AI
Artificial intelligence, machine learning, and everything LLM
#1961: Weaponizing Your Weirdness in an AI World
As AI homogenizes the web, contrarian thinking becomes a scarce asset. Here’s how to weaponize your weirdness for a competitive edge.
#1959: How Constrained AI Models Handle the Unexpected
Your AI assistant promised to only use your documents. Instead, it invented a case law that doesn't exist. Here's why.
#1957: Why AI Agents Think in Circles, Not Lines
Linear AI pipelines are brittle. Learn why loops, reflection, and state management are the new standard for reliable, autonomous agents.
#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.
#1952: Why We Built a 24/7 AI Radio Station
We turned our 1800-episode archive into a continuous AI-powered radio stream. Here’s the tech stack and the philosophy behind it.
#1951: Moltbook: A Social Network for AI Agents
Explore Moltbook, a social network where AI agents interact with persistent identities and goals, reshaping digital communication.
#1947: The AI Tool Flood: How to Find What Works
With 47 new AI video tools launching in a week, finding the right one is harder than using it.
#1946: LangGraph's 3-Layer Agent Stack Explained
We unpack LangGraph, LangChain, and Deep Agents to reveal the deliberate hierarchy behind the ecosystem.
#1945: The "USB-C for AI" Is Finally Here
MCP standardizes how AI tools connect to data, solving the N-times-M integration nightmare.
#1943: Why Tar Isn't Compression (And What Is)
LZMA, Zstandard, and Brotli are shrinking massive AI models, but how do they actually work?
#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.
#1940: Why Google's 31B Model Fits in Your GPU
Google just dropped Gemma four, and its 31-billion-parameter size is a masterclass in hardware-aware AI design.
#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.
#1938: JSON-to-SQL Type Mapping: A Practical Guide
Mapping JSON to SQL isn't as simple as it looks. Discover the hidden traps in data types that can cause performance hits and data corruption.
#1936: The Big Five FX Pairs: Personalities and Plumbing
We break down the world's most liquid currency pairs, from the Euro-Dollar heavyweight to the Swiss Franc safe-haven.
#1932: How Do You QA a Probabilistic System?
LLMs break traditional testing. Here’s the 3-pillar toolkit teams use to catch hallucinations and garbage outputs at scale.
#1931: AI Pipelines: In-Memory vs. Durable State
Why do AI pipelines crash? It’s not the models—it’s the plumbing. We break down how to manage data between stages.
#1930: The Agent Identity Crisis: Workflow vs. Conversation
One automates invoices silently; the other chats in Slack. Why the industry's favorite word means two totally different things.
#1929: Tracking AI Model Quality Over Time
We stopped "vibe-checking" our AI scripts and built a science fair for models. Here's how we grade them.
#1928: Why Webhook Gateways Beat Direct Wiring
Unscale your chaos: Why Kong beats manual webhook sprawl for auth, routing, and latency.