Full Tech Ahead

On this podcast, I sit down with business leaders, researchers and executives to explore innovative technology solutions and products, whether they’re transforming industries today or still in development. But we go far beyond the tech itself. From real-world use cases and business implementation journeys to cybersecurity challenges and future trends, we uncover what’s shaping the digital landscape. We also dive into topics that matter to every tech professional: Work/life balance, business communication, education and training. Think of it as your one-stop shop for meaningful technology discussions that inspire and inform.

Full Tech Ahead is a technology podcast hosted by Amanda Razani, with 57 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Amanda Razani hosts Full Tech Ahead, a technology show with 57 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #19

  Control Your Data and Stop AI Leaks

  Aug 13, 202616 minS2

  In this episode of "Full Tech Ahead," host Amanda Razani interviews Ward Balcerzak, Field CISO at Sentra. They explore how AI is fundamentally transforming data security posture management (DSPM) and exposing long-neglected operational hygiene, such as outdated access rights and forgotten data repositories. Balcerzak highlights the evolution from basic Large Language Models (LLMs) to fully Agentic AI systems capable of autonomous reasoning. He warns that threat actors are using advanced frontier models to chain together low-and-medium severity vulnerabilities to breach perimeters and exfiltrate IP. To counter these AI-driven external attacks and internal data overexposure, Balcerzak advises business leaders to move past "opening the floodgates," establish strict data provisioning based on specific use cases, build trust-based partnerships across departments (Legal, HR, Privacy), and master basic data and identity security fundamentals. Key Quotes "Sentra... we are a data security posture management software vendor. And what that really is, is we're finding where your sensitive data is at, what it is, how it's exposed." "AI is exposing things that we forgot about for the last twenty years or we ignored... hygiene, data hygiene, access rights." "Frontier models are able to chain exploits together in a way that humans really didn't think about... You need to focus on the mediums and lows, first and foremost." "Security leaders... you need to find your champions out there in the organization... Start reaching out... make them your best friends." Takeaways Address Medium and Low Vulnerabilities: Traditional vulnerability management focuses exclusively on high and critical risks. However, threat actors now leverage AI models to string together multiple minor, unpatched exploits into sophisticated breach pathways, making low-and-medium vulnerability remediation mandatory. Avoid Opening Data Floodgates: Deploying copilots or agentic AI across an entire corporate dataset by default creates severe overexposure. Companies must restrict training and input data to a minimal, highly specific subset tailored strictly to defined business outputs and permissioned user roles. Bridge the Security-Business Communication Gap: Security professionals cannot protect an organization without understanding operational goals. CISOs should establish non-transactional, human relationships with non-technical leaders in Legal, HR, Privacy, and specific business units to identify champions and align security posture with actual daily usage. Master Identity and Data Fundamentals: A strong AI defense relies on basic digital hygiene. Organizations must clean up authentication infrastructure (such as Active Directory) to enforce need-to-know access, tokenize or encrypt sensitive data in databases, and run continuous discovery to locate forgotten corporate data assets. Find Amanda Razani on LinkedIn. https://www.linkedin.com/in/amanda-razani-990a7233/ Follow the FTA LinkedIn Page: https://www.linkedin.com/company/full-tech-ahead/ Visit the FTA website: https://fulltechahead.com/ Check out the Substack Channel: https://fulltechahead.substack.com/

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  Full Tech Ahead

  Cyberattacks are up 4X. Are you Ready?

  Aug 6, 202618 min

  In this episode of "Full Tech Ahead," host Amanda Razani interviews Joe Sykora, CEO of Coro. They discuss the massive cybersecurity challenges facing small to medium-sized enterprises (SMEs) and Managed Service Providers (MSPs) who struggle with limited resources and complex "Franken-stacks"—a fragmented mix of disconnected, multi-vendor security tools stitched together via APIs. Sykora outlines how Coro eliminates this complexity by providing a unified platform powered by a single agent and a clean, consolidated dataset running roughly 14 integrated modules. This architecture enables an automated cyber threat remediation rate of 92% to 96%. Sykora notes that cyberattacks have surged 3 to 4 times per client compared to last year due to malicious AI use. To address this, he champions operational simplicity, a 100% channel-partner model, and urges security leaders to embrace rapid product cycles and platform consolidation to maximize MSP profit margins and eliminate costly misconfigurations. Key Quotes "Coro is a complete cybersecurity platform... We have a single agent that we provide roughly fourteen different modules... we cover all aspects of cyber." "The number one risk is people... but number two is misconfiguration. I've seen a lot of clients through the years have issues with something was misconfigured because they had that 'Franken-stack'." "As a provider who gets to see things happen, we've already seen almost four X the number of attacks so far this year than all of last year." "If you're not using an AI system, I don't see how you keep up... This is kind of hyperscale when it comes to that." Takeaways Ditch the "Franken-stack" for Data Cleanliness: Relying on separate security tools connected via APIs fails to provide a true "single pane of glass." A unified platform ensures a clean, singular dataset, which is the foundational prerequisite for defensive AI to effectively stop and remediate threats automatically. Consolidation Cuts Operational Overhead: For MSPs, the primary cost is not software licensing but backend operational labor. Switching from fragmented tools to a unified architecture allows a single security analyst to manage 100 to 200 clients seamlessly, compared to just 20 or 30 under an enterprise legacy setup, heavily expanding profit margins. Defensive AI is Mandatory: With AI-driven phishing and social engineering attacks scaling up to 4X per client in 2026, cyber threats no longer contain obvious grammar mistakes or broken logos. Keeping up with this hyper-scale execution requires immediate adoption of automated, defensive AI ecosystems. Embrace Hyper-Fast Change Cycles: The landscape is shifting so quickly that traditional long-term product roadmaps are being superseded by immediate, rolling update cycles. Cybersecurity leaders and developers must remain adaptable and open to constant system refactoring to survive market disruption. Coro website and social handles: https://www.coro.net/ https://www.linkedin.com/company/corocyber/ https://x.com/coro_cyber?s=20 https://www.youtube.com/@coro-cybersecurity Many Thanks to Coro for sponsoring this episode! Find Amanda Razani on LinkedIn. https://www.linkedin.com/in/amanda-razani-990a7233/ Follow the FTA LinkedIn Page: https://www.linkedin.com/company/full-tech-ahead/ Visit the FTA website: https://fulltechahead.com/ Check out the Substack Channel: https://fulltechahead.substack.com/

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  Episode #17

  Boost AI Token Efficiency by 20 Percent

  Jul 30, 202619 minS2

  In this episode of "Full Tech Ahead," host Amanda Razani interviews DJ Spry, Head of Product for Aria Networks. The discussion focuses on the rapidly shifting AI landscape and the critical infrastructure bottlenecks facing organizations building out AI factories and computing clusters. Spry introduces the pioneered concept of "Deep Networking," a vertically integrated hardware and software solution that embeds telemetry down to the lowest ASIC level while surfacing insights through natural language agentic AI interfaces. He highlights the stark architectural contrast between the cloud era and the AI era: while cloud applications are loosely coupled and resilient to localized infrastructure failures, AI networking is highly tightly coupled, meaning processing speeds automatically drag down to the slowest component. To achieve "time to first token" efficiency and secure a competitive advantage, Spry urges CIOs and CTOs to steer away from costly, prolonged in-house builds and instead leverage specialized commercial expertise and advanced "Neo Clouds" to optimize hardware investments. Key Quotes "Aria Networks... pioneered this concept of what we like to call as deep networking, and that is this vertically integrated solution that has like deep technology all the way down into the... ASICs, the lowest level of the hardware." "In cloud, the applications were loosely coupled to the infrastructure underneath them... In AI networking, that is very much the pendulum has swung the other way. These are very tightly coupled systems." "I think that there's going to be more consumers of our solutions and our products that don't have heartbeats... products are going to be consumed more and more by agents." "A two percent gain [in networking] can give you outsized impact, you know, like ten to twenty percent more token efficiency. So I think that it's worth steel-manning the counter [instead of driving cost to the lowest component]." Takeaways AI Architecture Demands Tight Coupling: Unlike cloud environments where infrastructure failures easily spin up in alternative VPC regions without user disruption, AI training and inference loops are highly tightly coupled. System performance and model completion rates are dictated by the slowest link, making deep, low-latency networking non-negotiable. Optimize via Outsized Technical Gains: When calculating infrastructure ROI, looking strictly for the lowest-priced hardware component is counterintuitive. Investing slightly more in hyper-speed networking can generate a tiny 2% infrastructure optimization that yields a massive 10% to 20% surge in enterprise token efficiency. Prepare for Non-Human Users: The traditional SaaS metrics of Daily Active Users (DAU) and Monthly Active Users (MAU) must be refactored to account for AI agents. The industry is moving toward a reality where digital workflows run autonomously 24/7 while human teams sleep, shifting software consumption primarily toward agentic workloads. Leverage Forward-Deployed Expertise: The specialized engineering skill set required to stand up GPU data centers is severely lacking in the broader enterprise market. Organizations should avoid the trap of prolonged internal tool builds that delay time-to-market and instead utilize forward-deployed commercial specialists to bootstrap systems rapidly. Speaker Bio: DJ Spry is Head of Product at Aria Networks. He previously served as Senior Director of Product Management at Juniper, leading the product team following the acquisition of Apstra, where he was an early employee. His commercial networking career includes driving GTM for Open Networking at Dell EMC and serving as a consulting engineer at Juniper. He began his career in the US Air Force and later served as a network engineer and architect for the US Intelligence Community. Aria website and social handles: arianetworks.com https://www.linkedin.com/company/aria-networks-inc/ https://x.com/AriaNetworks https://www.youtube.com/@Aria_Networks Find Amanda Razani on LinkedIn. https://www.linkedin.com/in/amanda-razani-990a7233/ Follow the FTA LinkedIn Page: https://www.linkedin.com/company/full-tech-ahead/ Visit the FTA website: https://fulltechahead.com/ Check out the Substack Channel: https://fulltechahead.substack.com/

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  Episode #16

  Manage Your AI Security Debt

  Jul 24, 202614 minS2

  In this episode of "Full Tech Ahead," host Amanda Razani interviews Nidhi Aggarwal, Chief Product Officer (CPO) of HackerOne. They discuss the paradigm shift in cybersecurity risks caused by AI-accelerated software development. Aggarwal introduces HackerOne’s new continuous threat exposure management platform, H1, designed to bridge the "find-to-fix" lifecycle gap. She reveals that following the release of advanced AI models, vulnerability report volumes surged by over 90% in April 2026 alone. This influx has dramatically shortened the "zero-day clock", the time between vulnerability discovery and adversary exploitation, from an average of one month down to mere hours or minutes. To combat the resulting 25X spike in critical vulnerability backlogs and build up "exposure debt," Aggarwal emphasizes that organizations must abandon seasonal compliance checks in favor of continuous, AI-driven adversarial pen testing combined with human discernment. Key Quotes "Remediation has not kept pace... most CISOs are not looking for more vulnerabilities. Everybody's inundated with vulnerabilities." "The zero day clock... has steadily gone down from it used to be about a month last year to a matter of a few hours now in this year with AI." "Defense has to operate at that AI offensive scale... We have a concept called exposure debt... you have to think of it like technical debt or something sitting on your balance sheet." "The big advice would be offense is defense. So you have to think offensively." Takeaways Automate Defense at Machine Scale: Since generative AI has driven the marginal cost of cyberattacks close to zero, adversaries can now launch massive, automated exploits in under ten minutes. Security defense can no longer operate at human speed; prioritization and remediation must scale up to match offensive AI. Manage Your "Exposure Debt": Unremediated high-risk vulnerabilities function like technical debt on an enterprise balance sheet. Organizations must treat this exposure as a board-level risk conversation and design a continuous drawing-down plan rather than letting critical backlogs accumulate. Filter out "AI Slop" via Bifurcation: The explosion of automated AI scanning has altered risk distribution. Security teams are experiencing a bifurcation: they are flooded either with informational "AI slop" (false positives that existing controls block) or hyper-critical zero-days. Rapid automated validation is mandatory to isolate true exposure. Shift to Continuous Risk-Based Pen Testing: Move away from compliance-driven, checkbox security architectures. True defensive resilience requires automated, 24/7 white-box and black-box pen testing, paired with the creative adversarial judgment of ethical human researchers using AI. Find Amanda Razani on LinkedIn. https://www.linkedin.com/in/amanda-razani-990a7233/ Follow the FTA LinkedIn Page: https://www.linkedin.com/company/full-tech-ahead/ Visit the FTA website: https://fulltechahead.com/ Check out the Substack Channel: https://fulltechahead.substack.com/

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  Episode #15

  Control Your AI Spending

  Jul 16, 202618 minS2

  In this episode of "Full Tech Ahead," host Amanda Razani interviews Matthew Shaxted, CEO of Parallel Works. The conversation centers on a major obstacle facing enterprises today: skyrocketing token consumption and the ballooning costs of using frontier AI models. Shaxted explains that opening up unrestricted API access to hundreds or thousands of users leads to rapid budget depletion, citing recent industry examples like Uber. Drawing a parallel to the high-performance computing (HPC) and cloud migration trends over the past decade, Shaxted predicts a cyclical shift: while firms currently rely heavily on public cloud endpoints, economic pressures and massive utilization rates will drive them to bring data workloads back on-premise using increasingly powerful open-weight models (like the recently released GLM 5.2). To combat initial adoption chaos, Parallel Works offers a computing control plane called Activate, providing a single pane of glass to enforce visibility, tracking, and strict "token budgets" that automatically deny requests once expenditure thresholds are met. Key Quotes "Unless [token usage] is thought about in the very beginning in terms of how are you going to control and monitor token usage... it really becomes a big problem. We've seen the Uber story recently, where you burn through the entire budget in a few months." "Having strong visibility in where the tokens are going... make sure from the very beginning you have visibility into who's doing what, because that's going to start growing very quickly." "As soon as it basically is out of budget, it will deny the request until you get more allotted. That's exactly what's happening." "As the open weights get better and better—which I think we're starting to see with GLM 5.2 coming out recently—you can start running open weight models for certain classes of things with much more predictable cost." Takeaways Establish Financial Guardrails Early: Unrestricted enterprise AI access creates a cash burn. Implement central governance and a "computing control plane" from day one to enforce hard spending limits (token budgets) at the user or team level, preventing unexpected tech invoicing. Prepare for the On-Premise AI Hybrid Shift: Much like cloud computing evolved, enterprise AI will hit a baseline utilization rate (e.g., 8k/80% load) where renting per-token public APIs becomes economically unsustainable. Companies should plan a hybrid stack that shifts routine tasks to dedicated on-premise infrastructure running open-weight models to cut costs up to 6X. Incentivize Token Awareness: End-users rarely optimize resource usage unless faced with explicit constraints. Providing visible token limits encourages developers and practitioners to delegate simpler, mundane prompts to lighter, less expensive internal models rather than burning resources on premium frontier labs. Architect for Agentic Workloads: With the industry shifting toward massive agentic systems where hundreds of autonomous agents execute tasks 24/7, compute demands are projected to scale up to 1,000X. Managing this scale without breaking corporate cost structures requires unified virtualization and gateway gateways across cloud and hardware assets. Find Amanda Razani on LinkedIn. https://www.linkedin.com/in/amanda-razani-990a7233/ Follow the FTA LinkedIn Page: https://www.linkedin.com/company/full-tech-ahead/ Visit the FTA website: https://fulltechahead.com/ Check out the Substack Channel: https://fulltechahead.substack.com/

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