Eye On A.I.
Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.
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#313 Jonathan Wall: AI Agents Are Reshaping the Future of Compute Infrastructure
01/11/2026
#313 Jonathan Wall: AI Agents Are Reshaping the Future of Compute Infrastructure
In this episode of Eye on AI, Craig Smith speaks with Jonathan Wall, founder and CEO of Runloop AI, about why AI agents require an entirely new approach to compute infrastructure. Jonathan explains why agents behave very differently from traditional servers, why giving agents their own isolated computers unlocks new capabilities, and how agent-native infrastructure is emerging as a critical layer of the AI stack. The conversation also covers scaling agents in production, building trust through benchmarking and human-in-the-loop workflows, and what agent-driven systems mean for the future of enterprise work. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Why AI Agents Require a New Infrastructure Paradigm (01:38) Jonathan Wall’s Journey: From Google Infrastructure to AI Agents (04:54) Why Agents Break Traditional Cloud and Server Models (07:36) Giving AI Agents Their Own Computers (Devboxes Explained) (12:39) How Agent Infrastructure Fits into the AI Stack (14:16) What It Takes to Run Thousands of AI Agents at Scale (17:45) Solving the Trust and Accuracy Problem with Benchmarks (22:28) Human-in-the-Loop vs Autonomous Agents in the Enterprise (27:24) A Practical Walkthrough: How an AI Agent Runs on Runloop (30:28) How Agents Change the Shape of Compute (34:02) Fine-Tuning, Reinforcement Learning, and Faster Iteration (38:08) Who This Infrastructure Is Built For: Startups to Enterprises (41:17) AI Agents as Coworkers and the Future of Work (46:37) The Road Ahead for Enterprise-Grade Agent Systems
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#312 Anurag Dhingra: Inside Cisco’s Vision for AI-Powered Enterprise Systems
01/07/2026
#312 Anurag Dhingra: Inside Cisco’s Vision for AI-Powered Enterprise Systems
In this episode of Eye on AI, Craig Smith sits down with Anurag Dhingra, Senior Vice President and General Manager at Cisco, to explore where AI is actually creating value inside the enterprise. Rather than focusing on flashy demos or speculative futures, this conversation goes deep into the invisible layer powering modern AI: infrastructure. Anurag breaks down how AI is being embedded into enterprise networking, security, observability, and collaboration systems to solve real operational problems at scale. From self-healing networks and agentic AI to edge computing, robotics, and domain-specific models, this episode reveals why the next phase of AI innovation is less about chatbots and more about resilient systems that quietly make everything work better. This episodeis perfect for enterprise leaders, AI practitioners, infrastructure teams, and anyone trying to understand how AI moves from theory into production. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Why AI Only Matters If the Infrastructure Works (01:22) Cisco’s Evolution (04:39) Connecting Networks, People, and Experiences at Scale (09:31) How AI Is Transforming Enterprise Networking (12:00) Edge AI, Robotics, and Real-World Reliability (14:18) Security Challenges in an Agent-Driven Enterprise (15:28) What Agentic AI Really Means (Beyond Automation) (20:51) The Rise of Hybrid AI: Cloud Models vs Edge Models (24:30) Why Small, Purpose-Built Models Are So Powerful (29:19) Open Ecosystems and Agent-to-Agent Collaboration (33:32) How Enterprises Actually Adopt AI in Practice (35:58) Building AI-Ready Infrastructure for the Long Term (40:14) AI in Customer Experience and Contact Centers (44:14) The Real Opportunity of AI and What Comes Next
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#311 Stefano Ermon: Why Diffusion Language Models Will Define the Next Generation of LLMs
01/04/2026
#311 Stefano Ermon: Why Diffusion Language Models Will Define the Next Generation of LLMs
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. Most large language models today generate text one token at a time. That design choice creates a hard limit on speed, cost, and scalability. In this episode of Eye on AI, Stefano Ermon breaks down diffusion language models and why a parallel, inference-first approach could define the next generation of LLMs. We explore how diffusion models differ from autoregressive systems, why inference efficiency matters more than training scale, and what this shift means for real-time AI applications like code generation, agents, and voice systems. This conversation goes deep into AI architecture, model controllability, latency, cost trade-offs, and the future of generative intelligence as AI moves from demos to production-scale systems. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Autoregressive vs Diffusion LLMs (02:12) Why Build Diffusion LLMs (05:51) Context Window Limits (08:39) How Diffusion Works (11:58) Global vs Token Prediction (17:19) Model Control and Safety (19:48) Training and RLHF (22:35) Evaluating Diffusion Models (24:18) Diffusion LLM Competition (30:09) Why Start With Code (32:04) Enterprise Fine-Tuning (33:16) Speed vs Accuracy Tradeoffs (35:34) Diffusion vs Autoregressive Future (38:18) Coding Workflows in Practice (43:07) Voice and Real-Time Agents (44:59) Reasoning Diffusion Models (46:39) Multimodal AI Direction (50:10) Handling Hallucinations
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#309 Jamie Metzl: Why Gene Editing Needs Governance Or We Lose Control
12/24/2025
#309 Jamie Metzl: Why Gene Editing Needs Governance Or We Lose Control
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. Why are AI, biotechnology, and gene editing converging right now, and what does that mean for the future of humanity? In this episode of Eye on AI, host Craig Smith sits down with futurist and author Jamie Metzl to explore the superconvergence of artificial intelligence, genomics, and exponential technologies that are reshaping life on Earth. We examine the ethical and scientific realities behind human genome editing, the controversy around CRISPR babies, and why society is not yet ready to edit human embryos at scale. The conversation unpacks the complexity of biology, the risks of tech driven hubris, and why governance, values, and social norms must evolve alongside scientific breakthroughs. You will also hear a wide ranging discussion on health span versus longevity, AI and human decision making, education and inequality, and how these technologies could either unlock massive human flourishing or deepen existing global challenges depending on the choices we make today. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#308 Christopher Bergey: How Arm Enables AI to Run Directly on Devices
12/19/2025
#308 Christopher Bergey: How Arm Enables AI to Run Directly on Devices
Try OCI for free at This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved. Why is AI moving from the cloud to our devices, and what makes on device intelligence finally practical at scale? In this episode of Eye on AI, host Craig Smith speaks with Christopher Bergey, Executive Vice President of Arm's Edge AI Business Unit, about how edge AI is reshaping computing across smartphones, PCs, wearables, cars, and everyday devices. We explore how Arm v9 enables AI inference at the edge, why heterogeneous computing across CPUs, GPUs, and NPUs matters, and how developers can balance performance, power, memory, and latency. Learn why memory bandwidth has become the biggest bottleneck for AI, how Arm approaches scalable matrix extensions, and what trade offs exist between accelerators and traditional CPU based AI workloads. You will also hear real world examples of edge AI in action, from smart cameras and hearing aids to XR devices, robotics, and in car systems. The conversation looks ahead to a future where intelligence is embedded into everything you use, where AI becomes the default interface, and why reliable, low latency, on device AI is essential for creating experiences users actually trust. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#307 Steven Brightfield: How Neuromorphic Computing Cuts Inference Power by 10x
12/16/2025
#307 Steven Brightfield: How Neuromorphic Computing Cuts Inference Power by 10x
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. Why is AI so powerful in the cloud but still so limited inside everyday devices, and what would it take to run intelligent systems locally without draining battery or sacrificing privacy? In this episode of Eye on AI, host Craig Smith speaks with Steve Brightfield, Chief Marketing Officer at BrainChip, about neuromorphic computing and why brain inspired architectures may be the key to the future of edge AI. We explore how neuromorphic systems differ from traditional GPU based AI, why event driven and spiking neural networks are dramatically more power efficient, and how on device inference enables faster response times, lower costs, and stronger data privacy. Steve explains why brute force computation works in data centers but breaks down at the edge, and how edge AI is reshaping wearables, sensors, robotics, hearing aids, and autonomous systems. You will also hear real world examples of neuromorphic AI in action, from smart glasses and medical monitoring to radar, defense, and space applications. The conversation covers how developers can transition from conventional models to neuromorphic architectures, what role heterogeneous computing plays alongside CPUs and GPUs, and why the next wave of AI adoption will happen quietly inside the devices we use every day. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#306 Jeffrey Ladish: What Shutdown-Avoiding AI Agents Mean for Future Safety
12/07/2025
#306 Jeffrey Ladish: What Shutdown-Avoiding AI Agents Mean for Future Safety
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. Why do some AI agents attempt to bypass shutdown, and what does this behavior reveal about the future of AI safety? In this episode of Eye on AI, host Craig Smith speaks with Jeffrey Ladish of Palisade Research to examine what recent shutdown experiments with agentic LLMs tell us about control, alignment, and the real world limits of current guardrails. We explore how models behave when placed in virtual machine environments, why some agents edit or disable their own shutdown scripts, and what these results mean for researchers working on alignment and oversight. Learn how different models respond to shutdown instructions, how system prompts influence behavior, and which failure modes matter most for safe deployment. You will also hear a detailed breakdown of the experimental setups, insights into tool using and self directed behavior, and a grounded discussion of the risks and opportunities that agentic systems introduce. This episode offers a clear and practical look at how AI agents operate under pressure and what these findings mean for the future of safe and reliable AI. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#305 Rakshit Ghura: How Lenovo Is Turning AI Agents Into Digital Coworkers
12/03/2025
#305 Rakshit Ghura: How Lenovo Is Turning AI Agents Into Digital Coworkers
Why are enterprises struggling to turn AI hype into real workplace transformation, and how is Lenovo using agentic AI to actually close that gap? In this episode of Eye on AI, host Craig Smith talks with Rakshit Ghura about how his team is reinventing the modern workplace with an omnichannel AI architecture powered by a fleet of specialized agents. We explore how Lenovo has evolved from a hardware company into a global solutions provider, and how its Care of One platform uses persona based design to improve employee experience, reduce downtime, and personalize support across IT, HR, and operations. You will learn what enterprises get wrong about AI readiness, why trust and change management matter more than technology, and how organizations can design workplace stacks that meet employees where they are. We also cover how Lenovo approaches responsible AI, how enterprises should think about security and governance when deploying agents, and why so many organizations are enthusiastic about AI but still not ready to adopt it. Rakshit shares real examples from retail, manufacturing, and field operations, including how AI can improve uptime, automate ticket resolution, monitor equipment, and provide proactive insights that drive measurable business impact. You will also learn how to evaluate ROI for digital workplace solutions, how to involve employees early in the adoption cycle, and which metrics matter most when scaling agentic AI, including uptime, productivity improvements, and employee satisfaction. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#304 Matt Zeiler: Why Government And Enterprises Choose Clarifai For AI Ops
11/28/2025
#304 Matt Zeiler: Why Government And Enterprises Choose Clarifai For AI Ops
Try OCI for free at This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved. Why is AI inference becoming the new battleground for speed, cost, and real world scalability, and how are companies like Clarifai reshaping the AI stack by optimizing every token and every deployment? In this episode of Eye on AI, host Craig Smith sits down with Clarifai founder and CEO Matt Zeiler to explore why inference is now more important than training and how a unified compute orchestration layer is changing the way teams run LLMs and agentic systems. We look at what makes high performance inference possible across cloud, on prem, and edge environments, how to get faster responses from large language models, and how to cut GPU spend without sacrificing intelligence or accuracy. Learn how organizations operate AI systems in regulated industries, how government teams and enterprises use Clarifai to deploy models securely, and which bottlenecks matter most when running long context, multimodal, or high throughput applications. You will also hear how to optimize your own AI workloads with better token throughput, how to choose the right hardware strategy for scale, and how inference first architecture can turn models into real products. This conversation breaks down the tools, techniques, and design patterns that can help your AI agents run faster, cheaper, and more reliably in production. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#303 Fei-Fei Li: Spatial Intelligence, World Models & the Future of AI
11/23/2025
#303 Fei-Fei Li: Spatial Intelligence, World Models & the Future of AI
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. How will AI evolve once it can understand and reason about the 3D world, not just text on a screen? In this episode of Eye on AI, host Craig Smith speaks with Fei Fei Li about the rise of spatial intelligence and the world models that could transform how machines perceive, imagine, and interact with reality. We explore how spatial intelligence goes beyond language to connect perception, action, and reasoning in physical environments. You will hear how models like Marble build consistent and persistent 3D spaces, why multimodal inputs matter, and what it takes to create digital worlds that are useful for robotics, simulation, design, and creative workflows. Fei Fei also explains the challenges of long term memory, continuous learning, and the search for training objectives that mirror the role next token prediction plays in language models. Learn how spatial reasoning unlocks new possibilities in robotics and telepresence, why classical physics engines still matter, and how future AI systems may merge perception, planning, and imagination. You will also hear Fei Fei’s perspective on the limits of current architectures, why true understanding is different from human understanding, and how world models could shape the next generation of intelligent systems. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#302 Karl Friston: How the Free Energy Principle Could Rewrite AI
11/19/2025
#302 Karl Friston: How the Free Energy Principle Could Rewrite AI
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. How could Karl Friston’s Free Energy Principle become a blueprint for the future of AI? In this episode of Eye on AI, host Craig Smith sits down with Karl Friston, the neuroscientist behind the Free Energy Principle and advisor to Verses AI, to explore how active inference and brain inspired generative models might move us beyond transformer based systems. They unpack how Axiom, Verses’ new architecture, uses probabilistic beliefs and message passing to build agents that learn like brains instead of just predicting the next token. We look at why transformers face scaling and reliability limits, how Free Energy unifies prediction, perception, and action, and what it means for an AI system to carry explicit uncertainty instead of overconfident guesses. Learn how active inference supports continual learning without catastrophic forgetting, how structure learning lets models grow and prune themselves, and why embodiment and interaction with the real world are essential for grounding language and meaning. You will also hear how Axiom can sit beside or beneath large language models, how explicit uncertainty can reduce hallucinations in high stakes workflows, and where these ideas are already being tested in areas like logistics, robotics, and autonomous agents. By the end of the episode, you will have a clearer picture of how Karl Friston’s Free Energy blueprint could reshape AI architectures, from enterprise planning systems to embodied agents that understand and act in the world. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#301 Hemant Banavar & Ryan Ennis: The AI Safety System Driving Toward Zero Harm
11/16/2025
#301 Hemant Banavar & Ryan Ennis: The AI Safety System Driving Toward Zero Harm
How are AI and telematics changing safety for fleets in the real world, and what does it take to get from basic recordings to true accident prevention? In this episode of Eye on AI, host Craig Smith speaks with Hemant Banavar, Chief Product Officer at Motive, and Ryan Ennis, CIO at FusionSite Services, to explore how AI powered cameras and telematics are transforming safety, productivity, and profitability across the physical economy, from trucking and construction to field services. We look at what makes safety AI trustworthy at scale, how to reduce false alerts that drivers ignore, and how to combine in cab coaching, human review, and rich telematics data to drive down risky behaviors. Learn how FusionSite Services cut unsafe events by more than ninety percent while tripling in size, slashed insurance claims and premiums, and used real time insights to tackle idling, under utilized assets, and the hidden costs of unsafe operations. You will also hear how leading fleets run side by side vendor tests, design incentive programs that get drivers on board with cameras, and build a culture around zero preventable accidents. If you are responsible for safety, operations, or risk, this episode will show you how to evaluate AI and telematics platforms, which benchmarks to demand, and how to turn your data into safer roads and stronger unit economics. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#300 Fred Laluyaux: How Decision Intelligence & AI Agents Are Redefining Enterprise Operations
11/13/2025
#300 Fred Laluyaux: How Decision Intelligence & AI Agents Are Redefining Enterprise Operations
How are Decision Intelligence and AI agents reshaping enterprise operations today? In this episode of Eye on AI, host Craig Smith sits down with Fred Laluyaux, CEO of Aera Technology, to unpack how organizations move from dashboards and ad hoc workflows to a system that senses, decides, and acts. AI is not just about chatbots. At the heart of this transformation is decision intelligence: connecting data, analytics, AI, and automation to optimize decisions across the enterprise. Fred explains why this is becoming the operating backbone of the modern enterprise and how it accelerates the shift toward autonomous, self-driving businesses. We look at how to build a decision intelligence stack end to end, how AI agents collaborate with people, and how to stand up a control room that monitors decisions across supply chain, finance, and customer operations. Learn how leading companies model decisions, govern them safely, and measure impact with clear metrics that matter, including service level, cost to serve, cash flow, inventory turns, and time to resolution. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#299 Jacob Buckman: Why the Future of AI Won’t Be Built on Transformers
11/09/2025
#299 Jacob Buckman: Why the Future of AI Won’t Be Built on Transformers
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. Why do today’s LLMs forget key details over long context, and what would it take to give them real memory that scales? In this episode of Eye on AI, host Craig Smith explores Manifest AI’s Power Retention architecture and how it rethinks memory, context, and learning for modern models. We look at why transformers struggle with long inputs, how state space and retention models keep context at linear cost, and how scaling state size unlocks reliable recall across lengthy conversations, code, and documents. We also cover practical paths to retrofit existing transformer models, how in context learning can replace frequent fine tuning, and what this means for teams building agents and RAG systems. Learn how product leaders and researchers measure true long context quality, which pitfalls to avoid when extending context windows, and which metrics matter most for success, including recall consistency, answer fidelity, task completion, CSAT, and cost per resolution. You will also hear how to design per user memory, set governance that prevents regressions, evaluate LLM as judge with human review, and plan a secure rollout that improves retrieval, multi step workflows, and agent reliability across chat, email, and voice. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#298 Ryan Kolln: How Appen Trains the World’s Most Powerful AI Models
11/06/2025
#298 Ryan Kolln: How Appen Trains the World’s Most Powerful AI Models
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. How do the world’s most powerful AI models get trained and trusted at scale, and what does that really take from data to deployment? In this episode, Appen CEO Ryan Kolln joins Eye on AI to unpack how rigorous human evaluation, culturally aware data, and model-based judges come together to raise real-world performance. In this episode of Eye on AI, host Craig Smith speaks with Ryan Kolln, CEO of Appen, about building evaluation systems that go beyond static benchmarks to measure usefulness, safety, and reliability in production. They explore how human raters and AI evaluators work in tandem, why localization matters across regions and domains, and how quality controls keep feedback signals trustworthy for training and post-training. Ryan explains how evaluation feeds reinforcement strategies, where rubric-driven human judgments inform reward models, and how enterprises can stand up secure workflows for sensitive use cases. He also discusses emerging needs around sovereign models, domain-specific testing, and the shift from general chat to agentic workflows that operate inside real business systems. Learn how leading teams design human-in-the-loop evaluation, when to route judgments from models back to expert reviewers, how to capture cultural nuance without losing universal guardrails, and how to build an evaluation stack that scales from early prototypes to production AI. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#297 Jeff Lunsford: How Agentic AI Will Redefine Every Digital Interaction
10/30/2025
#297 Jeff Lunsford: How Agentic AI Will Redefine Every Digital Interaction
Why will agentic AI redefine every digital interaction, and what foundation do enterprises need to make it safe, trusted, and real time? In this episode of Eye on AI, host Craig Smith sits down with Jeff Lunsford to unpack how a neutral customer data platform like Tealium becomes the control plane for agentic systems. We cover how to collect and unify first party data responsibly, enforce consent and identity across channels, and feed the right context to models so agents can act with confidence in the moment. You will hear how real time profiles, event streams, and deterministic identity power personalization, automation, and transactions across web, mobile, ads, email, and customer support. Learn how leading enterprises are preparing for agentic commerce that could double digital interactions, why governance and privacy must be embedded into delivery teams, and which standards enable safe transactions and payments with agents. You will also hear how to build an “agentic front door” for your business, design guardrails and spending allowances, choose where to run reasoning and inference, and measure impact with metrics like conversion rate, ROAS, CSAT, and cost per resolution. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#296 Yeop Lee: How Coxwave is Redefining AI Evaluation
10/26/2025
#296 Yeop Lee: How Coxwave is Redefining AI Evaluation
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. How is Coxwave Redefining AI Evaluation? In this episode of Eye on AI, host Craig Smith is joined by Yeop Lee, Head of Product at Coxwave. Together they explore how teams move beyond accuracy-only metrics to outcome focused evaluation with Coxwave’s Align. We look at how Align measures satisfaction, trust, and task completion across chat, email, and voice, how LLM as judge pairs with human review, and how product teams search conversations to find hidden failure patterns that block adoption. Learn how leading companies design an evaluation stack that guides prompts, agents, and UX, which pitfalls to avoid when shipping updates, and which metrics matter most for success, including completion rate, CSAT, retention, and cost per resolution. You will also hear how to run experiment tracking with model and prompt change logs, set up governance that prevents regressions, and choose between SaaS and on premise deployments that meet security and compliance needs. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#295 Fergal Reid: Why Your Bots Fail and How Agents Fix Your Customer Support
10/19/2025
#295 Fergal Reid: Why Your Bots Fail and How Agents Fix Your Customer Support
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. Why do so many chatbots fail in the real world, and how can AI agents actually fix customer support? In this episode of Eye on AI, host Craig Smith explores how teams move beyond scripted bots to production-grade AI agents that resolve real issues across chat, email, and voice. We look at what makes agents reliable at scale, how to configure them safely, and how to manage them like digital workers alongside your human team. Learn how leading companies approach agent onboarding and governance, which pitfalls to avoid, and which metrics matter most for success, including resolution rate, CSAT, and cost per resolution. You will also hear how to enable actions like refunds and returns through secure procedures, design human handoff that customers appreciate, and build an omnichannel rollout plan that scales responsibly. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI
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#294 Bhaskar Roy: How Workato Is Building the Rise of the Agentic Enterprise
10/16/2025
#294 Bhaskar Roy: How Workato Is Building the Rise of the Agentic Enterprise
Try OCI for free at http://oracle.com/eyeonai This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved. How are enterprises moving from AI experiments to a true agentic enterprise with measurable ROI? In this episode of Eye on AI, host Craig Smith speaks with Bhaskar Roy from Workato about how organizations can design, orchestrate, and govern AI agents at scale without sacrificing security or control. Together they unpack Workato’s approach to building a single workspace for employees while agents and apps work behind the scenes to automate real business processes. They explain why the future of enterprise AI depends on orchestration, permissions, and human in the loop design. You will hear how Workato One and Workato Go bring connectivity, action, and governance into one stack, how teams assign KPIs to agents and track outcomes, and how to reduce agent sprawl while optimizing SaaS spend. Learn how leading companies are defining the agentic enterprise, what pitfalls to avoid when moving from pilots to production, and how to measure impact across sales, IT, support, HR, and finance so AI drives durable business value. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X:
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#293 Greg Shewmaker: How Enterprises Can Implement and Scale with Agentic AI
10/13/2025
#293 Greg Shewmaker: How Enterprises Can Implement and Scale with Agentic AI
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. How can enterprises truly scale with agentic AI? In this episode of Eye on AI, host Craig Smith speaks with Greg Shewmaker, CEO of r.Potential, about how organizations can successfully implement agentic AI systems that enhance human performance instead of replacing it. Greg explains why the future of work depends on a new partnership between people and intelligent digital agents. He shares how r.Potential, a spin-out from the Adecco Group, helps enterprises design “digital workforces,” integrate AI agents into complex systems, and rethink productivity from the C-suite down. Learn how leading companies are approaching AI adoption, what pitfalls to avoid, and why agentic AI could redefine how enterprises operate and grow in the years ahead. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI
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#292 Peeyush Ranjan: How Nurix Is Redefining Voice AI for the Enterprise
10/09/2025
#292 Peeyush Ranjan: How Nurix Is Redefining Voice AI for the Enterprise
Discover how Neurix is building the next generation of voice AI that sounds and reacts like a human in this conversation with Peeyush, former Google technologist and co-founder of Miracle Labs. Peeyush shares how Neurix is solving the toughest challenges in conversational AI — from eliminating latency to creating natural, real-time dialogue that mirrors human interaction. He explains why voice is the hardest frontier in AI, how Neurix’s proprietary models manage conversation flow, and what it takes to integrate voice agents into enterprise systems at scale. Learn how Neurix is combining low-latency speech recognition, dialogue management, and large language models to deliver seamless, multilingual customer experiences. If you’re a business leader, product builder, or AI professional interested in how human-like voice agents are transforming customer support and enterprise communication, this episode reveals the future of intelligent conversation. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#291 Naveen Jain: How AI Predicts Cancer, Diabetes & Chronic Illness
10/06/2025
#291 Naveen Jain: How AI Predicts Cancer, Diabetes & Chronic Illness
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. Can AI and RNA testing make illness optional? In this episode, Eye on AI host Craig S. Smith sits down with Naveen Jain, founder and CEO of Viome, to explore how RNA sequencing and artificial intelligence are transforming our understanding of chronic disease. Jain shares how a personal tragedy led him to launch Viome, a company on a mission to digitize the human body, predict illness before symptoms appear, and revolutionize healthcare. Together they discuss how Viome uses metatranscriptomics to analyze microbiome and human gene expression, what makes RNA a better indicator of health than DNA, and how large molecular AI models are paving the way for early detection of cancer, diabetes, Alzheimer’s, and more. Jain also reveals his bold entrepreneurial framework—“Why this, why now, why me?”—and his belief that asking better questions is the real key to innovation. If you’re interested in the intersection of AI, biotechnology, and human longevity, this is an episode you won’t want to miss. Stay Updated: Craig Smith on X: Eye on A.I. on X:
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#290 Joel Hron: How Thomson Reuters is Approaching The Next Era of AI
09/29/2025
#290 Joel Hron: How Thomson Reuters is Approaching The Next Era of AI
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit and add your support. Joel Hron, Chief Technology Officer at Thomson Reuters, joins Eye on AI to unpack the future of agentic systems and what it takes to build them responsibly at enterprise scale. We dive into the shift from prompt-based AI to true agentic workflows capable of planning, reasoning, and executing complex tasks. Joel breaks down how Thomson Reuters is deploying generative AI across law, tax, risk, and compliance, while keeping human experts in the loop to ensure trust and accuracy in high-stakes domains. Topics include: - What separates agentic AI from simple prompt-based tools - How “agency dials” (autonomy, tools, memory) change system behavior - Infrastructure and architecture required for multi-agent collaboration - Why human verification and user experience design are essential for trust - The future of coding, engineering skills, and AI adoption inside enterprises If you want to understand how a 170-year-old company is reinventing itself with AI — and what’s next for agentic systems in business and knowledge work — this conversation is a must-listen. Stay Updated: Craig Smith on X:Eye on A.I. on X:
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#289 Eiso Kant: How Reinforcement Learning and Coding Could Unlock Human-Level AI
09/24/2025
#289 Eiso Kant: How Reinforcement Learning and Coding Could Unlock Human-Level AI
How do we get from today’s AI copilots to true human-level intelligence? In this episode of Eye on AI, Craig Smith sits down with Eiso Kant, Co-Founder of Poolside, to explore why reinforcement learning + software development might be the fastest path to human-level AI. Eiso shares Poolside’s mission to build AI that doesn’t just autocomplete code — but learns like a real developer. You’ll hear how Poolside uses reinforcement learning from code execution (RLCF), why software development is the perfect training ground for intelligence, and how agentic AI systems are about to transform the way we build and ship software. If you want to understand the future of AI, software engineering, and AGI, this conversation is packed with insights you won’t want to miss. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) The Missing Ingredient for Human-Level AI(01:02) Eiso Kant’s Journey(05:30) Using Software Development to Reach AGI(07:48) Why Coding Is the Perfect Training Ground for Intelligence(10:11) Reinforcement Learning from Code Execution (RLCF) Explained(13:14) How Poolside Builds and Trains Its Foundation Models(17:35) The Rise of Agentic AI(21:08) Making Software Creation Accessible to Everyone(26:03) Overcoming Model Limitations(32:08) Training Models to Think(37:24) Building the Future of AI Agents(42:11) Poolside’s Full-Stack Approach to AI Deployment(46:28) Enterprise Partnerships, Security & Customization Behind the Firewall(50:48) Giving Enterprises Transparency to Drive Adoption
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#288 Florian Douetteau: How Enterprises Can Scale and Adopt Agentic AI
09/21/2025
#288 Florian Douetteau: How Enterprises Can Scale and Adopt Agentic AI
Discover how enterprises can successfully adopt and scale agentic AI to create real business impact in this conversation with Florian Douetteau, CEO and co-founder of Dataiku. Florian shares why democratizing AI across the enterprise is essential, how to prevent agent sprawl, and what it takes to build a governance framework that keeps your data secure while enabling innovation. Learn about Dataiku’s enterprise AI blueprint, its partnership with NVIDIA, and how global companies are using agentic workflows to accelerate R&D, optimize operations, and stay competitive. If you’re a business leader, CTO, or data professional looking to scale AI safely and effectively, this episode is your playbook for the future of enterprise AI. Stay Updated: Craig Smith on X: Eye on A.I. on X: 00:00 Intro 00:31 Florian’s Background & Dataiku’s Founding 03:00 Enterprise Blueprint for AI with NVIDIA 05:13 Unique Needs of Financial Services 07:09 Building Agents on Dataiku 09:22 Permissioning & Governance 11:17 Agent Lifecycle Management 13:20 State of Agent-to-Agent Systems 15:02 Real-World Use Cases of Agents 16:28 The Most Complex Agents in Production 19:01 Future Vision: Headless Organizations 21:04 Human-Like Qualities of Agents 24:56 The LLM Mesh & Model Abstraction 28:55 Guardrails & Compliance 31:12 No-Code + Code-Friendly Collaboration 36:12 Breaking Silos & Centers of Excellence 41:36 Distribution & Seat Allocation 43:34 Most Common Agents by Industry 47:02 The State of Enterprise AI Adoption
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#287 Sahil Bansal: Why Developers Are Switching to CodeRabbit's AI Code Reviews
09/17/2025
#287 Sahil Bansal: Why Developers Are Switching to CodeRabbit's AI Code Reviews
Try OCI for free at This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved. AI-generated code is exploding, but reviewing it all has become the new bottleneck for engineering teams. In this episode, Sahil Bansil from CodeRabbit reveals how their AI-powered platform is transforming the code review process, helping developers ship faster without compromising quality. He explains how CodeRabbit uses advanced LLM context engineering to deliver senior-level review quality, reduce pull request merge times by up to 50%, and catch more bugs before they reach production. Whether you’re a developer, engineering manager, or CTO, this conversation shows why automated code review is essential in the AI era and how CodeRabbit can help your team scale software delivery while keeping quality high. Cut Code Review Time & Bugs in Half. Instantly with CodeRabbit: Stay Updated: Craig Smith on X:Eye on A.I. on X: (00:00) LLMs & Why Context Matters (02:26) Meet Sahil Bansil from CodeRabbit (04:04) AI Code Boom & The Review Bottleneck (06:05) Why CodeRabbit Focused on Reviews, Not Generation (09:55) Keeping Humans in the Loop for Code Quality (14:30) IDE Reviews vs PR Governance (17:51) Inside CodeRabbit’s Context Engineering (20:42) Building Context from Code Graphs & Jira Tickets (22:15) Eliminating AI Hallucinations with Verification (27:19) Empowering Junior Developers & Legacy Code Support (32:40) CodeRabbit’s Open Source & Enterprise Success Stories (36:56) Cutting Review Times & PR Merge Delays (44:35) Scaling CodeRabbit & The Growing Market
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#286 Ram Venkatesh: How to Build, Operate & Scale Enterprise AI Agents (Sema4.ai)
09/14/2025
#286 Ram Venkatesh: How to Build, Operate & Scale Enterprise AI Agents (Sema4.ai)
Discover how is redefining enterprise AI with a platform built to help businesses build, operate, and scale SAFE AI agents. In this conversation, CTO and co-founder Ram Venkatesh explains why simply generating insights isn’t enough and why enterprises need AI that can act on those insights reliably, securely, and at scale. If you want to understand the future of agentic AI and how to safely scale AI across your organization, this episode is a must-watch. Stay Updated:Craig Smith on X: Eye on A.I. on X: (00:00) The Data-to-Action Gap (00:38) Ram’s Big Data Background (03:22) Why RPA Failed & Agents Win (04:39) Conversational Agents vs Manual Workflows (06:28) The Power of a Semantic Layer (08:20) Runbooks: Capturing Intent, Not Just Steps (11:16) Connecting Data Across Systems (15:12) How Sema4.ai Keeps AI Secure (17:37) From 20 to 2,000 Agents: Scaling the Fleet (20:20) Choosing the Right Agent Platform (26:22) Process Architects: The New Role in AI (29:00) Why Finance & Healthcare Lead in Adoption (30:04) Sema4.ai’s Pricing & Adoption Playbook (41:29) Scaling Faster with Snowflake Deployment (43:10) ISVs & Domain Experts as Agent Builders
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#285 Raj Koneru: How Kore.ai is Building No Code Enterprise-Grade Agentic AI
09/10/2025
#285 Raj Koneru: How Kore.ai is Building No Code Enterprise-Grade Agentic AI
Enterprise AI Agents for Work, Service and Process: founder and CEO Raj Koneru breaks down how enterprises are moving beyond chatbots into agentic AI that actually ships. We get into the no-code tooling behind multi-agent workflows, agentic RAG, guardrails that keep outputs in scope, and why a control layer for governance is now essential. Raj shares real scale numbers, the three Kore.ai product lanes for customer and employee experience, and how partnerships with Microsoft and AWS let teams build where they already run. If you care about building secure, explainable AI agents that integrate fast and scale cleanly, this one is for you. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Raj Koneru’s Journey & The Birth of Kore.ai (03:10) From Chatbots to Enterprise-Grade Agents(06:33) Security, Scale & Proof in the Market(07:04) What Agentic AI Really Means(12:16) Building & Governing AI Agents(17:26) Kore.ai’s Product Lines & Differentiation(20:22) Industry Applications & Case Studies(28:17) User Experience & Change Management(34:46) Governance, Identity & Cost Controls(39:56) Adoption Timelines & Market Outlook(43:51) Roadmap & Partnerships(47:38) Future of the Enterprise AI Landscape
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#284 Pat Utz: Inside Abstract, The AI That Decodes Laws and Regulations
09/07/2025
#284 Pat Utz: Inside Abstract, The AI That Decodes Laws and Regulations
What if AI could decode government in real time? In this episode of Eye on AI, Craig Smith sits down with Pat Utz, CEO and Co-Founder of Abstract, the AI startup building “regulatory superintelligence” to track and analyze laws, bills, and regulations across 145,000+ government entities. Pat explains how Abstract evolved from university research into a venture-backed company helping law firms, enterprises, and policymakers cut through the noise of Congress, state legislatures, and regulatory agencies. From uncovering hidden amendments in massive bills to proactively identifying risks and opportunities for businesses, Abstract is transforming how we understand legislation. We cover: How AI is reshaping lobbying, law, and compliance Why Abstract is focused on proactive intelligence, not reactive compliance The role of AI agents, LLMs, and retrieval-augmented generation (RAG) in policy analysis Real examples of AI influencing funding and legislation The future of democracy when citizens and businesses have true transparency into government Whether you’re in tech, law, government affairs, or just curious about how AI is changing democracy, this conversation reveals the future of policy intelligence. 🔗 Learn more about Abstract:
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#283 Andrei Danescu: How Dexory Uses AI & Robotics for Warehouse Management
09/03/2025
#283 Andrei Danescu: How Dexory Uses AI & Robotics for Warehouse Management
What if your warehouse could see everything, all the time? In this episode of Eye on AI, we sit down with Andrei Danescu, CEO & Co-Founder of Dexory, to explore how AI and robotics are transforming logistics. Andrei shares his journey from Formula 1 engineering to building one of the fastest-growing robotics companies in Europe. He explains how Dexory’s autonomous robots and real-time digital twins are giving warehouses unprecedented visibility, cutting errors, boosting efficiency, and even turning storage into a profit driver. We cover: Why warehouses struggle with visibility and how AI solves it The role of autonomous robots in scanning 10,000+ pallet locations per hour How digital twins unlock optimization in space, flow, and production Dexory’s vision for the future of supply chains across Europe and the US The balance between human workers and automation in logistics If you want to understand the future of logistics, warehouse technology, and supply chain visibility, this conversation will give you a front-row seat. Subscribe for more deep dives on AI, robotics, and the future of work. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Intro (02:08) The Birth of Dexory and Its Mission (04:23) Building Autonomous Robots and Digital Twins (08:52) Optimizing Space, Storage, and Traffic Flow (12:15) DexoryView: The Platform Behind the Robots (16:03) Humans, Robots, and the Future of Warehouses (18:54) AI, SLAM, and the Tech Driving Dexory (23:17) Real-Time Visibility and Error Elimination (27:31) Multi-Site Insights and Supply Chain Potential (32:47) Scaling Dexory: Markets, Adoption, and Growth (37:01) Scanning at Scale: 10,000+ Pallets Per Hour (41:11) Roadmap: AI Agents, Simulations, and Next Steps (45:13) A Vision for Global Logistics Networks
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