Developers May Stop Depending on Libraries

Developers May Stop Depending on Libraries

Author: Demetrios July 6, 2026 Duration: 46:52

In this episode of Agentic Conversations, we're joined by Shaun Smith, software engineer, open source advocate, and contributor at Hugging Face, to explore how AI coding has changed almost overnight.


We dive into reinforcement learning, MCP (Model Context Protocol), Fast Agent, Claude Code, open source AI, and why today's language models have become so capable that many traditional software libraries are becoming "liquefied." Shaun explains how reinforcement learning unlocked long-running autonomous agents, why ideas are becoming more valuable than code, and how developers should think about building software in an era where AI can generate entire applications.


Along the way, we discuss Hugging Face's MCP server, Fast Agent, AI-powered developer tools, multimodal applications, MCP Apps, context windows, coding assistants, Rust, Python, TypeScript, open-weight models, software architecture, and what the future of programming looks like when humans increasingly focus on design instead of implementation.


Shaun Smith: https://www.linkedin.com/in/smithshaun

Demetrios: https://www.linkedin.com/in/dpbrinkm


Hugging Face: https://huggingface.co


⏱️ Timestamps[00:00] Introduction

[01:56] The State of Open Source AI

[05:18] Reinforcement Learning Changed Everything

[07:50] Fast Agent Explained

[10:18] Fast Agent as an MCP Reference Platform

[12:20] Building Smarter AI Tools at Hugging Face

[15:17] Natural Language Search Instead of APIs

[17:46] Why MCP Apps Matter

[20:06] The Evolution of MCP Apps

[23:05] Building AI-Native User Interfaces

[26:12] Context Is the New Programming Language

[28:00] The End of Code Libraries

[29:50] Why Developers Aren't Writing Code

[31:25] AI Changes Software Engineering

[33:05] The Future of Open Source AI

[35:43] Claude Skills That Save Hours

[38:02] Training Models with AI

[39:05] Building Your Own AI Tools

[40:50] MCP for Consumers, Enterprises, and Developers

[43:42] Why Shell Access Makes Agents Smarter

[45:18] Secure Agent Workflows

[46:08] The Future of AI Interfaces

[47:02] Outro

#HuggingFace #MCP #OpenSourceAI


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
Author: Language: en-us Episodes: 50

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