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THE CO-FOUNDER OF GITHUB GAVE A 46-MINUTE TALK ON GIT BECAUSE ENGINEERS WITH 10 YEARS IN HAVE NEVER SEEN HALF OF WHAT IT DOES This is Scott Chacon. He wrote Pro Git -- the book most devs secretly learned Git from and he co-founded GitHub. So when he says... you're missing things, you're missing things. About ten minutes in it clicks: half the "git disasters" you've ever fixed by deleting the folder and re-cloning had a one-line solution sitting in the tool the whole time. Git ships new code almost every day -> roughly nine commits a day for over a decade. Most of us stopped learning it the second we memorized add, commit, push. Knowing Git isn't a senior-dev flex anymore -> it's the floor. The agent writes the code now. Your real job is reading, branching, and untangling the history it leaves behind. The day an AI agent force-pushes over your main branch, these 46 minutes are the difference between a quiet fix and a very loud apology. Save it now. You'll reach for it sooner than you'd like ↓show more

slash1s

13,750 subscribers

28,133 просмотров • 4 месяцев назад •via X (Twitter)

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Комментарии: 33

Фото профиля shmidt

shmidt4 месяцев назад

realizing i've been using git on hard mode this whole time by not knowing what i'm doing

Фото профиля slash1s

slash1s4 месяцев назад

sadly bro

Фото профиля slash1s

slash1s4 месяцев назад

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

Фото профиля 0xbobaa

0xbobaa4 месяцев назад

when is his next lecture?

Фото профиля slash1s

slash1s4 месяцев назад

will send bro

Фото профиля Hussain Hashim | Building SundayBack

Hussain Hashim | Building SundayBack4 месяцев назад

@slash1sol wow, didn't know there was that much to it. always thought I was using git like a pro, but maybe not 😂 gonna have to check out that talk now

Фото профиля Gipp 🦅

Gipp 🦅4 месяцев назад

This bro is a legend and he created such an app for people

Фото профиля slash1s

slash1s4 месяцев назад

facts

Фото профиля monokern

monokern4 месяцев назад

it's worth taking 45 minutes of your time to watch this

Фото профиля slash1s

slash1s4 месяцев назад

truuue

Фото профиля Yarchi

Yarchi4 месяцев назад

git stopped being a flex and became the floor, he's right

Фото профиля Insomnia

Insomnia4 месяцев назад

full break down in 46 minutes

Фото профиля David Asher Simpson

David Asher Simpson4 месяцев назад

Classic! Extolling the virtues of a PM shipping features your target users are unaware of as somehow meritorious.

Фото профиля cristal💎

cristal💎4 месяцев назад

scott chacon knows git mechanics better than anyone

Фото профиля Bizzi

Bizzi4 месяцев назад

slash1s educates us

Фото профиля vorty

vorty4 месяцев назад

half the git disasters you fixed by re-cloning had a one-line solution sitting in the tool the whole time

Фото профиля Hanako

Hanako4 месяцев назад

the older i get, the more git matters

Фото профиля rari

rari4 месяцев назад

is worth to bookmark it 👀

Фото профиля Deydara

Deydara4 месяцев назад

A must-listen

Фото профиля Fokki

Fokki4 месяцев назад

Scott knows what he is talking about

Фото профиля leopardracer

leopardracer4 месяцев назад

thanks for sharing this alpha🙌🏽

Фото профиля cashhh.eth

cashhh.eth4 месяцев назад

rly interestin,ty!

Фото профиля 𝗢𝗠𝗘𝗚𝗔

𝗢𝗠𝗘𝗚𝗔4 месяцев назад

most devs will watch the 46 minutes then keep using the same three commands

Фото профиля kiosa

kiosa4 месяцев назад

Very useful bookmarked thanks

Фото профиля Atenov int.

Atenov int.4 месяцев назад

And I remember when I first learned Git, I didnt even touch half of its features.

Фото профиля Spivach

Spivach4 месяцев назад

i have thought a platform was totally done, and there is no need to update it, but I was totally wrong

Фото профиля Ridark

Ridark4 месяцев назад

The level of conversation is such that you want to take notes of every word

Фото профиля SCOTTY BEAM

SCOTTY BEAM4 месяцев назад

alpha as always bro, very interesting to listen, thx

Фото профиля grev

grev4 месяцев назад

Is it all because of new technologies?

Фото профиля Nekt0

Nekt04 месяцев назад

Go to watch this useful alpha

Фото профиля AnsuzIndustrial

AnsuzIndustrial4 месяцев назад

Actually there is no cofounder Linus Torvald built got in ten days now delete this post

Фото профиля cvxv666

cvxv6664 месяцев назад

real alpha. thx for sharing this stuff

Фото профиля vijn

vijn4 месяцев назад

this co-founder r legend!

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Git Merge vs. Rebase vs. Squash Commit What are the differences and when should you use each? As I explain in more detail in the video, there are some key distinctions. Git Merge This creates a new commit in the target branch. The new commit ties the histories of both main and feature branches together. Git merge is non-destructive - it introduces a new commit without altering existing ones. Git Rebase Rebase transplants commits to the tip of another branch. It creates new commits for each one moved over. The benefit is linear history. But be cautious with shared branches to avoid confusing collaborators. Squash Commit Squashing condenses multiple commits into one, streamlining the commit history. Watch the video to see when to use merge vs rebase vs squash when incorporating changes between main and feature branches. – Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages):

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slash1s

12,797 просмотров • 3 месяцев назад

ChatGPT Pro just FIXED my iPhone app in 46 minutes. It's way smarter, but less interactive to drive. Here are 3 ChatGPT Pro Tips: 1. Use the GitHub Plugin with ChatGPT Pro 2. Make the git branch for it to use. Ask for small atomic commits 3. Tell it to push changes as it works, because if it's tool calls time out, your code disappears... I have 2% of my tokens that reset in 2 hours.

ChatGPT Pro just FIXED my iPhone app in 46 minutes. It's way smarter, but less interactive to drive. Here are 3 ChatGPT Pro Tips: 1. Use the GitHub Plugin with ChatGPT Pro 2. Make the git branch for it to use. Ask for small atomic commits 3. Tell it to push changes as it works, because if it's tool calls time out, your code disappears... I have 2% of my tokens that reset in 2 hours.

Paul Solt

51,588 просмотров • 1 месяц назад

One of the best ways to win your time back with GitHub Copilot is to have it generate Git commit messages for you. Everyone has their own style - share yours with Copilot using Custom Instructions and save yourself a ton of time.

One of the best ways to win your time back with GitHub Copilot is to have it generate Git commit messages for you. Everyone has their own style - share yours with Copilot using Custom Instructions and save yourself a ton of time.

Visual Studio Code

66,328 просмотров • 1 год назад

HARVARD RELEASED A 65-MIN MASTERCLASS ON GIT & GITHUB BECAUSE VIBE-CODERS STILL DON'T KNOW HOW TO COMMIT 1 hour and 5 minutes of raw, no-nonsense version control architecture from the creators of CS50. -> The moment you watch it, you realize why most modern developers are breaking their production branches. Every tier-1 tech company is now filtering candidates who can't handle basic merge conflicts. Git isn't a "nice-to-know" anymore -> it's compliance. Your AI can write the code. That wasn't the problem. The problem is you don't know how to merge it without breaking the repo. Don’t forget to bookmark it.

HARVARD RELEASED A 65-MIN MASTERCLASS ON GIT & GITHUB BECAUSE VIBE-CODERS STILL DON'T KNOW HOW TO COMMIT 1 hour and 5 minutes of raw, no-nonsense version control architecture from the creators of CS50. -> The moment you watch it, you realize why most modern developers are breaking their production branches. Every tier-1 tech company is now filtering candidates who can't handle basic merge conflicts. Git isn't a "nice-to-know" anymore -> it's compliance. Your AI can write the code. That wasn't the problem. The problem is you don't know how to merge it without breaking the repo. Don’t forget to bookmark it.

slash1s

253,500 просмотров • 4 месяцев назад

Ex-Google engineer built a graph-based workflow that made Claude Code do nearly 10 days of work in about an hour. Here's the exact setup he uses. step 1. create a separate Git worktree for every task. run: git worktree add ../task-1 -b task-1 open a new terminal, cd into it, and launch Claude Code. repeat this for every agent. each one gets its own branch, so nothing conflicts. step 2. give every Claude agent a different task. same repository. different branches. they all work in parallel. step 3. once they're done, review the pull requests. keep the good ones. merge what works. step 4. add a review agent. paste each PR into Claude and ask: "does this implementation match the original specification" every agent now has another agent reviewing its work before it gets merged. step 5. scale it up. 48GB of RAM can comfortably run around 20 Claude Code agents. 128GB can handle roughly 50. most engineers run Claude Code once and wait. he runs dozens of Claude Code agents in parallel, then merges the best results. this 60-minute lecture is one of the best free resources on graph engineering and multi-agent workflows. bookmark it and watch it below.

Ex-Google engineer built a graph-based workflow that made Claude Code do nearly 10 days of work in about an hour. Here's the exact setup he uses. step 1. create a separate Git worktree for every task. run: git worktree add ../task-1 -b task-1 open a new terminal, cd into it, and launch Claude Code. repeat this for every agent. each one gets its own branch, so nothing conflicts. step 2. give every Claude agent a different task. same repository. different branches. they all work in parallel. step 3. once they're done, review the pull requests. keep the good ones. merge what works. step 4. add a review agent. paste each PR into Claude and ask: "does this implementation match the original specification" every agent now has another agent reviewing its work before it gets merged. step 5. scale it up. 48GB of RAM can comfortably run around 20 Claude Code agents. 128GB can handle roughly 50. most engineers run Claude Code once and wait. he runs dozens of Claude Code agents in parallel, then merges the best results. this 60-minute lecture is one of the best free resources on graph engineering and multi-agent workflows. bookmark it and watch it below.

MIKE

32,199 просмотров • 2 месяцев назад

IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓

slash1s

22,107 просмотров • 3 месяцев назад

haha, i used OpenAI operator build, deploy, and open source a tool on github using Replit ⠕ agent. took about 30 min, here's an ~8 min supercut video thoughts: - while working with replit agent, it actually deployed the app, tested it, and described the error back to replit agent for me - operator asked me a few more Qs than i wanted, but it was mostly for safety (eg filling forms) so i guess okay with it - it had trouble with a few things around UI like knowing it needs to scroll a page to see the rest of it, and it needed pointers to find the git feature in replit - once it found the git feature it didn't need my assistance to create a repo and open source after having the agent write a readme while a bit slower, this was even more automated than replit agent (especially testing features and working through errors) - which is impressive would be nice to have: push notifications for when it needs my attention, and voice mode capabilities

haha, i used OpenAI operator build, deploy, and open source a tool on github using Replit ⠕ agent. took about 30 min, here's an ~8 min supercut video thoughts: - while working with replit agent, it actually deployed the app, tested it, and described the error back to replit agent for me - operator asked me a few more Qs than i wanted, but it was mostly for safety (eg filling forms) so i guess okay with it - it had trouble with a few things around UI like knowing it needs to scroll a page to see the rest of it, and it needed pointers to find the git feature in replit - once it found the git feature it didn't need my assistance to create a repo and open source after having the agent write a readme while a bit slower, this was even more automated than replit agent (especially testing features and working through errors) - which is impressive would be nice to have: push notifications for when it needs my attention, and voice mode capabilities

Yohei

212,031 просмотров • 1 год назад

MIT HANDED ITS DEEP LEARNING COURSE TO A FRONTIER-LAB ENGINEER FOR 68 MINUTES BECAUSE 90% OF PEOPLE SHIPPING AI CODE CAN'T EXPLAIN HOW THE MODEL ACTUALLY WORKS This is Maxime Labonne. He runs post-training at Liquid AI and wrote the LLM Engineer's Handbook. MIT gave him the room to break down the engine sitting inside every coding agent you've ever prompted. Twenty minutes in it stops being abstract. You finally see why the model confidently invents things that don't exist, why context is everything, and why "Just tell it to try again" sometimes fixes it and sometimes makes it worse. In 2026 "I use AI to code" stopped being a skill. Knowing why the model behaves the way it does -> tokens, context, post-training, where it quietly breaks -> is what separates someone who ships from someone babysitting a black box. Understanding an LLM isn't a research-team luxury anymore -> it's the difference between driving the agent and being driven by it. Anyone can prompt. The person who knows what's under the hood is the one still standing when the prompt stops working. Save this one & actually finish it ↓

MIT HANDED ITS DEEP LEARNING COURSE TO A FRONTIER-LAB ENGINEER FOR 68 MINUTES BECAUSE 90% OF PEOPLE SHIPPING AI CODE CAN'T EXPLAIN HOW THE MODEL ACTUALLY WORKS This is Maxime Labonne. He runs post-training at Liquid AI and wrote the LLM Engineer's Handbook. MIT gave him the room to break down the engine sitting inside every coding agent you've ever prompted. Twenty minutes in it stops being abstract. You finally see why the model confidently invents things that don't exist, why context is everything, and why "Just tell it to try again" sometimes fixes it and sometimes makes it worse. In 2026 "I use AI to code" stopped being a skill. Knowing why the model behaves the way it does -> tokens, context, post-training, where it quietly breaks -> is what separates someone who ships from someone babysitting a black box. Understanding an LLM isn't a research-team luxury anymore -> it's the difference between driving the agent and being driven by it. Anyone can prompt. The person who knows what's under the hood is the one still standing when the prompt stops working. Save this one & actually finish it ↓

slash1s

236,758 просмотров • 4 месяцев назад

MIT GAVE DEBUGGING ITS OWN FULL LECTURE -- BECAUSE MOST DEVS STILL HUNT BUGS WITH PRINT STATEMENTS LIKE IT'S 1995 54 minutes that take the thing you do every single day, badly, and show you the tools schools never bothered to teach. -> The moment it lands, you realize "add a print, run it, add another print" was never debugging. It was guessing with extra steps. Most people never learned the real toolkit. A proper debugger, breakpoints, tracing what the program actually does instead of what you assume it does. In 2026 guessing isn't good enough -> the bug is buried in code you didn't even write, and printf won't find it for you. An AI agent will generate hundreds of lines in seconds. When one of them quietly breaks, finding it runs on exactly the skills in this lecture. Anyone can add a print statement. The person who can actually trace a bug to its source is the one who ships while everyone else guesses. Bookmark & Watch it ↓

MIT GAVE DEBUGGING ITS OWN FULL LECTURE -- BECAUSE MOST DEVS STILL HUNT BUGS WITH PRINT STATEMENTS LIKE IT'S 1995 54 minutes that take the thing you do every single day, badly, and show you the tools schools never bothered to teach. -> The moment it lands, you realize "add a print, run it, add another print" was never debugging. It was guessing with extra steps. Most people never learned the real toolkit. A proper debugger, breakpoints, tracing what the program actually does instead of what you assume it does. In 2026 guessing isn't good enough -> the bug is buried in code you didn't even write, and printf won't find it for you. An AI agent will generate hundreds of lines in seconds. When one of them quietly breaks, finding it runs on exactly the skills in this lecture. Anyone can add a print statement. The person who can actually trace a bug to its source is the one who ships while everyone else guesses. Bookmark & Watch it ↓

slash1s

10,864 просмотров • 4 месяцев назад