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

AI Conversations Powered by Prosus Group 

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.

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// Abstract

For 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, we will discuss ways that enterprise-scale organizations are addressing these challenges to safely and securely build these development environments.

// Bio

Hudson 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 Links

https://www.youtube.com/channel/UCh2hNg76zo3d1qQqTWIQxDg

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Timestamps:

[00:00] Value of Centralized Gateway

[00:35] Point Break vs Big Lebowski

[01:47] AI adoption failure stats

[05:12] ML vs Generative AI

[12:04] LLM adoption in enterprise

[18:08] MLOps Community alternative

[23:43] AI governance challenges

[27:39] Organizational debt comparison

[31:41] AI tool sprawl

[35:59] MLOps to platform evolution

[40:56] MLOps then vs now

[49:48] Model trust and safety

[52:19] AI model effectiveness

[55:54] Product discovery process

[58:38] Wrap up