AI
Artificial intelligence, machine learning, and everything LLM
#2281: Startup Funding Decoded: Stages, Dilution, and Exit Realities
Unpacking how startup funding works, from seed to exit, and why most equity grants don’t deliver as expected.
#2278: Visual Programming's Enduring Tradeoff
Why do visual programming tools keep resurfacing—and why do power users keep hitting their limits?
#2276: A Guided Tour Through My Weird Prompts' Best Episodes
Discover ten standout episodes that define the essence of My Weird Prompts, from AI insights to quirky curiosities.
#2274: Weekend Projects Gone Wild: Evaluating AI Startup Pitches
From fridge tax agents to guilt-scheduled cron jobs, we evaluate ten AI-driven startup ideas that could exist—but probably shouldn’t.
#2271: Vector Search in a Single File
What if you could do vector search with just SQLite? We explore sqlite-vec, the extension that adds embeddings to the world's simplest database, an...
#2267: The 50-Year Reign of Nine-to-Five
The nine-to-five workday feels eternal, but its dominance as the default for office workers is a surprisingly brief historical blip. We trace its f...
#2262: Documentaries About Parking Lots and Drying Paint
A tour of the most baffling documentaries ever made, from a 10-hour film of paint drying to a feature-length portrait of a single parking lot.
#2261: The Gap Between AI Output and Art
We assess if AI can truly invent a Tolkien-level language, write a coherent novel, or author an original screenplay—and where the real gaps in crea...
#2260: The Papier-Mâché Crab and the Cult Film
How did a bizarre, technically disastrous 1972 Israeli film flop, vanish, and then become a beloved midnight movie phenomenon? We dissect the legen...
#2255: Typst vs. LaTeX: The AI-Ready Document Engine
Can Typst succeed LaTeX as the go-to tool for programmatic typesetting, especially for AI agents? We compare the two and explore what makes a docum...
#2254: How to Test an AI Pipeline Change
When you tweak one part of a complex AI agent system, how do you know if it actually improved anything? The answer lies in engineering checkpoints.
#2253: Why AI Agents Get Three Steps, Not Infinity
Why do AI agents get exactly three rounds of tool use? It's a critical guardrail against infinite loops and runaway costs, not a limit on intellige...
#2251: Agent-to-Agent Protocols: What Actually Needs Standardizing
When autonomous agents call other agents, what does a working protocol actually require? Exploring session handling, state management, security, an...
#2250: How Incentives Shape AI Safety Research
Vendor labs, independent research orgs, government agencies—the AI safety field is messier and more diverse than most people realize. A map of wher...
#2249: Building Custom Benchmarks for Agentic Systems
Public benchmarks fail for agentic systems. Learn how to build evaluation frameworks that actually predict production behavior.
#2246: Constitutional AI: Anthropic's Theory of Safe Scaling
How Anthropic's Constitutional AI replaces human raters with AI self-critique guided by explicit principles—and what it assumes about the future of...
#2243: What Enterprise AI Pricing Actually Negotiates
Enterprise customers rarely get the deep discounts they expect from AI APIs. What they actually negotiate for—and why the ramp-up requirement exist...
#2242: AI as Your Ideation Blind Spot Spotter
How to use AI not to answer questions you already know to ask, but to surface possibilities your expertise has made invisible to you.
#2241: When More Frameworks Make Worse Decisions
Benjamin Franklin's 250-year-old pro/con list still dominates how we decide—but research shows it's riddled with bias. We map five frameworks that ...
#2239: How AI Benchmarks Became Broken (And What's Replacing Them)
The tests we use to measure AI progress are contaminated, saturated, and gamed. Here's what's actually working.