined by Rose Ross, founder and chief Trailblazer at the Tech Trailblazers Awards, to talk about how credible startup awards can act as a practical filter for enterprise IT leaders and a meaningful growth lever for founders.

We dig into what makes an enterprise tech awards program valuable instead of performative: clear criteria, a respected panel of judges, and an emphasis on proof over polish. Rose shares how the Tech Trailblazers Awards grew into its 15th edition across categories like cybersecurity, networking, telecoms, containers, sustainability, AI in a B2B context, plus newer frontiers like robotics and quantum computing. We also talk about why customer impact matters more than “sexiness,” and how buyers can use awards as a shortlist without outsourcing their judgment.

If you’re a founder or operator, we get very specific on the practical side: who can enter (nine years or younger and not beyond Series C), the Firestarter subset (three years or younger with no Series A), how to think about the entry like an investor pitch deck, and what judges hate most. The simplest advice wins: answer the question, drop the vague buzzwords, and back every claim with evidence.

Subscribe for more founder and enterprise tech conversations, share this with a builder or buyer who needs a better filter, and leave a review with the best buzzword you never want to hear again.

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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Frontier AI is changing the rules of security, and enterprises feel it first. From the floor at VMware Explore, we sit down with Purnima Padmanabhan
Vice President and General Manager, Tanzu Division, to unpack what customers are asking for as AI agents move into real systems and real data. The headline: private AI is getting a serious bump, not as a trend, but as a control strategy for regulated industries and anyone worried about risk, governance, and cost. 

We walk through the “threat side” of AI, where advanced models can amplify attacks and push open source security to a breaking point. Purima explains why so many enterprise applications depend on open source, especially Spring and Java, and what happens when vulnerability reports spike. We also dig into TrueSource by Broadcom, the idea of a secure software supply chain for curated open source packages, libraries, and images that enterprises can trust and operationalize. 

Then we shift to the “opportunity side”: moving beyond chat and RAG into workflow automation with enterprise AI agents. That raises hard questions about sandboxing, limiting autonomy, and keeping agents secure. Just as important, we talk about why data projects slow everything down, and why governed access to the right data is what makes agents useful at scale. 

Finally, we get practical about developer experience and SDLC automation, including Purima’s example of running a swarm of 21+ agents across planning, Jira creation, coding, and testing, plus the caution that not all AI-generated code is equal. If you’re building on VMware Tanzu, thinking about private cloud AI, or trying to balance security, sovereignty, and TCO, this is for you. Subscribe, share with a builder on your team, and leave a review. What would make you trust an AI agent in production?

Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n

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