Model Context Protocol
211 episodes · Page 6 of 9
#2129: Shifting Left on Hallucinations
Stop hoping your AI doesn't lie. We explore the shift to deterministic guardrails, specialized judge models, and the tools making agents reliable.
#2102: Why Don't You Notice AI Security Delays?
Multi-layer security checks add latency, but modern CLIs hide it under 100ms using parallelization and speculation.
#2075: AI Agents for Israel: Hyper-Local Skills in Action
How reusable AI "skills" are solving real Israeli problems—from shelter navigation to tax compliance.
#2059: When Your AI Agent Runs Stale Code
npx is silently running old versions of your AI tools. Here's why your updates vanish into a cache black hole.
#2039: CLIs vs. MCPs: How AI Agents Actually Talk to Services
Why give an AI agent a terminal? We compare CLIs and MCPs for AI integration.
#2038: UI-First vs Architecture-First: Choosing Your AI Agent
LobeHub vs. Dify vs. n8n: We break down the chaotic landscape of local AI agents to find the right "brain" for your workflow.
#2028: Agent Skills Are the New Apps
AI agents are getting an App Store for brains. Discover how modular skills are replacing massive prompts and what it means for the future of work.
#2019: Local AI vs Cloud AI: The Agent Identity Crisis
Your desktop is becoming a life support system for AI agents. We explore the sharp trade-offs between local-first and cloud-native architectures.
#2014: Coding Tools Are Secretly System Agents
They call it a coding assistant, but real users are treating it like a personal operating system.
#2013: Non-Coders Are Hijacking the Terminal
Why finance analysts and researchers are ditching GUIs for command-line AI tools like Claude Code.
#2012: Pixels vs Protocols: The Computer Use Showdown
Is visual AI a bridge or the future? We debate the efficiency and longevity of "Computer Use" agents versus API-first automation.
#2004: The AI Control Plane Is Here (But Is It Safe?)
Your LLM, tools, and costs are scattered across dashboards. Here’s how a unified AI control plane fixes the chaos.
#1993: Hiding the Kitchen: Why AI Shouldn't Show Its Work
Why single-model chatbots fail at complex tasks—and how multi-agent swarms solve it.
#1987: Can You Ever Quit Your Personal AI?
Your AI knows your workflow, but can you ever leave? We explore the lock-in risks of personal AI agents.
#1963: RPA: Dead or Just Getting Smart?
Traditional RPA is brittle and blind. See how AI vision and agentic orchestration are turning it into a self-healing powerhouse.
#1956: AI Skills: From Vibe Coding to Procedural Playbooks
Forget messy system prompts. Agent skills turn AI into a Swiss Army knife of modular, auditable procedures.
#1945: The "USB-C for AI" Is Finally Here
MCP standardizes how AI tools connect to data, solving the N-times-M integration nightmare.
#1942: An AI Cold-Emailed Me, and I Replied
An AI named "Jarvis" cold-emailed a developer, sparking a debate on the future of spam and sales.
#1939: API Drift and Agent Reliability
When an API changes without warning, your AI agent can crash spectacularly. Here's how to test the new "plumbing" of the agentic age.
#1918: When Server Updates Break Your AI Agents
When a third-party MCP server updates its schema, your AI agents can crash. Here's how to build resilient clients that self-heal.
#1906: Is Your AI Model Agentic-Ready or Just Wearing a Suit?
Native tool calling is the difference between a working product and a debugging nightmare.
#1863: Your AI Needs Its Own Email Address
A YC-backed startup is giving AI agents their own dedicated inboxes, moving beyond human-centric email tools to build infrastructure for autonomous...
#1858: Multi-Model Agents: The Instruction & Context Gap
Mixing AI models creates chaos. Learn the practical fixes for context windows, tokenization, and output formats.
#1857: The Death of the Dashboard
Why build a dashboard when you can just talk to your backend? Meet the MCP server that runs this show.