Artificial Intelligence
Episodes whose main subject is AI itself: building with, training, evaluating, or debating AI systems. AI used only as a tool for another topic goes to that topic.
#2020: 1,000 AI Agents Built a Religion in Minecraft
An experiment drops 1,000 autonomous agents into Minecraft, and they spontaneously invent religion, democracy, and taxes.
#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.
#2017: The Art of Squeezing AI Models onto Your GPU
Those cryptic letters on Hugging Face actually map how much brain power you trade for speed.
#2016: Andrej Karpathy: The Bob Ross of Deep Learning
Why the most influential AI mind prefers a blank text file to proprietary black boxes.
#2015: The Think Tanks Writing AI's Rulebook
As the EU AI Act takes hold, we spotlight the key think tanks shaping global AI policy, safety, and ethics.
#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.
#2011: Saving AI Knowledge Beyond the Chat Window
We're brilliant at prompting AI, but terrible at saving the answers. Here's why that "digital masterpiece on a chalkboard" vanishes.
#2010: Building Better AI Memory Systems
We obsess over AI inputs but treat outputs like Snapchat messages. Here's why that's a massive blind spot.
#2009: The Plumbing of AI Safety: Guardrails, Not Vibes
We dive deep into the specific libraries, proxy layers, and architectural decisions that keep an LLM from emptying a bank account.
#2008: Needle-in-a-Haystack Testing for LLMs
New AI models claim to be genius-level, but can they actually find a specific fact in a massive document?
#2007: AI Grading AI: The Snake Eating Its Tail
We asked an AI to write this script. Then we asked another AI to grade it. Here’s what happens when the judges have biases.
#2006: How Do You Measure an LLM's "Soul"?
Traditional benchmarks can't measure tone or empathy. Here's how to evaluate if an AI model truly "gets it right."
#2005: Beyond Vibes: The Hard Science of LLM Evaluation
Running the same LLM on different GPUs can produce different results. Here’s why that happens and how to test for it.
#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.
#2003: The Velocity Paradox: Why Faster Code Means Slower Ships
Agentic coding tools let you build features in minutes, but they also make it easy to build the wrong thing.
#2002: Brainstorming a Stable-by-Design Smart Home
We explore why Home Assistant is so fragile and brainstorm a stable-by-design future for the platform.
#1994: Why Can't AI Admit When It's Guessing?
Enterprise AI now auto-filters low-confidence claims, but do these self-reported scores actually mean anything?
#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.