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!
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// 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/
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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
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.
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// 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/
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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
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The Semantic Layer and AI Agents // MLOps Podcast #343 with David Jayatillake, VP of AI at Cube.dev.
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// 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
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Building Claude Code: Origin, Story, Product Iterations, & What's Next // MLOps Podcast #342 with Siddharth Bidasaria, Member of Technical Staff at Anthropic.
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// 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
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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
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
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#podcast #aiinfrastructure #aiagents #memory
LLMs at Scale: Infrastructure That Keeps AI Safe, Smart & Affordable // MLOps Podcast #341 with Marco Palladino, Kong's Co-Founder and CTO.
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// 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/
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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
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
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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.
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// 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/
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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
AI Conversations Powered by Prosus Group
Your AI agent isn’t failing because it’s dumb—it’s failing because you refuse to test it. Chiara Caratelli cuts through the hype to show why evaluations—not bigger models or fancier prompts—decide whether agents succeed in the real world. If you’re not stress-testing, simulating, and iterating on failures, you’re not building AI—you’re shipping experiments disguised as products.
Guest speaker: Chiara Caratelli - Data Scientist @ Prosus Group
Host: Demetrios Brinkmann - Founder of MLOps Community
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The DuckLake Lakehouse Format // MLOps Podcast #339 with Hannes Mühleisen, Co-founder and CEO of DuckDB Labs.
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// Abstract
Managing data on Object Stores has been a painful affair. Users had to choose between data swamp chaos or a maze of metadata files with catalog servers on top.
DuckLake is a new paradigm for managing data on object stores: First, it uses classical SQL data management systems to manage metadata. Second, actual data is stored in Parquet files on pretty arbitrary storage. Third, processing queries is done client-side, or anywhere really. DuckDB is the first system to integrate with DuckLake using an extension with the same name.
Conceptually, DuckLake enables central control over truth while decentralizing compute and storage entirely. DuckLake turns data warehouse architecture upside down by departing from the integrated metadata/compute layer towards a fully disconnected operation with only centralized metadata. For the first time, DuckLake allows a “multi-player” experience with DuckDB, where computation stays fully local, but transactional control is centralized.
// Bio
Hannes Mühleisen 🔈 is a creator of the DuckDB database management system and Co-founder and CEO of DuckDB Labs. He is a senior researcher at the Centrum Wiskunde & Informatica (CWI) in Amsterdam. He is also Professor of Data Engineering at Radboud University Nijmegen.
// Related Links
Website: https://hannes.muehleisen.orgUnleashing Unconstrained News Knowledge Graphs to Combat Misinformation // Robert Caulk // #279 - https://youtu.be/pF8zTI867EI
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Timestamps:[00:00] Spooky ease in tech[00:29] DuckDB and DuckLake[07:50] Pain vs trust factors[13:12] Prioritizing project features[16:16] Platform growth tension[22:06] Building principles[25:26] OSS vs system reliability[30:27] Creative uses of DuckDB[35:35] Tecton product strategy[43:30] Mindset shift[52:25] DuckDB future shifts[55:37] Wrap up
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Russ d'Sa shares how LiveKit went from a small open-source project during the pandemic to powering voice interfaces for giants like OpenAI. He talks about the turning point when LiveKit teamed up on ChatGPT’s voice features, the challenges of making AI sound human, and why voice could be the future of multimodal AI. It’s a story of chance, big shifts, and building the backbone of tomorrow’s AI.
Guest speakers: Russ Dsa - CEO of LiveKit
Host: Demetrios Brinkmann - Founder of MLOps Community
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#voiceagents #podcast
AI Conversations Powered by Prosus Group.
Craig Tavares, COO of Buzz High Performance Compute, shares lessons from building GPU cloud infrastructure worldwide. He stresses the role of sovereign mandates, renewable power, and modular cooling in scaling data centers, while highlighting NVIDIA partnerships and orchestration as key to sustaining AI workloads.
Guest speaker: Craig Tavares - COO of Buzz HPC
Host: Demetrios Brinkmann - Founder of MLOps Community
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Trust at Scale: Security and Governance for Open Source Models // MLOps Podcast #338 with Hudson Buzby, Solutions Architect at JFrog.
Appreciate JFrog for their support in bringing this blog to life.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractFor better or for worse, machine learning has traditionally escaped the gaze of security and infrastructure teams, operating outside traditional DevOps practices and not always adhering to organizations development or security standards. With the introduction of open source catalogs like HuggingFace and Ollama, a new standard has been established for locating, identifying, and deploying machine learning and AI models. But with this new standard comes a plethora of security, governance, and legal challenges that organizations need to address before they can comfortably allow developers to freely build and deploy ML/AI applications. In this conversation will discuss ways that enterprise scale organizations are addressing these challenges to safely and securely build these development environments. // BioHudson Buzby is a solution engineer with an emphasis on MLOps, LLMOps, Big Data, and Distributed Systems, leveraging his expertise to help organizations optimize their machine learning operations and large language model deployments. His role involves providing technical solutions and guidance to enhance the efficiency and effectiveness of AI-driven projects.// Related Linkshttps://www.youtube.com/channel/UCh2hNg76zo3d1qQqTWIQxDg~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin 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: /dpbrinkmConnect with Hudson on LinkedIn: /hudson-buzby/
AI Conversations Powered by Prosus Group
Nishikant Dhanuka talks about what it really takes to make AI agents useful—especially in e-commerce and productivity. From making them smarter with context (like user history and real-time data) to mixing chat and UI for smoother interactions, he breaks down what’s working and what’s not. He also shares why evals matter, how to test with real users, and why AI only succeeds when it actually makes life easier, not more complicated.
Guest speaker: Nishikant Dhanuka - Senior Director of AI at Prosus Group
Host: Demetrios Brinkmann - Founder of MLOps Community
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#contextengineering #aiengineer #aiinfrastructure #podcast
The Era of AI Agents in Marketing // MLOps Podcast #337 with Joel Horwitz, Growth Engineer at Neoteric3D.
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// Abstract
We’re entering a new era in marketing—one powered by AI agents, not just analysts. The rise of tools like Clay, Karrot.ai, 6sense, and Mutiny is reshaping how go-to-market (GTM) teams operate, making room for a new kind of operator: the GTM engineer. This hybrid role blends technical fluency with growth strategy, leveraging APIs, automation, and AI to orchestrate hyper-personalized, scalable campaigns. No longer just marketers, today’s GTM teams are builders—connecting data, deploying agents, and fine-tuning workflows in real time to meet buyers where they are. This shift isn’t just evolution—it’s a replatforming of the entire GTM function.
// Bio
Joel S. Horwitz has been riding the data wave since before it was cool—literally. He spoke at Spark Summit back in 2014 and penned a prescient piece for MIT Tech Review on data science and machine learning before they became boardroom buzzwords. A former big tech executive turned entrepreneur, Joel now runs Neoteric3D (N3D for short), a digital design and data growth agency that helps brands scale with smarts and style. When he’s not architecting next-gen growth strategies, you’ll find him logging long miles on the trail or coaching his sons’ soccer and baseball teams like a champ.
// Related Links
Website: https://www.neoteric3d.com
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Connect with Demetrios on LinkedIn: /dpbrinkm
Connect with Joel on LinkedIn: /joelshorwitz
Timestamps:
[00:00] Joel's preferred coffee
[00:53] Agentic workflows in marketing
[04:26] Agentic AI vs big data
[08:24] Creative outreach automation
[13:08] LLMs in marketing optimization
[17:36] Traffic relevance
[23:36] End-to-end AI workflow
[28:10] AI in task automation
[32:08] AI systems architecting
[38:00] AI vs Thought Leadership
[43:10] AI as sparring partner
[45:22] AI shifts human roles
[48:23] Wrap up
Distilling 200+ Hours of NeurIPS: What’s Next for AI // MLOps Podcast #336 with Nikolaos Vasiloglou, VP of Research ML at RelationalAI.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractNikolaos widely shared analysis on LinkedIn highlighted key insights across agentic AI, scaling laws, LLM development, and more. Now, he’s exploring how AI itself might be trained to automate this process in the future, offering a glimpse into how researchers could harness LLMs to synthesize conferences like NeurIPS in real-time.// BioNikolaos Vasiloglou is VP of Research-ML for RelationalAI, the industry's first knowledge graph coprocessor for the data cloud. Nikolaos has over 20 years of experience implementing high-value machine learning and AI solutions across various industries. // Related LinksWebsite: https://relational.ai/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin 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: /dpbrinkmConnect with Nikolaos on LinkedIn: /vasiloglou/
AI Conversations Powered by Prosus Group Demetrios chats with Beyang Liu about Sourcegraph’s AMP, exploring how AI coding agents are reshaping development—from IDEs to natural language commands—boosting productivity, cutting costs, and redefining how developers work with code.Guest speakers:Beyang Liu - CTO of SourcegraphHost:Demetrios Brinkmann - Founder of MLOps Community~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin 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/]
AI Conversations Powered by Prosus Group Stack Overflow is adapting to the AI era by licensing its trusted Q&A corpus, expanding into discussions and enterprise tools, and reinforcing its role as a reliable source as developer trust in AI output declines.Guest speaker:Prashanth Chandrashekar - CEO of Stack OverflowHost:Demetrios Brinkmann - Founder of MLOps Community2025 Developer Survey: https://survey.stackoverflow.co/2025?utm_medium=referral&utm_source=direct-share&utm_campaign=dev-survey-2025&utm_content=MLOps~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin 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/]
Knowledge is Eventually Consistent // MLOps Podcast #335 with Devin Stein, CEO of Dosu.
Grateful to @Databricks and @hyperbolic-labs for supporting our podcast and helping us keep great conversations going.
Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter
// Abstract
AI as a partner in building richer, more accessible written knowledge—so communities and teams can thrive, endure, and expand their reach.
// Bio
Devin is the CEO and Founder of Dosu. Prior to Dosu, Devin was an early engineer and leader at various startups. Outside of work, he is an active open source contributor and maintainer.
// Related Links
Website: https://github.com/devstein
https://www.youtube.com/watch?v=sC8aW47DqPg
https://www.youtube.com/watch?v=PuM0Gd3txfQ
https://www.youtube.com/watch?v=ah6diDQ9wyw
https://www.youtube.com/watch?v=x22FEQic8lg
~~~~~~~~ ✌️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 Devin on LinkedIn: /devstein/
Timestamps:
[00:00] Devin's preferred coffee
[00:53] Facts agent overview
[03:47] Decision state detection
[07:55 - 8:41] Databricks ad
[08:42] Context-dependent word meanings
[15:25] Fact lifecycle management
[24:40] Maintaining quality documentation
[30:10 - 31:06] Hyperbolic ad
[31:07] Agent collaboration scenarios
[38:22] Knowledge maintenance
[44:10] Deployment and integration strategies
[48:13] Flywheel data approach
[51:54] Horror story engineering function
[54:32] Wrap up