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    Technology

    Agentic Conversations (formally mlops.community)

    Relaxed conversations and technical deep dives around AI Agents. This Show is brought to you by the Agentic AI Foundation where the leading agentic open-source projects like MCP, Agents.md, and Goose live. See more at aaif.io

    Advertise

    Copyright: © Demetrios Brinkmann

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    Latest Episodes:
    The Future of AI Operations: Insights from PwC AI Managed Services Nov 14, 2025
    Show notes

    Rani Radhakrishnan is a Principal at PwC US, leading work on AI-managed services, autonomous agents, and data-driven transformation for enterprises.


    The Future of AI Operations: Insights from PwC AI Managed Services // MLOps Podcast #345 with Rani Radhakrishnan, Principal, Technology Managed Services - AI, Data Analytics and Insights at PwC US.


    Huge thanks to PwC for supporting this episode!


    Join the Community:

    https://go.mlops.community/YTJoinIn

    Get the newsletter: https://go.mlops.community/YTNewsletter


    // Abstract

    In today’s data-driven IT landscape, managing ML lifecycles and operations is converging.

    On this podcast, we’ll explore how end-to-end ML lifecycle practices extend to proactive, automation-driven IT operations.

    We'll discuss key MLOps concepts—CI/CD pipelines, feature stores, model monitoring—and how they power anomaly detection, event correlation, and automated remediation.


    // Bio

    Rani Radhakrishnan, a Principal at PwC, currently leads the AI Managed Services and Data & Insight teams in PwC US Technology Managed Services.

    Rani excels at transforming data into strategic insights, driving informed decision-making, and delivering innovative solutions. Her leadership is marked by a deep understanding of emerging technologies and a commitment to leveraging them for business growth.

    Rani’s ability to align and deliver AI solutions with organizational outcomes has established her as a thought leader in the industry.

    Her passion for applying technology to solve tough business challenges and dedication to excellence continue to inspire her teams and help drive success for her clients in the rapidly evolving AI landscape.


    // Related Links

    Website: https://www.pwc.com/us/managedservices

    https://www.pwc.com/us/en/tech-effect.html


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    Connect with Demetrios on LinkedIn: /dpbrinkm

    Connect with Rani on LinkedIn: /rani-radhakrishnan-163615


    Timestamps:

    [00:00] Getting to Know Rani

    [01:54] Managed services

    [03:50] AI usage reflection

    [06:21] IT operations and MLOps

    [11:23] MLOps and agent deployment

    [14:35] Startup challenges in managed services

    [16:50] Lift vs practicality in ML

    [23:45] Scaling in production

    [27:13] Data labeling effectiveness

    [29:40] Sustainability considerations

    [37:00] Product engineer roles

    [40:21] Wrap up


    GPU Uptime with VAST Data CTO Nov 11, 2025
    Show notes

    Andy Pernsteiner is the Field CTO at VAST Data, working on large-scale AI infrastructure, serverless compute near data, and the rollout of VAST’s AI Operating System.


    The GPU Uptime Battle // MLOps Podcast #346 with Andy Pernsteiner, Field CTO of VAST Data.Huge thanks to VAST Data for supporting this episode!


    Join the Community:

    https://go.mlops.community/YTJoinIn

    Get the newsletter:

    https://go.mlops.community/YTNewsletter


    // Abstract

    Most AI projects don’t fail because of bad models; they fail because of bad data plumbing. Andy Pernsteiner joins the podcast to talk about what it actually takes to build production-grade AI systems that aren’t held together by brittle ETL scripts and data copies. He unpacks why unifying data - rather than moving it - is key to real-time, secure inference, and how event-driven, Kubernetes-native pipelines are reshaping the way developers build AI applications. It’s a conversation about cutting out the complexity, keeping data live, and building systems smart enough to keep up with your models.


    // Bio

    Andy is the Field Chief Technology Officer at VAST, helping customers build, deploy, and scale some of the world’s largest and most demanding computing environments.


    Andy has spent the past 15 years focused on supporting and building large-scale, high-performance data platform solutions. From humble beginnings as an escalations engineer at pre-IPO Isilon, to leading a team of technical Ninjas at MapR, he’s consistently been in the frontlines solving some of the toughest challenges that customers face when implementing Big Data Analytics and next-generation AI solutions.


    // Related Links

    Website: www.vastdata.com

    https://www.youtube.com/watch?v=HYIEgFyHaxk

    https://www.youtube.com/watch?v=RyDHIMniLro

    The Mom Test by Rob Fitzpatrick: https://www.momtestbook.com/


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community

    [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    Connect with Demetrios on LinkedIn: /dpbrinkm

    Connect with Andy on LinkedIn: /andypernsteiner


    Timestamps:

    [00:00] Prototype to production gap

    [00:21] AI expectations vs reality

    [03:00] Prototype vs production costs

    [07:47] Technical debt awareness

    [10:13] The Mom Test

    [15:40] Chaos engineering

    [22:25] Data messiness reflection

    [26:50] Small data value

    [30:53] Platform engineer mindset shift

    [34:26] Gradient description comparison

    [38:12] Empathy in MLOps

    [45:48] Empathy in Engineering

    [51:04] GPU clusters rolling updates

    [1:03:14] Checkpointing strategy comparison

    [1:09:44] Predictive vs Generative AI

    [1:17:51] On Growth, Community, and New Directions

    [1:24:21] UX of agents

    [1:32:05] Wrap up



    The Evolution of AI in Cyber Security // Jeff Schwartzentruber // #344 Nov 04, 2025
    Show notes

    Dr. Jeff Schwartzentruber is a Senior Machine Learning Scientist at eSentire, working on anomaly detection pipelines and the use of large language models to enhance cybersecurity operations.


    The Evolution of AI in Cyber Security // MLOps Podcast #344 with Jeff Schwartzentruber, Staff Machine Learning Scientist at eSentire.


    Join the Community:

    https://go.mlops.community/YTJoinIn

    Get the newsletter: https://go.mlops.community/YTNewsletter


    // Abstract

    Modern cyber operations can feel opaque. This talk explains—step by step—what a security operations center (SOC) actually does, how telemetry flows in from networks, endpoints, and cloud apps, and what an investigation can credibly reveal about attacker behavior, exposure, and control gaps. We then trace how AI has shown up in the SOC: from rules and classic machine learning for detection to natural-language tools that summarize alerts and turn questions like “show failed logins from new countries in the last 24 hours” into fast database queries. The core of the talk is our next step: agentic investigations. These GenAI agents plan their work, run queries across tools, cite evidence, and draft analyst-grade findings—with guardrails and a human in the loop. We close with what’s next: risk-aware auto-remediation, verifiable knowledge sources, and a practical checklist for adopting these capabilities safely.

    // Bio

    Dr. Jeff Schwartzentruber holds the position of Sr. Machine Learning Scientist at eSentire – a Canadian cybersecurity company specializing in Managed Detection and Response (MDR). Dr. Schwartzentruber’s primary academic and industry research has been concentrated on solving problems at the intersection of cybersecurity and machine learning (ML). Over his +10-year career, Dr. Schwartzentruber has been involved in applying ML for threat detection and security analytics for several large Canadian financial institutions, public sector organizations (federal), and SME’s. In addition to his private sector work, Dr. Schwartzentruber is also an Adjunct Faculty at Dalhousie University in the Department of Computer Science, a Special Graduate Faculty member with the School of Computer Science at the University of Guelph, and a Sr. Advisor on AI at the Rogers Cyber Secure Catalysts.

    // Related Links

    Website: https://www.esentire.com/


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    Connect with Demetrios on LinkedIn: /dpbrinkm

    Connect with Jeff on LinkedIn: /jeff-schwartzentruber/



    Thousands of Fine-Tuned Models Nov 03, 2025
    Show notes

    Jaipal Singh Goud is the CTO at Prem AI, working on model customization and privacy-preserving compute.


    This episode was recorded at the Plan B studios in Lugano, Switzerland. For more information, visit https://pow.space/


    How do fine-tuned models and RAG systems power personalized AI agents that learn, collaborate, and transform enterprise workflows? What kind of technical challenges do we need to first examine before this becomes real?


    Demetrios Brinkmann - Founder of MLOps Community


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    The Semantic Layer and AI Agents // David Jayatillake // #343 Oct 24, 2025
    Show notes

    The Semantic Layer and AI Agents // MLOps Podcast #343 with David Jayatillake, VP of AI at Cube.dev.


    Join the Community:

    https://go.mlops.community/YTJoinIn

    Get the newsletter: https://go.mlops.community/YTNewsletter


    // Abstract

    David Jayatillake argues that the real battle in data isn’t about AI — it’s about who controls the semantics. In this episode, he calls out how proprietary BI tools quietly lock companies into their ecosystems, making data less open and less useful. David and Demetrios debate whether semantic layers should live in open-source hands and how AI agents might soon replace entire chunks of manual data engineering. From feature stores to LLM-driven analytics, this conversation challenges how we think about ownership, access, and the future of data workflows.


    // Bio

    Experienced and world-renowned data, technology, and AI leader. Expert in the application of LLMs to the semantic layer.


    Writes at davidsj.substack.com about data, leadership, architecture, venture capital, and artificial intelligence.


    Two-time co-founder in the data space. Founded Delphi Labs, which focused on applying LLMs to semantic layers to enable data democratization.


    Regular data conference, podcast, panel, and webinar speaker.


    // Related Links

    Website: davidsj.substack.com


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    Connect with Demetrios on LinkedIn: /dpbrinkm

    Connect with David on LinkedIn: /david-jayatillake/


    Building Claude Code: Origin, Story, Product Iterations, & What's Next // Siddharth Bidasaria // #342 Oct 21, 2025
    Show notes

    Building Claude Code: Origin, Story, Product Iterations, & What's Next // MLOps Podcast #342 with Siddharth Bidasaria, Member of Technical Staff at Anthropic.


    Join the Community:

    https://go.mlops.community/YTJoinIn

    Get the newsletter: https://go.mlops.community/YTNewsletter


    // Abstract

    Demetrios Brinkmann talks with Siddharth Bidasaria about Anthropic’s Claude code — how it was built, key features like file tools and Spotify control, and the team’s lean, user-focused approach. They explore testing, subagents, and the future of agentic coding, plus how users are pushing its limits.


    // BioSoftware engineer. Founding team of Claude Code. Ex-Robinhood and Rubrik.


    // Related Links

    Bio: https://sidb.io/

    Sid's Blog: https://sidb.io/posts/

    I Let An AI Play Pokémon! - Claude plays Pokémon Creator: https://youtu.be/nRHeGJwVP18

    How Data Platforms Affect ML & AI // Jake Watson // MLOps Podcast #207: https://youtu.be/xWApMuyct_4

    The Agent Landscape - Lessons Learned Putting Agents Into Production: https://youtu.be/lRGldru7ohU


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]

    Connect with Demetrios on LinkedIn: /dpbrinkm

    Connect with Marco on LinkedIn: /siddharthbidasaria/


    Timestamps:

    [00:00] MCP servers usage creativity

    [00:34] Claude's code origin story

    [05:17] R&D freedom and tools

    [09:08] Model potential discovery

    [12:06] Model adaptation strategies

    [19:13] Steerability vs pattern alignment

    [22:09] Features to delete

    [24:12] Moore's law in LLMs

    [32:42] Power user surprises

    [35:56] Sub-agent evolution insights

    [39:54] Agent communication governance

    [45:26] At-scale agent coordination

    [49:56] Wrap up


    Building an Agentic AI Memory Framework Oct 14, 2025
    Show notes

    What if AI could actually remember like humans do?


    Biswaroop Bhattacharjee joins Demetrios Brinkmann to challenge how we think about memory in AI. From building Cortex—a system inspired by human cognition—to exploring whether AI should forget, this conversation questions the limits of agentic memory and how far we should go in mimicking the mind.


    Guest speaker: Biswaroop Bhattacharjee - Senior ML Engineer at Prem AI


    Host :Demetrios Brinkmann - Founder of MLOps Community


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    #podcast #aiinfrastructure #aiagents #memory


    LLMs at Scale: Infrastructure That Keeps AI Safe, Smart & Affordable // Marco Palladino// # 341 Oct 07, 2025
    Show notes

    LLMs at Scale: Infrastructure That Keeps AI Safe, Smart & Affordable // MLOps Podcast #341 with Marco Palladino, Kong's Co-Founder and CTO.


    Join the Community: https://go.mlops.community/YTJoinIn

    Get the newsletter: https://go.mlops.community/YTNewsletter


    // Abstract

    While conversations around AI regulations continue to evolve, the responsibility for AI continues to be with developers. In this episode, Marco Palladino, CTO and co-founder of Kong Inc., explores what it means to build and scale AI responsibly when the rulebook is still being written. He explains that infrastructure should be the frontline defense for enforcing governance, security, and reliability in AI deployments. Marco shares how Kong’s technologies, including AI Gateway and AI Manager, help organizations rein in shadow AI, reduce LLM hallucinations, improve observability, and act as the foundation for agentic workflows.


    // Bio

    Marco Palladino is an inventor, software developer, and internet entrepreneur. As the CTO and co-founder of Kong, he is Kong’s co-author, responsible for the design and delivery of the company’s products, while also providing technical thought leadership around APIs and microservices within both Kong and the external software community. Prior to Kong, Marco co-founded Mashape in 2010, which became the largest API marketplace and was acquired by RapidAPI in 2017.


    // Related Links

    Website: https://konghq.com/ https://www.youtube.com/watch?v=odpPVeQZjHU https://www.thestack.technology/the-big-interview-kong-cto-marco-palladino/


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    Connect with Demetrios on LinkedIn: /dpbrinkm

    Connect with Marco on LinkedIn: /marcopalladino/


    Timestamps:

    [00:00] Agent-mediated interactions shift

    [01:17] Kong connectivity and agents

    [04:36] Transcript cleanup request

    [08:11] MCP server use cases

    [12:37] Agent world possibilities

    [15:55] Business communication evolution

    [18:55] System optimization

    [25:36] AI gateway patterns

    [31:30] Investment decision making

    [35:54] Building conviction process

    [41:34] Polished customer conversation

    [46:37] AI gateway R&D future

    [50:52] Wrap up


    Best AI Hackathon Project Ever? [Bite Size Episode] Oct 03, 2025
    Show notes

    AI Conversations Powered by Prosus Group


    Unicorn Mafia won the recent hackathon at Raise Summit and explained to me what they built, including all the tech they used under the hood to make their AI agents work.


    Winners:

    Charlie Cheesman - Co-founder at 60x.ai

    Marissa Liu - Tech Lead, Reporting at Watershed

    Ana Shevchenko - Software Engineer II at Spotify

    Fergus McKenzie-Wilson - Co-founder at 60x.ai

    Alex Choi - Founding Engineer at Medfin


    Host:

    Demetrios Brinkmann - Founder of MLOps Community


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    On-Device AI Agents in Production: Privacy, Performance, and Scale // Varun Khare & Neeraj Poddar // #340 Sep 30, 2025
    Show notes

    On-Device AI Agents in Production: Privacy, Performance, and Scale // MLOps Podcast #340 with NimbleEdge's Varun Khare, Founder/CEO and Neeraj Poddar, Co-founder & CTO.


    Join the Community:

    https://go.mlops.community/YTJoinIn

    Get the newsletter: https://go.mlops.community/YTNewsletter


    // Abstract

    AI agents are transitioning from experimental stages to performing real work in production; however, they have largely been limited to backend task automation. A critical frontier in this evolution is the on-device AI agent, enabling sophisticated, AI-native experiences directly on mobile and embedded devices. While cloud-based AI faces challenges like constant connectivity demands, increased latency, privacy risks, and high operational costs, on-device breaks through these trade-offs.


    We'll delve into the practical side of building and deploying AI agents with “DeliteAI”, an open-source on-device AI agentic framework. We'll explore how lightweight Python runtimes facilitate the seamless orchestration of end-to-end workflows directly on devices, allowing AI/ML teams to define data preprocessing, feature computation, model execution, and post-processing logic independently of frontend code. This architecture empowers agents to adapt to varying tasks and user contexts through an ecosystem of tools natively supported on Android/iOS platforms, handling all the permissions, model lifecycles, and many more.


    // Bio

    Varun Khare

    Varun is the Founder and CEO of NimbleEdge, an AI startup pioneering privacy-first, on-device intelligence. With an academic foundation in AI and neuroscience from UC Berkeley, MPI Frankfurt, and IIT Kanpur, Varun brings deep expertise at the intersection of technology and science. Before founding NimbleEdge, Varun led open-source projects at OpenMined, focusing on privacy-aware AI, and published research in computer vision.


    Neeraj Poddar

    Neeraj Poddar is the Co-founder and CTO at NimbleEdge. Prior to NimbleEdge, he was the Co-founder of Aspen Mesh, VP of Engineering at Solo.io, and led the Istio open source community. He has worked on various aspects of AI, networking, security, and distributed systems over the span of his career. Neeraj focuses on the application of open source technologies across different industries in terms of scalability and security. When not working on AI, you can find him playing racquetball and gaining back the calories spent playing by trying out new restaurants.


    // Related Links

    Website: https://www.nimbleedge.com/

    https://www.nimbleedge.com/blog/why-ai-is-not-working-for-you

    https://www.nimbleedge.com/blog/state-of-on-device-ai

    https://www.youtube.com/watch?v=Qqj_Nl2MihE

    https://www.linkedin.com/events/7343237917982527488/comments/


    ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

    Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

    Join our Slack community [https://go.mlops.community/slack]

    Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

    Sign up for the next meetup: [https://go.mlops.community/register]

    MLOps Swag/Merch: [https://shop.mlops.community/]


    Connect with Demetrios on LinkedIn: /dpbrinkm

    Connect with Varun on LinkedIn: /vkkhare/

    Connect with Neeraj on LinkedIn: /nrjpoddar/


    Timestamps:

    [00:00] On-device AI skepticism

    [02:47] Word suggestion for AI

    [06:40] Optimizing unique challenges

    [13:39] LLM on-device challenges

    [20:34] Agent overlord tension

    [23:56] AI app constraints

    [29:23] Siri limitations and trust gap

    [32:01] Voice-driven app privacy

    [35:49] Platform lock-in vs aggregation

    [42:26] On-device AI optimizations

    [45:38] Wrap up


    Previous 1 7 8 9 10 11 56 Next

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