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cover of episode A Candid Conversation Around MCP and A2A // Rahul Parundekar and Sam Partee // #316 SF Live

A Candid Conversation Around MCP and A2A // Rahul Parundekar and Sam Partee // #316 SF Live

2025/5/21
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AI Deep Dive AI Chapters Transcript
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Rahul Parundekar
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Sam Partee
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Sam Partee: 我认为Agent是一个能够将文本输入到确定性过程(通常是代码)并运行该过程的文本片段或大型语言模型。工具是任何代表性函数,只要大型语言模型的输出能够成为其输入。目前工具的执行主要由开发者负责,而MCP和Arcade等项目正试图解决这个问题。由于RAG,人们倾向于获取文本以增强过程,但在使用工具采取行动时会出现问题,因为服务器没有准备好代表个人行事。为了让Agent能够执行操作而非仅获取上下文,我们需要提升它们的权限。 Rahul Parundekar: 我认为工具使Agent能够访问其未记忆的信息,从而扩展了LLM的工作范围。LLM不完美且不确定,因此赋予它们过多的权限可能会导致意外后果。我们不应该给Agent所有权限,而是要有目的地赋予它们工作权限。应该为每个Agent分配不同的权限。

Deep Dive

Chapters
The conversation starts by defining AI agents and tools. An agent uses text input to feed a deterministic process (code) and run it as a tool. The current challenge is that the execution of these tools is left to developers, leading to inefficiencies and potential issues.
  • Agent: piece of text fed to a deterministic process (code)
  • Tool: function whose input is the output of a large language model
  • Challenge: execution of tools left to developers, not optimal

Shownotes Transcript

Demetrios, Sam Partee, and Rahul Parundekar unpack the chaos of AI agent tools and the evolving world of MCP (Model Context Protocol). With sharp insights and plenty of laughs, they dig into tool permissions, security quirks, agent memory, and the messy path to making agents actually useful.

// Bio

Sam Partee

Sam Partee is the CTO and Co-Founder of Arcade AI. Previously a Principal Engineer leading the Applied AI team at Redis, Sam led the effort in creating the ecosystem around Redis as a vector database. He is a contributor to multiple OSS projects including Langchain, DeterminedAI, LlamaIndex and Chapel amongst others. While at Cray/HPE he created the SmartSim AI framework which is now used at national labs around the country to integrate HPC simulations like climate models with AI.

Rahul Parundekar

Rahul Parundekar is the founder of AI Hero. He graduated with a Master's in Computer Science from USC Los Angeles in 2010, and embarked on a career focused on Artificial Intelligence. From 2010-2017, he worked as a Senior Researcher at Toyota ITC working on agent autonomy within vehicles. His journey continued as the Director of Data Science at FigureEight (later acquired by Appen), where he and his team developed an architecture supporting over 36 ML models and managing over a million predictions daily. Since 2021, he has been working on AI Hero, aiming to democratize AI access, while also consulting on LLMOps(Large Language Model Operations), and AI system scalability. Other than his full time role as a founder, he is also passionate about community engagement, and actively organizes MLOps events in SF, and contributes educational content on RAG and LLMOps at learn.mlops.community.

// Related Links

Websites:

arcade.dev

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Connect with Demetrios on LinkedIn: /dpbrinkm

Connect with Rahul on LinkedIn: /rparundekar

Connect with Sam on LinkedIn: /samparteeTimestamps:[00:00] Agents & Tools, Explained (Without Melting Your Brain)

[09:51] MVP Servers: Why Everything’s on Fire (and How to Fix It)

[13:18] Can We Actually Trust the Protocol?

[18:13] KYC, But Make It AI (and Less Painful)

[25:25] Web Automation Tests: The Bugs Strike Back

[28:18] MCP Dev: What Went Wrong (and What Saved Us)

[33:53] Social Login: One Button to Rule Them All

[39:33] What Even Is an AI-Native Developer?

[42:21] Betting Big on Smarter Models (High Risk, High Reward)

[51:40] Harrison’s Bold New Tactic (With Real-Life Magic Tricks)

[55:31] Async Task Handoffs: Herding Cats, But Digitally

[1:00:37] Getting AI to Actually Help Your Workflow

[1:03:53] The Infamous Varma System Error (And How We Dodge It)