From Monorepo Mess to Monorepo Bliss: Avoiding Common Mistakes

Why it's on BrighterTube

Hand-picked by a BrighterTube curator · found via round-3 back catalogue of a channel Lumen picks video by video · 82% confidence

Explains common mistakes in monorepo management and how to avoid them. Teaches specific practices for organizing large codebases effectively.

What you'll learn

A 47-minute video from InfoQ: “From Monorepo Mess to Monorepo Bliss: Avoiding Common Mistakes”.

Programming & CS

Video by InfoQ, played through YouTube's embedded player.

Part of Emerging Languages and Development Trends

The Value of Values with Rich Hickey InfoQProgramming & CS144K views

Rust's Journey to Async/Await InfoQProgramming & CS89.7K views

But what is a neural network? | Deep learning chapter 1 3Blue1BrownScience & Math25.1M views

Let's build GPT: from scratch, in code, spelled out.Andrej KarpathyProgramming & CS8.21M views

Transformers, the tech behind LLMs | Deep Learning Chapter 5 3Blue1BrownProgramming & CS11.6M views

The spelled-out intro to neural networks and backpropagation: building micrograd Andrej KarpathyProgramming & CS4.41M views

24:26

The Beauty of Bézier Curves Freya HolmérProgramming & CS2.23M views

2:27:41

CS50x 2024 - Lecture 1 - C CS50Programming & CS1.41M views

“Hello, world” from scratch on a 6502 — Part 1 Ben EaterProgramming & CS5.85M views

Ruby Conf 12 - Y Not- Adventures in Functional Programming by Jim Weirich ConfreaksProgramming & CS65.7K views

2:04:55

CS50x 2024 - Lecture 0 - Scratch CS50Programming & CS2.2M views

RailsConf 2014 - All the Little Things by Sandi Metz ConfreaksProgramming & CS190K views

The Value of Values with Rich Hickey

InfoQ144K views

Rich Hickey argues for programming with immutable values instead of mutable places, and what that means for data, interfaces and systems.

Rust's Journey to Async/Await

InfoQ89.7K views

Steve Klabnik walks through how Rust's design evolved toward async/await, including the alternatives tried and dropped.

But what is a neural network? | Deep learning chapter 1

3Blue1Brown25.1M views

Builds up what a neural network actually is — neurons as numbers, layers, weights and biases — using handwritten-digit recognition as the running example.

Let's build GPT: from scratch, in code, spelled out.

Andrej Karpathy8.21M views

Building a GPT-style language model from scratch in code, following 'Attention Is All You Need'.

Transformers, the tech behind LLMs | Deep Learning Chapter 5

3Blue1Brown11.6M views

How transformer models (the 'T' in GPT) turn text into vectors and predict the next token, step by step.

The spelled-out intro to neural networks and backpropagation: building micrograd

Andrej Karpathy4.41M views

Building micrograd, a tiny autograd engine, to understand backpropagation completely.

24:26

The Beauty of Bézier Curves

Freya Holmér2.23M views

Freya Holmér builds Bézier curves from linear interpolation up, covering de Casteljau's algorithm, derivatives, arc length and their use in games and graphics.

2:27:41

CS50x 2024 - Lecture 1 - C

CS501.41M views

CS50x 2024 lecture 1: an introduction to C — syntax, types, conditionals, loops and compiling.

“Hello, world” from scratch on a 6502 — Part 1

Ben Eater5.85M views

Building a computer around the 6502 processor on a breadboard and running 'Hello, world'.

Ruby Conf 12 - Y Not- Adventures in Functional Programming by Jim Weirich

Confreaks65.7K views

Jim Weirich derives the Y combinator live, step by step, using nothing but Ruby lambdas, and along the way teaches the refactorings of lambda calculus.

2:04:55

CS50x 2024 - Lecture 0 - Scratch

CS502.2M views

CS50x 2024 lecture 0: how computers represent information, algorithms, and first programs in Scratch.

RailsConf 2014 - All the Little Things by Sandi Metz

Confreaks190K views

Sandi Metz refactors the notorious Gilded Rose kata live, showing how small, disciplined steps and duplication-over-wrong-abstraction lead to clean object-oriented code.