Eye On A.I.

• #287 Sahil Bansal: Why Developers Are Switching to CodeRabbit's AI Code Reviews

  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. 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: https://www.coderabbit.ai/ Stay Updated: Craig Smith on X:https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI (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)

  Discover how Sema4.ai 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: https://x.com/craigssEye on A.I. on X: https://x.com/EyeOn_AI (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

  Enterprise AI Agents for Work, Service and Process: www.kore.ai Kore.ai 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:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (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

  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: https://www.abstract.us

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• #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:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (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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