Sport

Master Your Race Week: 7-Day Taper and Nutrition Tips

The Science

This 7-day pre-race plan exists for one simple reason:
to get you to the start line slightly bored, mildly twitchy, and annoyingly fresh –> That’s the “sweet spot”.

It’s built on two ideas that sports science actually agrees on (a rare event):
tapering and nutrition periodization.
No crystals.
No miracle powders.
Just physiology doing its thing if you don’t mess with it.

Training Taper: Doing Less Is a Skill

Tapering is the controlled art of not ruining months of work in the final week.

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Business, life

Charlie Munger’s Lessons on Human Judgment

Charlie Munger spent nearly a century studying how humans outsmart… themselves. The man treated bad decisions the way a forensic detective treats fingerprints. And the funny part? Most of the traps he identified hit smart people harder than everyone else. Intelligence doesn’t protect you—it just lets you come up with more elegant ways to be wrong.

Here’s the Munger playbook, rewritten in plain English and spiced with some real-world bruises. Ahh… it’s also much shorter then the original work. However, you do with to read the original as he is much better writer.

Let’s start with the elephant Munger kept in the room: brains aren’t the bottleneck—judgment is. You can have a rocket scientist mind and still steer straight into a mountain if you use it wrong.

1. Using One Mental Model Is Like Using One Dumbbell

When someone only uses the tools from their field, they distort reality to fit their toolbox.

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AI, Chrome, webdev

Transforming Recipe Chaos with SeasonApp

Some projects start with ambition.

This one started with annoyance.

I was tired of juggling recipes across bookmarks, screenshots, messages, and the occasional scribble in a notes app.
A normal person would’ve organized things.
I opened Cursor.

The plan was simple: a quick weekend hack.
Nothing serious. Just a tiny tool to help me stop losing recipes.

But then it worked. And I liked using it.
Then I showed it to a couple of friends.
Then my family started using it.
Then those friends shared it with their friends.

That’s when the “weekend hack” quietly transformed into SeasonApp—a small but mighty full-stack platform for cooking, powered by AI and built to remove friction from the kitchen.


Why SeasonApp Exists

If you cook regularly, your digital life eventually turns into a disorganized pantry. Tabs everywhere. Screenshots mixed with flight confirmations. Recipe blogs where you scroll past a childhood memoir before finding the ingredient list. And once you finally want to cook something, you can’t find the right recipe—or you’re missing one ingredient and the whole plan collapses.

SeasonApp brings order to that chaos.

It gives recipes a home.
It helps you create new ones.
And it actually understands what you want to do with whatever’s in your fridge.

The more people around me used it, the more obvious the need felt.
Everyone had the same pain; they just tolerated it.
SeasonApp gives them a better way.

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Business

Protect Your Digital Life: 3 Key Security Habits

We imagine hackers as trench-coat wizards hammering keyboards while green code rains down the screen.
Reality is less Matrix and more lazy cat burglar.

They don’t “hack in.”

They log in, using the same password you used for LinkedIn in 2014 and also for your Gmail, bank, gym, YMCA portal, and that meditation app you opened (only) once.

Let’s fix that.
It’s not hard but it’s important.

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AI

Gemini 3: Your New AI Coding Assistant

Every developer has that moment where they stare at the screen and wish for a magic wand.
Something that can unscramble a legacy codebase, sketch a UI without endless Figma tabs, or summarize a 300-page API doc that reads like… and create some good tests out of nothing.

Google just dropped something dangerously close.

Gemini 3 isn’t another “slightly better benchmark” release. It’s a real step forward—especially for people who build things for a living.

Here’s where it gets interesting:

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AI, webdev

8 Top Tips to Actually Use Cursor (Without Setting Your Wallet on Fire)

TL;DR

Open a new agent/chat for each new request or task, instead of continuing everything in one long conversation.

Keeping unrelated work in a single long chat makes the agent less efficient, increases context noise, and also becomes more expensive because the full conversation history keeps getting processed.

Best practice:

  • One request / task = one new agent
  • Keep chats focused on a single issue or feature
  • Start a fresh chat when switching topics
  • If you can –> Combine Cursor with Ollama + local models

If you’ve been coding anytime in the past year, you’ve probably heard the buzz about Cursor — the AI-powered IDE that promises to write your code, clean your code, and maybe even refactor your soul.

It’s built on top of VS Code, so it feels instantly familiar.
But the moment you hit that shiny AI shortcut, you realize: this thing is smarter than your codebase and hungrier than your wallet.

After a few months of using Cursor — and after accidentally vaporizing a scandalous number of API tokens — I’ve learned how to stay productive and solvent.


And yes, the TL;DR is that you can still combine Cursor with Ollama + local models to get many of these benefits for free.
Here are my 8 hard-earned tips to make Cursor your loyal sidekick within the limits of your budget.

The #1 tip: Control context scope aggressively – This is the biggest win

Cursor auto-includes files, diffs, and history—this explodes token usage.

Do this:

  • Manually select only the exact files/functions needed
  • Avoid “entire repo” context unless absolutely required
  • Use @file and @selection instead of implicit context
  • Clear chat or start a new thread when switching tasks

Why it matters:
Token cost scales with every line in context, not just your prompt.

Below are a bit more tips:

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AI

Transform Your Coding with Gemini CLI: A Local AI Assistant

Every developer has a moment mid-flow when they break concentration to look up a flag, debug an error, or Google that one awk trick they always forget. It’s death by context switching — and the browser is the grim reaper.

That’s where Gemini CLI comes in.

It’s not just another AI chatbot ported into a terminal.
It’s an embedded, context-aware development assistant that lives alongside your code, speaks your language, and remembers what you’ve worked on — locally.
No browser tabs, no copy-paste gymnastics, no handing your project to the cloud gods.

When choosing an AI coding assistant, developers have several strong options to consider.
Claude Code offers sophisticated reasoning and natural language understanding, excelling at complex problem-solving and architectural decisions through its command-line interface.
OpenAI Codex, which powers GitHub Copilot, integrates seamlessly into popular IDEs and has been widely adopted for its reliable code completion and suggestion capabilities.

Google’s Gemini stands out with its multimodal capabilities and strong performance across various coding tasks, while offering a particularly appealing advantage for developers just getting started: it’s available for free.

This makes Gemini an excellent entry point for newcomers who want to explore AI-assisted development without any initial investment, allowing them to experiment and learn before committing to paid tools as their needs grow.

Let’s unpack how Gemini CLI changes the game for developers, how to use it effectively, and where it still falls short.

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Chrome, JavaScript, webdev

Building a Real-Time Pull-Up Tracker: How I Taught The Browser to Count Our Pain

It started as a simple idea my son brought up: Can we make a web app that counts our pull-ups during our pull-up games?

Turns out, teaching a machine to recognize human suffering is both hilarious and complicated.
What began as a “let’s make a quick pull-ups app” spiraled into an intense journey through computer vision, browser quirks, and a few accidental infinite loops that made our laptop sound like a jet engine.

The “Simple” Goal

I wanted to automatically count pull-ups using a web camera.

Easy, right?

Just detect a human, see when they go up and down, and count.

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Business, life

Nine Mental Models to Stop You from Making Dumb Decisions

We all think we’re rational.

We’re not.

Most of the time, most of the people are just apes with phones making pattern-matching errors at scale. If you aren’t sure, just look around.

Shane Parrish’s The Great Mental Models, is a antidote — a toolkit for thinking clearly and making fewer stupid decisions. Hopefully.

Btw, I wrote about it in the past as I ‘took’ ideas from the great Charlie Munger:

Below are nine models I keep coming back to, rephrased for the real world (and with fewer academic eyebrows raised).

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