Model Context Protocol
211 episodes · Page 7 of 9
#1846: Right-Sizing Your Agent's MCP Toolkit
AI agents slow down when overloaded with tool schemas. Just-in-time usage is the fix.
#1843: Why Is My AI Pipeline Stuck? (Kanban-Style Observability)
Stop digging through JSON logs. See your AI jobs moving on a board, not just server metrics.
#1840: Your Calendar Is Now a Negotiation
AI agents are now negotiating meetings behind the scenes using JSON schemas and zero-knowledge proofs.
#1834: Owning Your AI Memory: The Data Exit Strategy
Why your AI remembers your coffee order but forgets your son’s name—and how to build a portable, federated memory layer you actually own.
#1832: From Local Chaos to Cloud Control
Local MCP servers are a configuration nightmare. Cloud aggregators like Composio offer a unified control plane for AI tools.
#1812: When AI Gets a Truth Tether to the Talmud
Sefaria's new MCP server connects AI directly to 2,700 years of Jewish texts, transforming how scholars and curious learners study ancient literature.
#1804: The Fork in the Road: Why AI Agents Check Old Receipts First
Stop your AI agent from overthinking. Learn why it checks old memories instead of booking flights—and how to fix the "eagerness" problem.
#1779: AI Memory Is a Mess: Files, Vectors, or Cloud?
Why your AI forgets your instructions and what the battle over portable memory means for the future of agents.
#1767: From Eyeballs to Tokens: The Web's Agentic Shift
The web's new primary user isn't human—it's AI. See how JavaScript evolved to serve autonomous agents.
#1765: The Agentic Internet: A Clean Web for Machines
We explore the tools building a parallel, machine-readable web—from SearXNG to Tavily.
#1764: Your Repo as a Knowledge Base
How to give AI agents instant memory of your entire project—without cloud costs or complex infrastructure.
#1754: From Ollama to Agentic CLIs: The Rise of the AI Harness
Explore the evolution from local LLMs to modern agentic CLIs, focusing on the "harness" that gives models context, tools, and autonomy.
#1753: AI Makes Coding Harder, Not Easier
Claude Code writes the syntax, but you need more technical knowledge than ever to guide it.
#1732: Why AI Agents Need an Operating System
AIOS aims to be the Linux for AI agents, managing memory, scheduling, and tools in one open-source kernel.
#1730: Are Multi-Agent Coding Frameworks Obsolete?
MetaGPT, SWE-agent, and OpenHands promised a team of AI devs. But in 2026, are they still useful, or has raw model power made them obsolete?
#1727: The Great Architectural Heist: LSP as AI's Universal Plumbing
Explore how the Language Server Protocol is being repurposed to integrate AI directly into code editors, unifying development workflows.
#1725: The Death of the Lonely Chatbot
Forget chatbots: AI orchestration is now the key to scaling intelligent agents in the enterprise.
#1723: Why Agentic AI Needs a Hive Mind, Not a Single Brain
The single monolithic AI model is dying. Meet the new native multi-agent architectures that think like a team, not a solo genius.
#1711: Stop Building the Bucket: The Vendor SDK Era
We compare the three major vendor SDKs for building AI agents, weighing speed, safety, and scalability.
#1708: Why Your AI Agent Forgets Everything (And How to Fix It)
Learn how Letta's memory-first architecture solves the AI context bottleneck for long-term agents.
#1705: Microsoft's Phi: The Small Model Bet for Agentic AI
Microsoft is pushing small language models like Phi for agentic AI. Here’s why that strategy matters for speed, cost, and edge computing.
#1666: The Agent Mesh: Shared Context That Changes Everything
Grok 4.20’s native multi-agent architecture cuts token costs by 75% and enables real-time cross-agent reasoning.
#1652: AI Gateways: The Nginx for Your AI Stack
Why agentic AI needs a unified control plane to route models, aggregate tools, and cut costs.
#1649: The Vendor SDK Moat: Real or Illusion?
Is the vendor lock-in real, or just good marketing? We dissect the trade-offs between vendor SDKs and agnostic frameworks.