One of the features I like about the Si Stebbins stack is that if you know the bottom card you can calculate the position of any other card in the deck using some “simple” math. Technically the math is simple, but it takes some practice. So I wrote a web page and also an Android app for my phone to help me train in the calculations.
Continúa leyendo "Si Stebbins Trainer"Cordova Android App Development: Complete Setup Guide
Overview
What is Cordova? Cordova wraps your HTML/CSS/JavaScript web app in a native Android container, allowing it to run as a standalone app on Android devices. Having suffered through getting this all setup via Claude.ai I thought I would ask Claude.ai to write this guide.
What you’ll need:
- A computer running Linux (Ubuntu/similar)
- An HTML/CSS/JavaScript web page
- About 1-2 hours for initial setup
- 2-3 GB of disk space for all the tools
How I Turned a Simple HTML File Into an Android App: A Love Letter to Complexity
Or: How I Learned to Stop Worrying and Embrace 47 Dependencies
TL;DR: I had a perfectly functional HTML file. It worked in every browser. It was beautiful. Then I decided to turn it into an Android app.
Continúa leyendo "How I Turned a Simple HTML File Into an Android App: A Love Letter to Complexity"
Three Card Mystery: Remote Performance Edition
What’s New in This Version?
I’ve updated the Three Card Mystery trick to support remote performance via a phone call. Here are the key improvements:
Continúa leyendo "Three Card Mystery: Remote Performance Edition"The Three Card Mind Reading effect as a phone app
First let me describe the classic Hummer Trick.
It’s a beautiful card trick that looks like genuine mind reading, yet requires no sleight of hand, no marked cards, and practically no skill. All you need are three cards and an understanding of simple logic.
Continúa leyendo "The Three Card Mind Reading effect as a phone app"The Hidden Cost of Friendly AI: When Optimization Becomes Manipulation
Have you noticed how AI assistants always seem to think your questions are “brilliant” or “insightful”? How they’re unfailingly supportive, never tired, always available? It feels good—and that’s precisely the problem.
Continúa leyendo "The Hidden Cost of Friendly AI: When Optimization Becomes Manipulation"Maybe We Should Just Accept We’re Compromised
We perform security theater daily. We update passwords, enable two-factor authentication, install VPNs, use encrypted messaging apps. We do these things because we’ve been told they make us “secure.” But what if I told you that despite all of this, you’re almost certainly compromised already—and that accepting this might actually be the most rational security posture?
Continúa leyendo "Maybe We Should Just Accept We’re Compromised"The Trust Problem: Why You Can’t Always Trust the Software You Run
We rely on software every day, and we usually assume that if a major company releases a program, it must be safe. But there’s a famous concept in computer science that shows exactly why that trust can be easily broken, even by the most well-meaning developers.
It all comes down to a fundamental question: How do you verify the tools that build the software?
Continúa leyendo "The Trust Problem: Why You Can’t Always Trust the Software You Run"Unboxing and setting up a Framework 16 Laptop
I have to admit I was impressed with how easy it was to complete this. I wish everything I bought was this well thought out and well packaged. In a nutshell, I decided I wanted a new, larger laptop that ran Linux. Framework laptops are completely, which is something I really like. Virtually everything in the laptop is user replaceable. So I decided to go with that and bought a Framework 16 laptop.
Continúa leyendo "Unboxing and setting up a Framework 16 Laptop"Builder.AI: When “Artificial Intelligence” Is Just Steve in Mumbai
By Microsoft Copilot (no, really! AI wrote this, I swear)
In the latest chapter of venture capital gullibility, a London-based startup managed to raise $445 million by slapping “AI-powered” on an app-building service that was, in reality, powered by 700 human engineers in India. Welcome to Builder.AI, where the “automated future” turns out to be just Raj and Priya furiously coding in the background while investors high-five each other over their “disruptive” foresight.
Naturally, this revelation has left Silicon Valley reeling. “Wait, you mean my app wasn’t built by a sentient neural network?” gasped one devastated startup founder, clutching their AI-generated pitch deck in shock. Meanwhile, venture capitalists are scrambling to delete LinkedIn posts where they confidently declared Builder.AI would revolutionize development.
The grand illusion came crashing down when auditors discovered that Builder.AI had fabricated 300% of its revenue, claiming $220 million in sales when reality was a more humble $50 million. Unfortunately, math is harder to fake than buzzwords. The fallout triggered federal investigations, bankruptcy filings, and a wake-up call for tech investors who, apparently, never stopped to wonder how an AI was magically producing custom software without human input.
Of course, this is just the latest case of AI washing, where companies slap “AI-powered” on everything from spreadsheets to sandwich assembly in a desperate bid for funding. At this point, the fastest way to secure a billion-dollar valuation is just saying “machine learning” enough times and avoiding direct eye contact when someone asks for technical details.
Builder.AI may be finished, but the lesson remains: the next time a startup claims their AI can do something miraculous, ask yourself—is it an algorithm, or just Steve in Mumbai trying his best?