AI
Artificial intelligence, machine learning, and everything LLM
#2028: Agent Skills Are the New Apps
AI agents are getting an App Store for brains. Discover how modular skills are replacing massive prompts and what it means for the future of work.
#2027: Text-In, Text-Out: The Missing Photoshop for Words
Why is editing text with AI so clunky? We explore the "TITO" paradigm—using small, local models for fast, private text transformation.
#2026: Prompt Layering: Beyond the Monolithic Prompt
Stop writing giant, monolithic prompts. Learn how to stack modular layers for cleaner, more powerful AI applications.
#2025: How Do You Reward a Thought?
Rewarding an AI agent is harder than just saying "good job"—here's how we turn messy human values into math.
#2024: Your AI Council: Digital Committee or Groupthink?
A digital boardroom of AI models promises better decisions, but risks amplifying the same old biases.
#2022: OpenClaw: The 16 Trillion Token Autonomy Engine
We dug into a repo of 47 real-world projects showing how OpenClaw powers everything from self-healing servers to overnight app builders.
#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: When They're Worth It
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: 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?