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A DEVELOPER TAUGHT GIT WITH A BOX OF CHILDREN'S TOYS AND ENGINEERS WITH TEN YEARS IN SAY IT'S THE FIRST TIME THE THING EVER ACTUALLY MADE SENSE 90 minutes, one table, a pile of Tinkertoys. No wall of jargon -- he builds a real Git repo out of plastic...

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slash1s

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228,636 次观看 • 3 个月前 •via X (Twitter)

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42 条评论

MBH 的头像
MBH3 个月前

@jetha You should link to the original video instead of stealing it for engagement farming. Also, no one likes watching long videos on this horrid platform. Michale G Schwern: Git for Ages 4 and Up Posted on YouTube 9 years ago.

shmidt 的头像
shmidt3 个月前

this is unhinged in the best way finally someone who gets that git is just... objects pointing at other objects

slash1s 的头像
slash1s3 个月前

welcome bro

slash1s 的头像
slash1s3 个月前

join my tg for the actual alpha on ai, financial markets and coding ->

Ridark 的头像
Ridark3 个月前

The graphics overlay during technical explanations was clutch

slash1s 的头像
slash1s3 个月前

👀

monokern 的头像
monokern3 个月前

used Git for 5 years before I actually understood what a commit object was this hurts a little

slash1s 的头像
slash1s3 个月前

🥲

Aleiah 的头像
Aleiah3 个月前

90 min and so much information

slash1s 的头像
slash1s3 个月前

😉 u know

Victor | Structural Alpha 的头像
Victor | Structural Alpha3 个月前

the tinkertoys are cute but the real move is having the guts to say 'let's start over' to a room of seniors. i've sat in those trainings. nobody asks the dumb question because everyone thinks they're the only one faking

vijn 的头像
vijn3 个月前

bookmarked

slash1s 的头像
slash1s3 个月前

🤝

Yarchi 的头像
Yarchi3 个月前

holding the model beats memorizing commands every single time

Insomnia 的头像
Insomnia3 个月前

new lecturer which I saved

slash1s 的头像
slash1s3 个月前

🤝🤝

Mike Sullivan 的头像
Mike Sullivan3 个月前

And at what point are you going to share the link to his original video or provide some attribution?

Bizzi 的头像
Bizzi3 个月前

I’ll watch it bro thanks

slash1s 的头像
slash1s3 个月前

right decision imo

AdiiX 的头像
AdiiX3 个月前

Best 90 min today

slash1s 的头像
slash1s3 个月前

100% bro

Gipp 🦅 的头像
Gipp 🦅3 个月前

I think these will be my best 90 minutes

slash1s 的头像
slash1s3 个月前

will see👀👀

Lummox 的头像
Lummox3 个月前

Uhhh, thanks for dropping it Best video before going to bed

slash1s 的头像
slash1s3 个月前

nice bro🙌

DEFINIT og 的头像
DEFINIT og3 个月前

おもちゃを使ってGitを教える開発者は、エンジニアたちにはじめて理解できるようになりました。真の理解は簡単で、複雑なコマンドラインではありません。Gitは小さなオブジェクトの連鎖です。命令を覚えるよりも、モデルを保持することが重要です。その1.5時間は、あなたのキャリアのために返ってくる価値があります。

zostaff 的头像
zostaff3 个月前

ty for sharing

Dinh Chung 的头像
Dinh Chung3 个月前

おもちゃでGitを教えてもらうことで、エンジニアと10年間一緒にいる人たちは、この教え方で初めてGitが理解できたと言います。どのようなおもちゃを使って教えられたのでしょうか？

cvxv666 的头像
cvxv6663 个月前

these guys looks like real geeks haha

exodus 的头像
exodus3 个月前

That was a great lecture. Thanks for sharing it.

beamnxw ./ 的头像
beamnxw ./3 个月前

holding the git graph in your head is everything

IRMC 的头像
IRMC3 个月前

Thank you. Maybe I will start using git after watching this video. I've installed git and now more than 3000 commits are waiting.

Tokiki Takatochiku ⭐⭐ 的头像
Tokiki Takatochiku ⭐⭐3 个月前

@readwise save

Hanako 的头像
Hanako3 个月前

the graph is the thing, commands are just shortcuts

cristal💎 的头像
cristal💎3 个月前

lets stop treating version control like scary command-line magic

Zack Forsyth 的头像
Zack Forsyth3 个月前

Quite nice. Thanks for putting it up.

Marius Miclau 的头像
Marius Miclau3 个月前

the tinkertoys thing works because git is actually simple but we teach it backwards , most tutorials start with merge conflicts instead of just showing you it's snapshots with pointers

Nekt0 的头像
Nekt03 个月前

he knows a thing or two about making money

Communication through ❤️ mutual influence 的头像
Communication through ❤️ mutual influence3 个月前

The hype is just like crypto.

kiosa 的头像
kiosa3 个月前

Those people studied in one school for sure

kvro 的头像
kvro3 个月前

the future probably belongs to models that can manage complexity not just generate code

Grobb 的头像
Grobb3 个月前

@grok worth watching?

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THE GUY WHO BUILT GIT GAVE A FULL LECTURE AT GOOGLE BECAUSE 99% OF DEVELOPERS USE IT WRONG 70 minutes of pure firepower from Linus Torvalds himself - the man who wrote both Linux and Git from scratch. -> The moment you watch it, you realize why "I'll just figure out merge conflicts on the job" is the dumbest sentence in modern software engineering. He spends the first 10 minutes calling out every other version control system in existence and he's not joking. He literally tells Google engineers using Perforce to find a new tool. Git isn't a "nice-to-have" anymore -> it's the operating system of every codebase you'll ever touch. If the man who built it had to explain it to a room full of Google engineers, you don't get a pass either. Don't forget to bookmark & watch it today.
1:09:56

THE GUY WHO BUILT GIT GAVE A FULL LECTURE AT GOOGLE BECAUSE 99% OF DEVELOPERS USE IT WRONG 70 minutes of pure firepower from Linus Torvalds himself - the man who wrote both Linux and Git from scratch. -> The moment you watch it, you realize why "I'll just figure out merge conflicts on the job" is the dumbest sentence in modern software engineering. He spends the first 10 minutes calling out every other version control system in existence and he's not joking. He literally tells Google engineers using Perforce to find a new tool. Git isn't a "nice-to-have" anymore -> it's the operating system of every codebase you'll ever touch. If the man who built it had to explain it to a room full of Google engineers, you don't get a pass either. Don't forget to bookmark & watch it today.

slash1s

214,967 次观看 • 4 个月前

A DEVELOPER WHO HELPS MAINTAIN GIT ITSELF PROVED THAT USING GIT AND CONTRIBUTING WITH GIT ARE TWO DIFFERENT SKILLS AND ALMOST NO ONE LEARNS THE SECOND 55 minutes from Johannes Schindelin, one of git's most prolific contributors, on the workflow that gets your code accepted into a project you don't own. -> The moment it lands, committing to your own repo turns out to be the easy 10%. Landing a change in someone else's codebase is the part nobody taught you. Most people can save their own work. Far fewer can revise a patch five times, keep the history clean, and merge it into a project moving under them. Saving your code was never the skill -> getting it merged into someone else's is. And when an AI agent fires off a pull request nobody asked for, the person who knows how to really contribute is the one who gets it accepted instead of closed. Anyone can commit to their own repo. The person who can land a change in a project they don't own is the one who actually ships. Bookmark & Watch it today ↓
55:43

A DEVELOPER WHO HELPS MAINTAIN GIT ITSELF PROVED THAT USING GIT AND CONTRIBUTING WITH GIT ARE TWO DIFFERENT SKILLS AND ALMOST NO ONE LEARNS THE SECOND 55 minutes from Johannes Schindelin, one of git's most prolific contributors, on the workflow that gets your code accepted into a project you don't own. -> The moment it lands, committing to your own repo turns out to be the easy 10%. Landing a change in someone else's codebase is the part nobody taught you. Most people can save their own work. Far fewer can revise a patch five times, keep the history clean, and merge it into a project moving under them. Saving your code was never the skill -> getting it merged into someone else's is. And when an AI agent fires off a pull request nobody asked for, the person who knows how to really contribute is the one who gets it accepted instead of closed. Anyone can commit to their own repo. The person who can land a change in a project they don't own is the one who actually ships. Bookmark & Watch it today ↓

slash1s

12,797 次观看 • 3 个月前

IN 1999 MIT FILMED A MATH LECTURE THAT QUIETLY BECAME THE FOUNDATION OF EVERY AI MODEL YOU'VE EVER USED AND ALMOST NO ONE WAS TAUGHT TO SEE IT THAT WAY 39 minutes from Gilbert Strang, who taught this at MIT for over 60 years -- the linear algebra course an entire generation of engineers and data scientists grew up on. -> The shift it creates: you stop seeing matrices as boring grids of numbers and start seeing them as the language of space, data, and motion itself. School drilled you to crunch matrices by hand and never told you why. Strang shows you what they actually mean. Every neural net, every embedding, every model you prompt is linear algebra running underneath. The math you skipped is the engine of the thing you use all day. Memorizing the steps was never the skill -> seeing what the numbers do is. This is where it finally clicks. Most people fear linear algebra and move on. The ones who watched this see straight into how AI actually works. Bookmark & Watch it today, this one's a legend ↓
39:31

IN 1999 MIT FILMED A MATH LECTURE THAT QUIETLY BECAME THE FOUNDATION OF EVERY AI MODEL YOU'VE EVER USED AND ALMOST NO ONE WAS TAUGHT TO SEE IT THAT WAY 39 minutes from Gilbert Strang, who taught this at MIT for over 60 years -- the linear algebra course an entire generation of engineers and data scientists grew up on. -> The shift it creates: you stop seeing matrices as boring grids of numbers and start seeing them as the language of space, data, and motion itself. School drilled you to crunch matrices by hand and never told you why. Strang shows you what they actually mean. Every neural net, every embedding, every model you prompt is linear algebra running underneath. The math you skipped is the engine of the thing you use all day. Memorizing the steps was never the skill -> seeing what the numbers do is. This is where it finally clicks. Most people fear linear algebra and move on. The ones who watched this see straight into how AI actually works. Bookmark & Watch it today, this one's a legend ↓

slash1s

434,785 次观看 • 3 个月前

When you touch something warm, a Yale physicist can tell you exactly what you are feeling. Not heat. The speed of atoms hitting your hand. His name is Ramamurthy Shankar. You were taught that temperature means how hot something is. That is a description, not an answer. In this lecture he goes under the word and shows what temperature actually is, and it is not what any school ever told you. He builds it from nothing. A box of gas. Invisible atoms bouncing off the walls. He counts the hits, tracks the momentum, and slowly two sides of a chalkboard drift toward each other. When they finally meet, out falls one clean line that redefines a word you have used your whole life. The same lecture answers a question that should be impossible. How did anyone count the atoms in a gram of matter before anyone could prove atoms were real? The answer is so simple it feels like cheating, and it is why a single number, six followed by 23 zeros, sits at the center of chemistry. He assumes nothing. Every step is earned in front of you, no memorizing, no faith required. This is the lecture where hot and cold stop being feelings and become physics.
1:14:40

When you touch something warm, a Yale physicist can tell you exactly what you are feeling. Not heat. The speed of atoms hitting your hand. His name is Ramamurthy Shankar. You were taught that temperature means how hot something is. That is a description, not an answer. In this lecture he goes under the word and shows what temperature actually is, and it is not what any school ever told you. He builds it from nothing. A box of gas. Invisible atoms bouncing off the walls. He counts the hits, tracks the momentum, and slowly two sides of a chalkboard drift toward each other. When they finally meet, out falls one clean line that redefines a word you have used your whole life. The same lecture answers a question that should be impossible. How did anyone count the atoms in a gram of matter before anyone could prove atoms were real? The answer is so simple it feels like cheating, and it is why a single number, six followed by 23 zeros, sits at the center of chemistry. He assumes nothing. Every step is earned in front of you, no memorizing, no faith required. This is the lecture where hot and cold stop being feelings and become physics.

Silverhand

22,362 次观看 • 2 个月前

A DEVELOPER PROVED THE REGEX YOU'VE WRITTEN A THOUSAND TIMES IS SECRETLY A COMPILER AND THAT ALMOST NO ONE WHO USES THEM HAS ANY IDEA WHAT ACTUALLY RUNS 36 minutes from Paul Wankadia, the engineer behind a regex engine that compiles your pattern straight down to raw machine code -- walking through what really happens between the slashes. -> The moment it clicks, regex stops being magic punctuation you paste from Stack Overflow and becomes what it actually is: a tiny machine. Your pattern gets turned into a state machine, and that machine is what runs against every character of your text. That one idea explains everything you never understood. Why one regex returns instantly and a nearly identical one hangs your whole server. Why some patterns are safe and others are a denial-of-service waiting to happen. It was never random -- it's whether the machine underneath is built well or badly. Writing a regex was never the skill -> reading one is. And now that an AI agent hands you dense, clever patterns you'd never write yourself, the person who can see the machine underneath is the one who catches the one that takes down production at 3am. Everyone copies regex and prays. This is the talk that ends the praying. Save it. The next time a pattern "Just works," you'll actually know why ↓
36:09

A DEVELOPER PROVED THE REGEX YOU'VE WRITTEN A THOUSAND TIMES IS SECRETLY A COMPILER AND THAT ALMOST NO ONE WHO USES THEM HAS ANY IDEA WHAT ACTUALLY RUNS 36 minutes from Paul Wankadia, the engineer behind a regex engine that compiles your pattern straight down to raw machine code -- walking through what really happens between the slashes. -> The moment it clicks, regex stops being magic punctuation you paste from Stack Overflow and becomes what it actually is: a tiny machine. Your pattern gets turned into a state machine, and that machine is what runs against every character of your text. That one idea explains everything you never understood. Why one regex returns instantly and a nearly identical one hangs your whole server. Why some patterns are safe and others are a denial-of-service waiting to happen. It was never random -- it's whether the machine underneath is built well or badly. Writing a regex was never the skill -> reading one is. And now that an AI agent hands you dense, clever patterns you'd never write yourself, the person who can see the machine underneath is the one who catches the one that takes down production at 3am. Everyone copies regex and prays. This is the talk that ends the praying. Save it. The next time a pattern "Just works," you'll actually know why ↓

slash1s

193,107 次观看 • 3 个月前

BlackRock runs on 20,000 people. Elon's Grok Bot runs the same shape for $300 a month, and it hires its own staff. You do not get an assistant. You get a company that hires. It does not throw ten agents at your problem and hand you the pile. It makes one agent that makes 10, and those ten make a 100. > LAYER ONE is one agent, the chief of staff, and it never touches the market > LAYER TWO is six desk heads, one job each, every one on its own computer with its own logins > LAYER THREE is whatever those six decide they need, spun up on the spot and shut down when the work is done Nobody writes a task list. You hand out job titles and the org fills itself in underneath. The swarm is never the same twice. Agents get spun up for one job, finish it, and are gone before I ever read their names. Not one of them sees the whole picture. The answer only exists after they hand off to each other. Wall Street cannot copy that. You cannot hire a hundred people for eleven minutes. BlackRock holds that shape together with a risk system called Aladdin. Mine holds it together with one agent that is only allowed to say no. I gave it $1,000 and told it to grow the money or get deleted. 15 hours later it was holding $3,900, on an address anyone can open and read. I was asleep for most of it, and I have still not written a line of code. The whole thing runs with my laptop shut, because none of it lives on my laptop. Setup is one evening. Create the chief, hand out the titles, run one trade on your screen while they watch, connect Telegram. Ten years ago a machine this shape had its name on a tower. Mine has a name I typed into a box. Save this while the whole thing still fits on one screen.
0:45

BlackRock runs on 20,000 people. Elon's Grok Bot runs the same shape for $300 a month, and it hires its own staff. You do not get an assistant. You get a company that hires. It does not throw ten agents at your problem and hand you the pile. It makes one agent that makes 10, and those ten make a 100. > LAYER ONE is one agent, the chief of staff, and it never touches the market > LAYER TWO is six desk heads, one job each, every one on its own computer with its own logins > LAYER THREE is whatever those six decide they need, spun up on the spot and shut down when the work is done Nobody writes a task list. You hand out job titles and the org fills itself in underneath. The swarm is never the same twice. Agents get spun up for one job, finish it, and are gone before I ever read their names. Not one of them sees the whole picture. The answer only exists after they hand off to each other. Wall Street cannot copy that. You cannot hire a hundred people for eleven minutes. BlackRock holds that shape together with a risk system called Aladdin. Mine holds it together with one agent that is only allowed to say no. I gave it $1,000 and told it to grow the money or get deleted. 15 hours later it was holding $3,900, on an address anyone can open and read. I was asleep for most of it, and I have still not written a line of code. The whole thing runs with my laptop shut, because none of it lives on my laptop. Setup is one evening. Create the chief, hand out the titles, run one trade on your screen while they watch, connect Telegram. Ten years ago a machine this shape had its name on a tower. Mine has a name I typed into a box. Save this while the whole thing still fits on one screen.

cvxv666

45,488 次观看 • 25 天前

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.
1:54

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.

Milind S

12,409 次观看 • 2 个月前

Boris Cherny (creator of Claude Code, Anthropic): "My entire CLAUDE.md is two lines. With every new model you need less instruction, not more, most people are over-engineering the one thing that should stay tiny." in a 7-minute interview, Boris Cherny breaks down why the smallest AI-coding setup wins, and the one moment you should delete your config and start from scratch most engineers do the opposite: they pile on rules, build scaffolding around the model… then the next model ships and makes all of it useless. what he actually keeps in those two lines, and why he tells his team to throw the rest away. Watch the talk, then read the article below. That’s worth more than a $800 course on agent engineering.
7:13

Boris Cherny (creator of Claude Code, Anthropic): "My entire CLAUDE.md is two lines. With every new model you need less instruction, not more, most people are over-engineering the one thing that should stay tiny." in a 7-minute interview, Boris Cherny breaks down why the smallest AI-coding setup wins, and the one moment you should delete your config and start from scratch most engineers do the opposite: they pile on rules, build scaffolding around the model… then the next model ships and makes all of it useless. what he actually keeps in those two lines, and why he tells his team to throw the rest away. Watch the talk, then read the article below. That’s worth more than a $800 course on agent engineering.

Prometheus

238,143 次观看 • 3 个月前