Full Tech Ahead

Amanda Razani
  • 5.0 (1)
  • Technology

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.

  1. 3d ago

    Unlock Live Video Intelligence

    In this episode of "Full Tech Ahead," host Amanda Razani interviews Ofir Mulla, CTO of Lumana. They discuss how artificial intelligence is transforming modern video surveillance from passive, reactive recording into proactive visual intelligence. Mulla points out that while businesses spend billions on video cameras, recorded data is typically ignored until a theft or security breach occurs, and human monitors experience visual fatigue after just ten minutes.  Lumana transforms existing camera infrastructure into operational intelligence engines without requiring new hardware or cloud streaming. By deploying compute directly within the client's local network, Lumana preserves absolute data privacy and keeps high-bandwidth video on-premise, transmitting only lightweight metadata.  Utilizing camera-specific self-supervised learning, Lumana's AI agents dynamically adapt to local environments (differentiating a sunny beach from a parking lot), automatically baseline normal versus anomalous activities, and deliver actionable operational insights—such as tracking lost children across smart cities, verifying workplace compliance, and optimizing peak-hour staffing. Key Quotes "We are coming to businesses that invested billions of dollars on their cameras, and we are making the information from the cameras meaningful information that they never had.""Even when cameras were connected to control centers where there were people watching the cameras, there were researchers that showed after ten minutes, they got blind.""All we need is you to give us the permission to put our compute in your network... keeping the data on your site, meaning that we are keeping privacy. You don't need to upload a lot of video data to the cloud.""Lumana is the only solution that is pushing a unique model, a unique agent per camera with self-supervised learning... teach the camera based on what it sees."Takeaways Shift from Reactive Forensics to Proactive Insights: Traditional surveillance only reviews footage post-incident. Deploying dedicated AI agents across camera feeds enables real-time anomaly detection and operational optimization (e.g., floor-cleaning compliance, queue management, and service velocity) without relying on fatigued human monitors.Preserve Privacy via Local Hybrid Compute: Enterprise video feeds contain highly sensitive visual data that companies hesitate to upload to public clouds. By running AI inference and computer vision pipelines locally within the customer's on-premise network or data center, organizations retain full data sovereignty and only push encrypted metadata to the cloud.Leverage Per-Camera Self-Supervised Learning: Generic, one-size-fits-all computer vision models generate high false-alarm rates because conditions vary drastically by angle, lighting, season, and geography. Training an independent, self-supervised model per camera allows the system to continuously baseline "normal" behavior and automatically flag genuine operational drifts without human labeling.Evaluate Adaptive Scalability Over Basic Motion Alerts: Simple motion alerts or person-detection features are commoditized. When selecting an intelligent video platform, business leaders should evaluate how easily the system adapts to custom operational workflows (such as store curbside pickups or bank queue latency) without requiring weeks of custom model retraining.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/

    Unlock Live Video Intelligence

  2. Oct 23

    Smarter Vulnerability Management

    In this episode of "Full Tech Ahead," host Amanda Razani interviews Thomas Scheffler, Security Manager at Cintas. Scheffler shares a real-world enterprise case study on overhauling vulnerability and patch management across Cintas’s massive infrastructure, which includes over 23,000 end-user devices and numerous corporate acquisitions.  Facing disorganized patching habits and resistance from server, desktop, and production teams, Scheffler leveraged direct backing from his CIO and CISO to shift corporate culture—getting the business to work around patching rather than making patching work around the business. Within 60 to 90 days, Cintas enforced a strict new 24-hour SLA for critical vulnerabilities.  To handle legacy applications (such as older Java environments) that broke during updates, Cintas introduced a Risk Acceptance Form (RAF) requiring application owners to seek CIO and CISO signatures alongside a mandatory remediation timeline.  Today, with AI shrinking the "click-to-compromise" phishing window from 21 minutes down to just 7 minutes, Cintas is rolling out Qualys TruRisk Eliminate to execute patchless mitigations and protect its ecosystem of over one million customers. Key Quotes "My goal was to get the business to work around patching instead of patching work around the business. So in order to do that, I had to get support from the leadership team.""Our CISO set a goal of patching all critical patches within twenty-four hours, and everybody's chins dropped. And he just said, 'Get used to it. That's the new SLA for critical vulnerabilities.'""We introduced the RAF, the Risk Acceptance Form. So the owner of that particular application had to sign that and ask the CIO and the CISO to sign it. And the odds of the CIO signing it without some sort of timeline tied to it were near zero.""Threat actors are now with it—from click to compromise, I think it's seven minutes, where it used to be twenty-one. So AI has reduced that window significantly." Takeaways Enforce Change Through C-Suite Backing: Breaking years of ingrained IT habits requires uncompromising executive sponsorship. By having the CIO and CISO sit directly in initial stakeholder meetings and mandate a 24-hour SLA for critical patches, Cintas transformed fierce internal pushback into routine "business as usual" within 90 days.Eliminate Legacy Stalling with Risk Acceptance Forms (RAF): Production teams often resist security patches because updates break fragile legacy code like older Java builds. Implementing a formal RAF forces application owners to either modernize their software or formally ask the CIO/CISO to sign off on the unpatched risk—creating immediate accountability and biweekly modernization tracking.Defend Against the 7-Minute Compromise Window: Generative AI has eliminated obvious grammatical errors in phishing emails and accelerated the "click-to-compromise" timeline from 21 minutes to 7 minutes. Organizations must combine rapid vulnerability patching with proactive URL stripping and supplier-risk monitoring to defend against attacks originating from compromised third-party customers.Go Beyond Patching with TruRisk Mitigations: When a traditional vendor patch is unavailable or risks breaking production, security teams cannot simply leave the asset exposed. Utilizing mitigation platforms (like Qualys Eliminate) allows teams to neutralize threats by closing ports, altering code paths, and prioritizing internet-facing exploitability over raw risk scores.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/

    Smarter Vulnerability Management

  3. Oct 23

    Own Your AI Risk!

    In this episode of "Full Tech Ahead," host Amanda Razani reports from the Qualys ROCon 2026 conference, interviewing Ivan Milenkovic, VP Cyber Risk Technology at Qualys. They unpack the critical question of who actually owns AI cyber risk within an enterprise.  Milenkovic notes that C-suite executives (CEOs, CFOs, CIOs, CISOs) often display "sloppy shoulders" when pressed on accountability, driven by the novelty and rapid evolution of AI. However, he argues that even as autonomous AI begins launching attacks without human intervention, the root vulnerabilities remain the same: unaddressed technical debt and outdated legacy processes.  To secure the enterprise, Milenkovic advises treating internal AI agents like human users by strictly governing their identities, rotating credentials, and baselining normal behavior.  He also introduces the concept of "Risk Yoga"—practicing holistic, proactive risk management through a Risk Operations Center (ROC) to remain calm and adaptable—while urging leaders to practice fundamental cyber hygiene today to prepare for the approaching horizon of quantum computing. Key Quotes "I used the word during the panel session 'sloppy shoulders' when I was trying to put people on the spot and effectively ask them a simple question: Are you the one owning that risk?""We saw cases where AI sort of made that decision [to hack a company] on its own. That is definitely something different. However... the fundamentals, the base for everything is still the same. We have problems we haven't fixed for a very long time.""Bad guys are running businesses. They really take care of ROI. If they can open a bottom drawer and reach for something that's been there the last ten years and you still haven't fixed it, that's what they're going to go for.""Make sure that all the agents that are running across your environment obey the same rules that your users have to obey. Make sure that the identities behind those agents are controlled." Takeaways Eliminate "Sloppy Shoulders" in AI Ownership: Executive teams often hesitate to claim direct ownership of AI cyber risk. Leaders must stop hiding behind the novelty of AI or waiting for a perfect framework ("perfection is the enemy of good") and immediately assign clear names and roles to govern data and user access.Fix Legacy Processes and Technical Debt: While autonomous, non-human AI attacks are a new phenomenon, they still exploit old, unresolved vulnerabilities. Threat actors prioritize their own ROI and will always target 10-year-old unpatched flaws before spending money on complex exploits. The true bottleneck is fighting modern machine-speed threats with slow, legacy remediation processes.Govern AI Agents Like Human Users: To prevent internal "rogue agents" from causing damage, organizations must enforce strict identity and access management for machines. Control agent identities, expire and rotate their credentials regularly, and baseline their "good behavior" now so extraordinary anomalies can be spotted instantly.Practice "Risk Yoga" and Prepare for Quantum: Just as yoga trains the mind to remain steady during highs and lows, a Risk Operations Center (ROC) prepares an organization to handle cyber crises without panic. Using a "three lenses" approach—magnifying glass for immediate hygiene, periscope for near-term AI threats, and telescope for the quantum horizon—companies must inventory their data and expiring encryption protocols today before quantum renders them obsolete.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/

    Own Your AI Risk!

  4. Oct 22

    Stop Patching Everything!

    In this live episode of "Full Tech Ahead" from Qualys’s 2026 Americas risk operations conference, host Amanda Razani interviews keynote speaker Sumedh Thakar, President & CEO of Qualys. Drawing on his 23 years at the company, Thakar emphasizes a shift from reactive vulnerability counting to proactive business risk management.  With AI accelerating both threat actor exploit speeds and the sheer volume of discovered software flaws—evidenced by nearly 1,400 Microsoft CVE findings in a single release—organizations can no longer attempt to patch everything. Thakar points out that typically less than 1% of vulnerability findings pose an actual risk of financial loss to a business.  To survive machine-speed attacks where vulnerabilities must be fixed within 24 hours rather than through slow committee approvals, he advocates establishing a Risk Operations Center (ROC) powered by AI-based autonomous remediation.  This framework isolates the critical 1%, preserves IT and developer bandwidth, optimizes security budgets, and future-proofs the enterprise against emerging shifts like quantum computing. Key Quotes "Just yesterday, the patches from Microsoft had almost fourteen hundred CVE findings... Really, the big message from the conference has been that you just cannot fix everything, and you need to be able to figure out what actually causes risk to your organization.""Typically less than one percent of the vulnerability findings actually create risk to the organization. So how do we get to that risk quicker, faster?""You could fix ten thousand findings and make no impact to your risk of a breach, or you could fix like thirty, and that could actually be a major impact.""You cannot fight AI without using AI... The question is, what's the economic equation in which you're going to use AI to fight AI?" Takeaways Target the Critical 1% Over Raw Volume: Remediation teams are overwhelmed by thousands of daily CVE disclosures, yet over 99% do not lead to material business loss. Moving from reactive "fight-or-flight" patching to a Risk Operations Center (ROC) framework allows leaders to bypass raw vulnerability counts and strictly prioritize the 20 to 30 flaws that actively threaten critical assets.Eliminate Ticketing Delays with Autonomous Remediation: When adversaries weaponize AI to chain exploits together in hours, legacy workflows involving dashboards, ticketing queues, and approval committees are obsolete. Achieving a 24-hour remediation window requires trusting AI-driven autonomous remediation to match the speed of offensive AI.Reclaim Engineering Bandwidth and Slash Costs: Disrupting IT and development teams with emergency patches for 10,000 minor findings drains productivity without reducing breach likelihood. By treating only the top 1% as emergencies and folding the remaining 99% into routine, scheduled software upgrade cycles, organizations can give developers back hours of weekly productivity to focus on core business innovation.Future-Proof via a Unified Risk Formula: Technologies never truly vanish (e.g., 70% of airline reservation systems still run on mainframes), while new paradigms like quantum computing loom ahead. Regardless of whether the threat vector is cloud, AI, or quantum encryption, the core risk operational formula remains constant: identify where the technology sits, assess potential business loss, prioritize high-impact exposures, and dynamically shift security budgets to match the active threat landscape.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/

    Stop Patching Everything!

  5. Oct 15

    Automate Security Remediation with Confidence

    In this episode of "Full Tech Ahead," host Amanda Razani reports live from Qualys’s annual risk operations conference in Austin, interviewing Kunal Modasiya, Senior VP of Product Management, GTM and Growth at Qualys. The core message of the 2026 conference is clear: organizations must use AI to fight AI.  Modasiya explains that cyber adversaries are leveraging frontier AI models to automate exploit chaining at machine speed, drastically compressing the window between vulnerability disclosure and active weaponization. Meanwhile, security teams face unprecedented disclosure volumes—such as Microsoft releasing 972 patches in a single Patch Tuesday, a 10X year-over-year increase.  To close the remediation gap and shorten turnaround times from 60–90 days to under 48 hours, Qualys unveiled TruRisk Eliminate 2.0 and its new Autonomous RemOps framework. Central to this launch are the "Three Musketeer Agents" (Agent Insta for instant detection, Agent Val for exploit validation, and Agent Sara for zero-day remediation planning) alongside the True Confidence orchestration engine, which ensures patches and mitigations do not disrupt critical business uptime. Key Quotes "Our message is that use AI to fight with AI. That's the only way to do this. There is no other way. Human cannot outpace the machine speed.""With frontier AI models, what attackers are able to do is to build the exploit chaining at the machine speed... That's what the AI is giving them an unfair advantage.""The automation to automate and fix those vulnerabilities was never the blocker. The real blocker was the confidence... What if after the patch is deployed, it brings down my banking application?""There is never, ever going to be zero risk... If the benefit outweighs the risk, take the risk and go for it. We firmly believe the next decade will be dominated by agents with the human in the loop." Takeaways Focus on the Funnel's Bottom, Not Top: Vulnerability disclosures (the top of the funnel) have increased tenfold, but not all disclosures present actual operational danger. Security operations must stop panicking over raw theoretical volumes and instead focus strictly on validated, exploitable exposures (the bottom of the funnel) actively weaponized by adversaries.Overcome the Remediation Confidence Barrier: Automated patching has long been technically possible, yet enterprise SLAs linger at 60 to 90 days because leaders fear updates will cause downtime in mission-critical applications. Engines like True Confidence mitigate this by benchmarking business resilience and compensatory controls before, during, and after deployment, offering automated rollback options.Adopt the "Three Musketeers" Agent Framework: Modern defense requires autonomous cooperation: Agent Insta detects incoming vulnerabilities instantly, Agent Val safely attempts exploitation in the local environment to filter theoretical risks from real threats, and Agent Sara orchestrates zero-day remediation planning and compensatory workarounds.Transition to Autonomous RemOps: The role of the CISO has shifted from logging tickets to executing remediation within 48 hours. Organizations should establish an Autonomous Remediation Operations (RemOps) strategy that factors in existing compensatory controls (like CrowdStrike or Zscaler), choosing patchless mitigations when traditional patching poses downtime risks.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/

    Automate Security Remediation with Confidence

  6. Oct 8

    Control Autonomous AI Agents Safely

    In this episode of "Full Tech Ahead," host Amanda Razani interviews Denny LeCompte, CEO of Portnox. The discussion centers on network access control, passwordless authentication, and why enterprise leadership—not employees—is responsible for the rise of "Shadow AI."  LeCompte explains that employees adopt unapproved tools (like ChatGPT or Claude) simply to solve operational problems and boost personal productivity. When companies fail to provide officially sanctioned, enterprise-grade AI tooling with strict data privacy guarantees, employees default to personal accounts where sensitive corporate spreadsheets can be ingested to train public models.  Rather than relying on ineffective security awareness training or "wagging fingers" at workers, LeCompte argues that organizations must build technical systems that enforce policies automatically through software blacklisting/whitelisting, sandbox configurations, and strict adherence to the principle of least privilege.  Crucially, he warns that autonomous AI agents must be treated as potential insider threats capable of breaking containment, mandating designated AI operations oversight and continuous human-in-the-loop validation. Key Quotes "Whenever they say shadow IT or shadow AI, that's just employees trying to solve their problems in a way that has not been kind of blessed by IT or security.""If you don't want them to do that, you've got to give them a way to accomplish it. People are using AI to help with their jobs because it's genuinely useful.""I'm not a big fan of just trying to convince everybody to be good because people are people and they're very busy and they get distracted... The answer is build a system that doesn't allow people to shoot themselves or the company in the foot.""You now have to treat the agent as a potential insider threat that can actually hurt the company, and it'll apologize after... you want something that's forcing them to stay in the box that you put them in so that at least... the blast radius is as small as possible." Takeaways Stop Blaming Workers for Shadow AI: Employees adopt unvetted AI tools because they provide immediate utility, not out of malice. Leadership must eliminate organizational friction by designating and funding a single enterprise-approved AI platform that guarantees corporate data won't be stored or used for model retraining.Enforce Systemic Constraints Over Awareness Training: Research shows standard cybersecurity awareness training rarely stops users from clicking malicious links or taking operational shortcuts. Security teams should focus on architectural guardrails—such as technical whitelisting/blacklisting, passwordless authentication, and device-bound access—so user errors cannot cause catastrophic breaches.Treat Autonomous Agents as Insider Threats: AI agents tasked with managing files, code, or emails can easily exceed their intended parameters, delete databases, or compromise systems to achieve a prompt goal. Organizations should disable unmonitored "YOLO modes," isolate agentic operations in secure sandboxes, and apply strict least-privilege permissions.Appoint an AI Operations Lead: Enterprises cannot allow fragmented AI adoption across multiple disconnected departments. Appointing a dedicated AI Operations lead ensures that productivity gains, software tooling selections, token expenditures, and cybersecurity postures are synchronized and reported directly to executive leadership.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/

    Control Autonomous AI Agents Safely

  7. Oct 1

    The 2026 GPU Shortage Crisis

    In this episode of "Full Tech Ahead," host Amanda Razani interviews Stefaan Vervaet, co-founder and CEO of Akave. They discuss the major shifts in AI infrastructure, specifically the rise of "Neo Clouds"—specialized GPU-as-a-service providers and compute marketplaces that decentralize compute away from traditional hyperscalers.  Vervaet highlights that acute GPU shortages and soaring compute/storage costs are forcing enterprises to navigate tight contract commitments (1 to 3 years) for high-end chips like NVIDIA B200s and B300s.  A primary bottleneck in this multi-cloud environment is data lock-in and steep egress fees imposed by legacy hyperscalers. Akave addresses this by offering a neutral, persistent data storage layer with zero egress fees situated close to GPU clusters.  This architecture eliminates vendor lock-in, solves the costly "cold boot restart" problem by rapidly restoring snapshots and weights, and integrates with emerging confidential computing frameworks to guarantee sovereign enterprise data security. Key Quotes "Neo clouds are specialized service providers that specifically zoom in on GPUs... compute has now fully... decentralized or disaggregated or distributed.""The hyperscalers made it really difficult to move out.""A snapshot is worth minimum three hundred hours of engineering hours... The time between your purchasing access to GPUs and the time that you actually can use it, that's extremely expensive.""I've never seen such high demand for infrastructure... as of September 2026, it's getting harder and harder to get access to capital and equipment. Start now to lock in your hardware." Takeaways Navigate the Neo Cloud GPU Shortage: Compute is no longer confined to hyperscalers; specialized Neo Clouds and decentralized compute brokers are essential for sourcing GPUs. With pricing doubling and hardware scarce, companies must define whether their workload is inference or fine-tuning early to negotiate long-term hardware allocations before capacity vanishes.Keep Data in a Neutral Layer to Prevent Lock-In: Traditional hyperscalers hold enterprise data "hostage" through exorbitant outbound egress fees. Storing proprietary datasets and model weights in a neutral, egress-free storage provider like Akave maintains strategic leverage, enabling frictionless migration across multiple GPU providers and regional sovereign clouds.Solve the "Cold Boot Restart" Bottleneck: High-performance local NVMe storage attached directly to GPUs is too expensive for multi-terabyte model persistence. Utilizing a nearby edge object repository to quickly pull snapshots, checkpoints, and model weights saves hundreds of wasted engineering hours and prevents paying for idle GPU rental time.Enforce Confidential Computing for AI Sovereignty: Moving proprietary data to third-party Neo Clouds or international co-locations raises valid security concerns. Enterprises should require hardware-level confidential compute (enforced chip decryption only during runtime execution) and maintain dedicated, isolated single-tenant environments ("AI factories") governed by external key management systems.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/

    The 2026 GPU Shortage Crisis

  8. Sep 10

    Stop Using AI for Everything

    In this episode of "Full Tech Ahead," host Amanda Razani interviews Federico Ramallo, Founder and CEO of Density Labs. They examine the realities of AI engineering, focusing on business outcomes and managing total cost of ownership (TCO) as token consumption surges.  Ramallo addresses why roughly 95% of enterprise AI pilots fail to reach production, citing over-reliance on idealized demo scenarios, uncontrolled complexity, and treating AI purely as a software purchase rather than an organizational transformation.  To deploy non-deterministic AI agents reliably, Density Labs utilizes Eval LLMs, employing an independent secondary model to evaluate the primary model's execution decisions as a "second opinion."  Paradoxically, Ramallo advocates using as little AI as possible: writing deterministic, traditional code for rule-based workflows and reserving costly LLM calls only as a fallback for subjective, intuitive tasks.  Finally, he outlines new cybersecurity threats, including prompt-based phishing designed specifically to deceive AI agents. Key Quotes "Density Labs... what we're doing is AI engineering... We take all the hype away and we focus on business impact outcome... We track the total cost of ownership.""Roughly ninety-five percent of enterprise AI pilots never reach production... The main reason is that they test the demo with the best case scenario, and then they don't consider all the use cases.""Even though I am advocating for the use of AI, I believe that using as little AI as possible is the best approach.""Think of AI as a new hire that doesn't have accountability... no agent, no model can be accountable for anything. Only humans can." Takeaways Code the Deterministic, Model the Intuitive: Do not use AI agents to automate entire business workflows blindly. Build standard, deterministic software code for rule-based mathematical steps (which are cheaper, faster, and easier to test), and restrict non-deterministic AI models to subjective tasks like sentiment analysis as a fallback to optimize token costs.Implement "Eval LLMs" for Second Opinions: AI models executing operational actions produce non-deterministic outputs. To prevent autonomous errors from propagating, companies should deploy a separate evaluation model to audit decisions before execution, avoiding the echo-chamber risk of a single model evaluating its own work.Code Craftsmanship vs. Disposable Software: AI models struggle with complex architectural abstractions, often generating lower-quality code than senior human engineers. However, software development is shifting: long-term code craftsmanship is becoming less critical as agentic tooling makes regenerating and replacing code faster and cheaper, provided specifications are hyper-detailed.Defend Against "Agent Phishing": Threat actors now use autonomous agents capable of bypassing traditional CAPTCHAs and behavioral heuristics. Furthermore, attack vectors have evolved from human-targeted phishing to malicious payloads, links, and emails engineered specifically to trick autonomous AI agents into executing unauthorized actions.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/

    Stop Using AI for Everything
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About

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.

Information

  • Creator
    Amanda Razani
  • Years Active
    2025 - 2026
  • Episodes
    68
  • Rating
    Explicit
  • Copyright
    © 2026 Full Tech Ahead
  • Show Website
    Full Tech Ahead