Episodes
1954 episodes · Page 1 of 98
#2021: Your Frozen AI Is Getting Smarter (Here's How)
Your AI model might be static, but the system around it can make it learn in real-time.
#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.
#2018: Micro Frontends: Luxury Tax or Lifesaver?
The frontend monolith is a nightmare of coordination. Micro frontends promise autonomy, but is the operational complexity worth the cost?
#2017: That Q4_K_M Is Not a Cat Sneeze
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: AI's Watchdogs: Who's Actually Regulating Tech?
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: The Ephemeral Context Trap: AI Chats Lost to the Void
We're brilliant at prompting AI, but terrible at saving the answers. Here's why that "digital masterpiece on a chalkboard" vanishes.
#2010: AI's Great Data Lobotomy: Fixing the Memory Leak
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: Why Your AI Genius Can't Find the Needle
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: Why Your GPU Changes LLM Output
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: Home Assistant's Stability Problem and Its Future
We explore why Home Assistant is so fragile and brainstorm a stable-by-design future for the platform.