Full Tech Ahead

Discover the hidden threat undermining successful AI adoption in enterprises: risk silos. In this episode, privacy and AI governance expert Cassandra Maldini joins Amanda Razani to reveal how fragmented risk management exposes businesses to compliance failures, wasted resources, and missed innovation. Learn why breaking down silos with cross-functional teamwork is essential for effective AI governance and long-term enterprise success. Tune in for actionable strategies and leadership insights to future-proof your organization in the fast-evolving world of AI.

Summary

Cassandra Maldini, Vice President of Privacy and AI Governance at Security.AI, discusses the fragmentation and risk silos in AI governance across different departments. She emphasizes the need for cross-functional collaboration among CEOs, CISOs, CPOs, and other executives to address these issues. Maldini highlights the inefficiencies and redundancies caused by silos, such as redundant meetings and tools. She argues that new regulations like the EU AI Act and California's act necessitate cross-functional efforts to achieve compliance and reduce risk. Maldini advocates for leadership to drive this collaboration and improve AI governance efficiency.

Key Quotes:

• “AI governance means different things to different teams.”
• “The biggest risk is not uniting all the pieces.”
• “Silos waste money and resources.”
• “Collaboration gets products to market faster.”
• “Regulations require cross-functional efforts.”
• “Get the right people in the room—it’s a team project.”

Takeaways

• AI governance is fragmented across departments, creating risk silos.
• Cross-functional collaboration is crucial to overcome siloed thinking.
• Silos cause redundancy, waste resources, and slow innovation.
• Strong leadership from the top is needed to unite risk teams.
• New regulations demand integrated, cross-team compliance.
• Bringing all key stakeholders together is the key first step for effective AI governance.

Timestamps

• [0:00:02] Introduction. Amanda welcomes Cassandra Maldini and introduces the podcast and guest.
• [0:00:28] Cassandra’s background. Intersection of law, compliance, and AI governance explained.
• [0:02:03] Main topic. Introduction to AI risk silos and fragmentation across departments.
• [0:02:28] Defining AI governance. Different teams have different definitions and approaches, leading to silos.
• [0:06:17] Solutions. Emphasis on courageous leadership and cross-functional collaboration.
• [0:09:54] Business challenges. Silos waste resources and create redundant efforts in compliance.
• [0:13:41] Regulatory impact. New laws require integrated teamwork and evolving executive roles.
• [0:16:55] Key takeaway. Get all stakeholders involved early and treat AI governance as a collaborative group effort.
• [0:17:49] Conclusion. Thanks to the guest and call to action for listeners.

Links/Resource

Website: Cassandra Maldini - https://securiti.ai/author/cassandra-maldini/ 

LinkedIn:  Cassandra Maldini - https://www.linkedin.com/in/cassandra-maldini/ 

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

AI is redefining warehouse operations by merging robotics, data, and intelligent automation. In this episode of Full Tech Ahead, host Amanda Razani talks with Andrei Danescu, CEO of Dexory, about how autonomous robots are revolutionizing logistics. Danescu explains how real-time data capture and AI-powered digital twins are transforming supply chain visibility and driving measurable ROI.

Summary

Andrei Danescu, CEO of Dexory, shares how his company is using the world’s tallest autonomous robots to digitize warehouses and optimize logistics operations. Dexory’s platform integrates robotics, data intelligence, and AI to provide continuous visibility into warehouse environments, replacing assumptions and manual checks with real-time insights. Danescu explains that the technology allows companies to transition from sparse, outdated data to a continuous stream of operational information—driving accuracy, efficiency, and smarter decision-making.

He highlights how Dexory’s robots can digitize a million square feet in under a day, giving customers a near-instant snapshot of every pallet, rack, and product location. This shift enables faster optimization, reduced errors, and major cost savings. In one deployment, a client saved over £200,000 within the first four weeks. Danescu also discusses how AI helps users not just collect data but act on it—automating analysis and suggesting improvements. Looking ahead, he sees a future of symbiotic collaboration between humans and intelligent systems, where technology amplifies human capabilities rather than replaces them.

Key Quotes:

• “Transitioning operations from sparse data to continuous visibility is a game changer.”
• “You can digitize a million square feet in less than a day—something unheard of in the industry.”
• “AI becomes truly powerful when it not only analyzes data but helps optimize decisions.”
• “The future is about collaboration—humans and machines working smarter together.”
• “It’s an incredibly exciting time to be alive; we’re on the verge of major breakthroughs.”

Takeaways

• Autonomous robots and AI enable real-time visibility into warehouse operations.
• Digitization turns assumptions into actionable insights that improve efficiency.
• AI can guide decision-making by suggesting optimizations automatically.
• Warehouse operations see rapid ROI, often within weeks of deployment.
• Technology is shifting logistics toward a data-driven, human-machine collaboration.
• The pace of innovation is accelerating—embracing it is key to staying competitive.

Timestamps

• [00:00] Introduction — Amanda Razani welcomes Andrei Danescu of Dexory
• [00:23] Andrei’s technical background and Dexory’s mission in logistics intelligence
• [01:07] How autonomous robots create digital twins of warehouses
• [01:55] The challenge of building AI for industry versus consumer data
• [03:21] Real-world use cases and the impact of data-driven operations
• [05:00] Continuous visibility as the foundation for smarter decision-making
• [07:11] Measuring ROI and customer results, including a £200K savings
• [08:54] The future of intelligent automation and accelerated adoption
• [10:42] How AI and robotics enhance, not replace, human work
• [11:13] Final takeaway: embracing rapid technological change

Links/Resource

Website: Dexory - https://www.dexory.com/ 

LinkedIn: Andrei Danescu - https://www.linkedin.com/in/darthvader1/ 

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

As digital transformation accelerates and hybrid environments scale, enterprise networks face unprecedented demand. In this episode, Andrew Wertkin, Chief Strategy Officer at BlueCat, joins Amanda Razani to break down how network architectures must evolve to support rapid change, rising data volumes, and increasing cybersecurity threats. He explains why observability is now foundational, how SD-WAN and edge computing are shifting performance expectations, and why automation and self-healing networks will define the next era of operations. Listeners will gain insights into modernizing infrastructure, strengthening security, and preparing for AI-driven demands.

Summary

Andrew Wertkin, Chief Strategy Officer at BlueCat, discusses how enterprise networks are being reshaped by cloud adoption, digital transformation, and rapid innovation. He explains the shift from slow, planned change windows to continuous, DevOps-style network updates that require flexibility, delegated control, and strong guardrails. Wertkin emphasizes the importance of observability for understanding the impact of frequent changes and preventing outages. He highlights challenges created by siloed tools, rising data demands, AI-driven threats, and the need for updated quality-of-service strategies. Looking ahead, he predicts a move toward automated, self-healing networks that can scale, remediate issues, and adapt automatically to business needs.

Key Quotes:

• “Rapid innovation breaks what normal looked like.”
• “If you can’t understand the impact of change, you’re going to create an outage.”
• “The pipes are being filled up—bandwidth can’t be taken for granted anymore.”
• “Networks will become self healing and able to scale without human intervention.”
• “Don’t change something if you can’t see it.”

Takeaways

• Enterprise networks must evolve to support continuous, rapid change.
• Observability is essential for managing risk, performance, and the impact of modifications.
• AI introduces both new threats and new tools for defense.
• SD-WAN and edge computing improve availability but create new bandwidth and QoS challenges.
• The future points to automated, self-healing networks with less manual intervention.
• Security and networking teams must shift from blockers to business enablers.

Timestamps

• 00:02 – Introduction & Guest Bio
• 01:03 – Evolution of Network Architecture
• 04:18 – Observability & Network Management
• 07:47 – Network Security & AI
• 11:53 – SD-WAN, Edge Computing & Performance
• 15:01 – The Future of Network Operations
• 17:06 – Key Takeaway & Closing

Links/Resource

Website: BlueCat - https://securiti.ai/author/cassandra-maldini/ 

LinkedIn:  Andrew Wertkin - https://www.linkedin.com/in/awertkin/ 

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

In this dynamic episode, Qlik CTO Sam Pierson reveals how smart, data-driven decisions and a rock-solid data strategy pave the way for AI success. He explains the rise of agentic AI and what it means for your business, and shares how to set clear goals, measure ROI, and sidestep common tech missteps. Pierson also shares essential tips on leveraging the low-code and AI-assisted development boom, plus the career skills you need to thrive in tomorrow’s rapidly evolving technology landscape.

Summary

Sam Pierson brings his perspective as Qlik’s CTO to the table, diving into the transformative journey businesses face when they harness AI alongside a strategic approach to data. He shares the practical realities of how companies are adopting task-focused AI agents, why well-maintained data is critical for real results, and the ways Qlik is empowering organizations to blend flexibility with robust analytics across their tech ecosystem. The conversation spotlights overcoming past challenges in data management, setting clear goals for ROI, and navigating the surge in AI-assisted and low-code development. Throughout, Sam underscores that genuine innovation starts with clarity and experimentation, always anchored by a solid data strategy at the foundation.

Key Quotes:

• "The real breakthrough with AI comes when your agents can safely leverage your company’s own proprietary data."
• "Unlike the past, adopting modern AI systems is easier than ever because you can access powerful models simply through an API."
• "Every successful technology project needs to begin with clear metrics to guide what you want to achieve and how you’ll measure it."
• "AI-assisted development tools now make it possible to rapidly turn ideas into real products, changing the pace of innovation."
• "While AI is transforming everything, the success of these initiatives always comes back to building from a strong data foundation."

Takeaways

• Ensuring your proprietary data is well-structured is the foundation of successful AI initiatives.
• Modern AI solutions are easier to implement than ever before, thanks to accessible APIs and cloud platforms.
• Setting clear, measurable goals and metrics is essential for tracking the success and return on investment of new technologies.
• Companies should embrace both established vendors and innovative development tools to remain adaptable and competitive.
• Experimentation, piloting projects, and developing a deliberate data strategy are critical for technologists aiming to thrive in a rapidly evolving landscape.

Timestamps

• 00:00:00 – Introduction and Guest Background
• 00:01:17 – The Shift Toward Task-Specific AI Agents
• 00:03:20 – Data as the Key to AI Success
• 00:05:10 – Overcoming Historical Technology Hurdles
• 00:06:02 – Qlik’s Approach to Data Solutions
• 00:07:58 – Measuring ROI and Setting Metrics
• 00:09:43 – The Rise of Vibe Coded Applications
• 00:12:21 – Gaps and Opportunities in Tech Careers
• 00:13:45 – Key Takeaways and Closing Remarks

Links/Resource

Website: Qlick - https://www.qlik.com/us 

LinkedIn:  Sam Pierson - https://www.linkedin.com/in/samuelpierson/ 

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

Can AI really revolutionize insurance? Amanda Razani interviews Sonny Patel, CPO and CTO of Socotra, to explore how artificial intelligence is transforming the industry. Patel explains how Socotra’s policy administration system leverages AI to streamline policy management, boost efficiency, and support better decision‑making. She highlights AI’s role in document intake and data summarization, helping underwriters make smarter choices, and notes the industry’s shift from building custom AI models to using pre‑built tools like ChatGPT and AWS Bedrock for enhanced security. Patel also emphasizes the importance of explainability in AI and encourages professionals to stay curious and experiment with emerging technologies to drive innovation in insurance.

Summary

Amanda Razani interviews Sonny Patel, the Chief Product Officer and Chief Technology Officer of Socotra, focusing on how artificial intelligence is transforming the insurance industry. Sonny shares her professional journey, highlighting her work at top technology companies such as Microsoft and Amazon, where she contributed to projects like Alexa’s voice recognition. She explains that Socotra is utilizing artificial intelligence to make insurance processes more efficient, particularly in managing document intake and providing clear insights to underwriters. Sonny emphasizes that artificial intelligence can help carriers make decisions that match their specific guidelines, while still keeping human expertise involved in the process.

The conversation further explores how the skills required for implementing artificial intelligence have evolved as tools become increasingly accessible for everyday users. Sonny mentions the shift from building foundational machine learning models to creating user-friendly applications, making artificial intelligence easier to adopt in business operations. Discussions around regulation and security underline the importance of explainable artificial intelligence and the need for guardrails to ensure data privacy and maintain trust. In closing, Sonny encourages professionals to remain curious and experiment with artificial intelligence, recognizing its potential to improve job satisfaction and efficiency, even if the technology is not yet perfect.

Key Quotes:

• "I would say we should just get very curious about what this technology can enable us to do."
• "What I feel is the most practical right in front of us is, I think there is a lot of capabilities available to us today that, in my opinion, not everybody is utilizing to their fullest."

Takeaways

• Advancements in artificial intelligence are making insurance processes more efficient by automating complex tasks like document intake and decision support for underwriters.
• Leveraging AI technology allows insurance carriers to make choices that align more closely with their specific risk guidelines and maintain human oversight in critical decisions.

Timestamps

• 0:00:02 Introduction and Guest Background
• 0:01:36 How AI Is Impacting the Insurance Industry
• 0:04:34 AI’s Influence on Insurance Approval Decisions
• 0:06:53 Skills Needed and Accessibility of AI Tools
• 0:12:00 Regulations and Data Security for AI
• 0:15:05 The Future of AI and Industry Speculation
• 0:18:42 Key Takeaways and Final Thoughts

Links/Resource

Website: Socotra - https://www.socotra.com/ 

LinkedIn: Sonny Patel - https://www.linkedin.com/in/sonpat/ 

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

As drones move from niche gadgets to everyday infrastructure, they’re also becoming a new kind of storytelling canvas. In this episode, Jamar Williams, CEO and founder of Promo Drone, joins host Amanda Razani to share how his team is turning drones into flying video messaging boards for fan engagement, advertising, and public safety. Jamar explains how transparent aerial messaging can shift public perception of drones, how his systems are used at major events, and why law enforcement and emergency responders are paying attention. He also dives into regulations, cost and ROI, and his journey from music production and videography into building a drone-tech company.

Summary

Jamar Williams, founder and CEO of Promo Drone, is transforming drones from mysterious flying cameras into community-friendly communication tools by outfitting them with LED video displays—essentially “flying television screens”—that deliver targeted messages at live events, festivals, stadiums, and public safety scenarios. Based in San Diego, Promo Drone makes the purpose of each drone clear, whether it's showcasing promotions, fan experiences, QR codes, or urgent alerts like road closures and missing persons notices. Williams explains how the platform operates within FAA Part 107 regulations, including weight limits and crowd safety, and shares deployment strategies like offset “drone zones” at venues. He also explores the broader drone entertainment landscape, highlighting environmental benefits over fireworks and detailing how Promo Drone is building a turnkey advertising network that links brands, events, and drone operators. He concludes with advice for aspiring drone entrepreneurs, emphasizing creativity, problem-solving, and the importance of building something that endures.

Key Quotes:

• “We wanted to make drones more community friendly by being more transparent, more visible, and clearly understood.”
• “It’s literally a flying video screen—like a mobile, hyper-targeted digital billboard in the sky.”
• “People have fear of what they don’t know or why a drone is there.”

Takeaways

• Drones become far more community friendly when they display transparent, visible messages that clearly show why they’re in the air.
• Flying LED screens create new layers of fan engagement through dynamic, interactive, and hyper-targeted content.
• The same drone messaging technology used for ads can be deployed for public safety alerts and emergency communication.
• FAA Part 107 rules shape how Promo Drone designs and deploys its systems, especially around weight limits and crowd safety.

Timestamps

• 00:02 – Introduction & Guest Bio
• 01:05 – What Is Promo Drone?
• 03:40 – From Ads to Public Safety
• 05:50 – How Flying Digital Screens Work
• 07:25 – FAA Part 107 & Drone Specs
• 08:50 – Safety, Crowds & Venue Operations
• 10:15 – Jamar’s Journey into Drones
• 11:45 – The Drone Entertainment Landscape
• 13:50 – Cost, Value & Social Media Buzz
• 15:40 – Environmental Impact of Drones
• 16:50 – Getting Into the Drone Business
• 19:05 – Key Takeaway & Final Message
• 19:50 – Closing & Call to Action

Links/Resource

Website: Promo Drone - https://securiti.ai/author/cassandra-maldini/ 

LinkedIn:  Jamar Williams - https://www.linkedin.com/in/jamarwilliamsceopromodrone/ 

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

AI and data are converging faster than ever before. In this episode of Full Tech Ahead, host Amanda Razani sits down with Szymon Kulec, Lead Developer Advocate at RavenDB, to discuss how the future of data management and AI integration is unfolding. Kulec explains how RavenDB’s native AI agents, vector search, and secure data architecture empower developers to move faster while maintaining compliance and governance.

Summary

Szymon Kulec brings his experience as a computer scientist and developer advocate to explore how RavenDB, a NoSQL distributed database, is bridging the gap between data systems and artificial intelligence. He explains that RavenDB is designed to make data handling “as boring as possible” for developers — reliable, seamless, and automatically managed.

The conversation dives into RavenDB’s native AI agents, which operate close to the data for both performance and security. These agents integrate safely with AI models through the Model Context Protocol (MCP), ensuring data is queried efficiently and responsibly. Sensitive information, such as payroll or health data, can be tightly restricted to prevent prompt injection, data leaks, or jailbreaks.

Kulec highlights the importance of real-time data in powering modern AI applications. With tools such as vector search, semantic queries, and RAG (retrieval-augmented generation), RavenDB enables AI models to access the most relevant, up-to-date data without manual intervention. This balance of openness, safety, and accessibility gives organizations the agility to maintain control and comply.

Looking to the future, he predicts that the integration between databases and AI will become even more automated. Developers will rely less on writing extensive glue code and more on configurable systems that “just work.” As AI becomes embedded into every layer of data infrastructure, tools like RavenDB will help enterprises remain efficient, secure, and compliant.

Quotes

• “We put the agents as close to data as possible and as safe as possible.”
• “With RavenDB, if you forbid it to query certain data, it will be strictly forbidden. The contract will not be breached.”
• “RavenDB tries to be as boring as possible for you as the end user, which is a good thing — it just works.”

Takeaways

• RavenDB is a NoSQL database offering powerful indexing, sharding, and distributed data capabilities with integrated AI features.
• Native AI agents within RavenDB interact directly and safely with data, ensuring compliance with privacy and security requirements.
• Using open standards like the Model Context Protocol enables controlled AI behavior, reducing risks of data breaches or prompt injections.

Timestamps

[00:00] Introduction — Amanda Razani and Szymon Kulec
[00:28] Background and overview of RavenDB
[01:25] What makes NoSQL different from traditional SQL databases
[02:33] How RavenDB integrates native AI agents
[04:50] The importance of real-time data and retrieval-augmented generation
[06:59] Balancing developer speed with data safety and compliance
[09:22] The evolving relationship between AI and databases
[11:14] Real-world example: building an HR app in under 700 lines of code
[12:00] Key takeaway: use tools wisely and automate whenever possible

Links / Resources

Website: RavenDB - https://ravendb.net

 LinkedIn: Szymon Kulec - https://www.linkedin.com/in/szymon-kulec/
Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

AI chatbots are reshaping customer interactions, but they also introduce new risks. In this episode of Full Tech Ahead, host Amanda Razani sits down with Andre Scott, Developer Advocate at Coralogix, to discuss how businesses can protect themselves from chatbot failures, misinformation, and data leaks.

Coralogix provides a full-stack observability and monitoring platform that includes logs, metrics, traces, APM, and AI observability. Scott explains how organizations can instrument their AI systems for transparency using open telemetry and evaluation tools, ensuring chatbots remain compliant, secure, and reliable as regulations tighten across industries.

Summary

Andre Scott shares insights into the current challenges of managing AI chatbots in enterprise environments. Unlike traditional deterministic systems, chatbots are non-deterministic—meaning even successful responses can fail catastrophically. Scott emphasizes that businesses must move beyond static monitoring to adopt AI evaluation engines that assess correctness, detect prompt injection, and ensure chatbots stay on topic.

He outlines a roadmap for companies:

• Instrument chatbots with open telemetry and trace kits.
• Integrate evaluation layers to analyze model behavior in real time.
• Comply with evolving regulations around data protection and AI accountability.

Failure to do so can lead to reputational and regulatory damage, as seen in incidents like Air Canada, DPD, and Chevrolet’s chatbot misfires. Scott also highlights the benefits of chatbots for customer support and productivity when they’re properly evaluated and monitored. Looking ahead, he predicts a future of voice-enabled and multimodal AI agents, which will bring both innovation and new oversight challenges.

Quotes

• “Evaluation is the crown jewels when it comes to these agentic AI workflows.”
• “Traditional monitoring shows a 200 OK, but with AI, that doesn’t mean success — it could still be failing catastrophically.”
• “Do you really own your code? You need open-source instrumentation to truly understand what’s happening inside your models.”

Takeaways

• AI chatbots require evaluation, not just monitoring. Traditional success metrics don’t capture AI logic failures.
• Open-source instrumentation such as LM Trace Kit and OpenTelemetry enables visibility into chatbot behavior.
• Compliance and privacy risks including GDPR, HIPAA, and data leakage demand proactive observability.

Timestamps

[00:00] Introduction — Andre Scott and Coralogix

[01:00] AI chatbot failures: Air Canada, NYC, and Chevrolet

[01:30] Why chatbots still fail and the problem of non-determinism

[03:00] How evaluation engines detect errors and hallucinations

[03:40] Integrating evaluators and open telemetry

[05:00] Repercussions of poor chatbot oversight

[06:20] Compliance and regulation readiness

[07:30] Business benefits of responsible AI chatbot use

[08:20] Future trends including speech-to-speech and multimodal chatbots

[08:57] Key takeaway: own your code, monitor everything, and evaluate always

Links / Resources

Website: Coralogix - https://coralogix.com/

LinkedIn: Andre Scott - https://www.linkedin.com/in/andre-scott/

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

AI is escaping the screen and stepping into the physical world. In this episode of Full Tech Ahead, host Amanda Razani talks with Mat Gilbert, Director of AI and Data at Synapse, about how intelligent systems are being embedded into real-world products and machines. Gilbert explains how “physical AI” — the next evolution beyond generative models — is already powering robotics, logistics, and industrial automation, and what this means for the future of work.

Summary

Mat Gilbert leads the AI and Data division at Synapse, where his team creates the intelligence that powers next-generation physical products. He describes physical AI as the “third wave” of artificial intelligence, following perception and generative AI. This new phase gives machines the ability to act and interact with the world, turning data-driven insights into real-world motion. Gilbert shares how industries like logistics, agriculture, and manufacturing are already using agentic AI to automate complex physical tasks once handled by humans.

He also highlights how decreasing hardware costs, new robotics foundation models, and advanced simulation tools are accelerating adoption. Companies such as Boston Dynamics, Tesla, and Figure AI are taking different approaches to humanoid robotics, each aiming to balance agility, intelligence, and scalability. Gilbert stresses that safety must be at the core of every design, since physical AI operates in irreversible real-world environments. Within the next two years, he predicts that pilot projects will evolve into full-scale deployments, with autonomous systems becoming an ordinary part of everyday life.

Key Quotes:

“We are moving from chatbots that book hotels to intelligent hotel rooms that adapt in real time.”
“Physical AI is where intelligence learns to act, perceive, and reason in the real world.”
“Hardware and sensor costs are falling fast, making robotics accessible to everyone.”
“In digital AI, errors can be undone. In physical AI, they can cause harm, so safety must come first.”
“This is no longer science fiction. It is happening right now and expanding quickly.

Takeaways

Physical AI represents the third major stage of artificial intelligence, focused on action and interaction.
Falling costs for sensors, batteries, and computing power are making advanced robotics attainable.
Early use cases appear in structured environments like warehouses and farms before expanding to homes and cities.
Humanoid robot development follows three main paths: agility, intelligence, and mass production.
Safety, reliability, and ethical design are essential as digital intelligence takes physical form.
Large-scale deployments of agentic AI systems are expected within the next few years.

Timestamps

[00:00] Introduction — Amanda Razani and Mat Gilbert
[00:24] Matt’s role at Synapse and how his team builds intelligent products
[01:06] Defining the “third wave” of AI: from perception to generation to action
[02:33] Early examples of physical AI in industry and logistics
[03:24] Falling hardware costs and new robotics foundation models
[04:36] Humanoid-robot development: Boston Dynamics, Tesla, Figure AI
[06:52] Real-world use cases — agriculture, manufacturing, and logistics
[08:09] The unique safety risks of physical AI vs digital AI
[09:18] Two-year outlook: from pilot programs to scaled deployments
[11:39] Key takeaway: physical AI is happening now, not in the distant future

Links/Resource

Website: Synapse Product Development - https://www.synapse.com/ 
LinkedIn: Mat Gilbert - https://www.linkedin.com/in/mat-gilbert/
Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/

In this episode of Full Tech Ahead, host Amanda Razani sits down with Patrick Sayler to explore the growing threat of AI-powered social engineering. As Director of Social Engineering at NetSPI, Patrick has seen firsthand how attackers exploit human psychology to breach even the most secure systems. From SMS phishing to voice cloning and Deepfakes, he explains how the lines between real and artificial are becoming increasingly blurred.

Patrick’s insights offer a sobering reminder that while cybersecurity defenses continue to evolve, the human element remains the most vulnerable link. He shares real-world examples from his work simulating attacks on major enterprises, along with practical advice for business leaders looking to strengthen their organizations against manipulation and deception.

Summary

Patrick Sayler, Director of Social Engineering at NetSPI, discusses the rising threats of SMS phishing and AI voice cloning. He highlights that SMS phishing is increasingly common, while AI voice cloning allows attackers to impersonate individuals using short audio clips. Saylor emphasizes the importance of secondary verification methods like email or Slack to prevent scams. He notes that phone calls remain a significant blind spot for security measures. For proactive defense in 2025, he recommends continuous training and phishing exercises. He also shares a personal anecdote about bypassing multi-factor authentication using a lab coat and mask, underscoring the human element's vulnerability to social engineering.

Key Quotes

• "AI voice cloning is the new big, big, hot thing to look out for."
• "Even with advanced technology, people remain the weakest link."
• "You can't trick someone if they don't respond to it."
• “The easiest way to stop it is to just not answer your phone.”
• “Phone calls are the biggest blind spot for both people and organizations.”
• “These attacks aren’t new — the barrier to entry is just lower now.”
• “You can’t trick someone if they don’t respond to it.”

Takeaways

• Voice cloning is the next major frontier in cyber deception.
• Secondary verification (e.g., Slack, Teams, or email) is critical before acting on phone requests.
• Continuous training and simulated phishing campaigns build awareness and resilience.
• Report incidents immediately—don’t hide mistakes.
• Human behavior is the weakest link, not technology.
• Low-tech methods still work because attackers exploit trust, not just tools.
  
  
  

Timestamps

• [00:00] Introduction to Patrick Sayler and NetSPI
• [01:20] Trends in social engineering: SMS phishing and AI voice cloning
• [02:50] How to defend against AI-driven deception
• [04:10] Human blind spots and phone-based attacks
• [05:30] Proactive social engineering defense for 2025
• [07:00] Financial fraud and voice cloning
• [08:20] Deepfake video risks and a real-world case study
• [10:00] Final takeaway: “Don’t talk to people — let it go to voicemail.”

Links/Resource

Website: netspi.com - https://www.netspi.com/

LinkedIn: Patrick Sayler -  https://www.linkedin.com/in/psayler/

Podcast: Full Tech Ahead — Hosted by Amanda Razani

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/