Development
Building software: programming, developer tools, APIs, deployment and DevOps, and building with AI (agents, MCP servers, RAG, AI coding tools). An extra channel alongside an episode's main one, so AI engineering episodes sit in both.
#1736: The Hidden AI Economy: Following the Tokens
OpenClaw is processing 16.5 trillion tokens daily, dwarfing Wikipedia. Here’s why it’s #1.
#1735: The Agentic Stone Age: A Retrospective
We revisit the chaotic rise of BabyAGI and AutoGPT, exploring why their promise of total autonomy led to spectacular failure.
#1734: You vs. Your Digital Twin: Who Wins?
Your AI clone is getting scarily good. We explore the tech behind high-fidelity digital twins and the uncanny valley of your own voice.
#1733: When AI Agents Build Their Own Societies
AI agents are forming neighborhoods, economies, and hospitals in server-side simulations that mirror real human behavior.
#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.
#1731: Why Deep Research Agents Are Being Forgotten
Specialized research agents outperform general orchestrators by 40-60% on verification tasks, yet developer hype is fading. Here's why.
#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?
#1729: Why Is AI Code So Hard to Read?
AI writes code faster than ever, but the output is often a cryptic mess. We explore why and how to fix it.
#1728: The AI Carpool: Emergent Collaboration Through Role-Playing
CAMEL AI lets two agents role-play to solve tasks autonomously. No complex code—just emergent teamwork.
#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.
#1719: Why Pattern Matching Fails for PII at Scale
Regex alone is brittle; NER is expensive. See how hybrid frameworks like Presidio balance speed and accuracy to stop data leaks.
#1718: The Ralph Wiggum Technique: AI That Codes Itself
Stop babysitting AI agents. Learn the Ralph Wiggum technique to automate iterative coding loops and let AI finish the job itself.
#1717: The AI Framework Name Game
Why are there thousands of "AI frameworks" on GitHub? We unpack the naming mess and the cost of semantic inflation.
#1716: Seeing the AI Think: Visual Debugging for Agent Workflows
See how a visual, node-based tool lets you build complex AI agent workflows without writing code.
#1715: Why Voice Agents Need Frameworks (Not Just APIs)
Raw APIs handle models, but who manages the audio plumbing? We break down Vapi, LiveKit, and Pipecat.
#1714: The Hidden Cost of Rolling Your Own
Why do companies pour millions into SDKs? We explore the hidden costs of raw APIs and the strategic advantages of using software kits.
#1713: Why Native AI Search Grounding Still Fails
Native search grounding is expensive and flaky. Here’s why bolt-on tools still win for accurate, real-time AI answers.
#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.