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MIT DEDICATED A FULL LECTURE TO GIT'S INTERNALS -- BECAUSE THEY FOUND MOST DEVS MEMORIZE THE COMMANDS AND HAVE NO IDEA WHAT THE TOOL ACTUALLY DOES A whole 85 minutes MIT session that refuses to teach git as a list of commands to copy, and instead shows you the...

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slash1s

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459,754 Aufrufe • vor 3 Monaten •via X (Twitter)

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33 Kommentare

Profilbild von Rohan Gayen
Rohan Gayenvor 3 Monaten

If anyone wants the youtube link of the original video

Profilbild von stephane.eth
stephane.ethvor 3 Monaten

it’s next to impossible to actually lose any code once that code has been committed That’s what most devs fear and why the unofficial "mv repo repo.backup; git clone <cloneagain>" is so popular 😝 Compiled a couple more references (and a hopefully truly easy walkthrough) here:

Profilbild von Nicolae
Nicolaevor 3 Monaten

You don't need to know the intervals of every technology you are using. And in fact most don't and do just fine.

Profilbild von slash1s
slash1svor 3 Monaten

join my tg for the actual alpha on ai, financial markets and coding -&gt;

Profilbild von Philip Stubbs
Philip Stubbsvor 3 Monaten

1) I require our devs to use GIT Extensions - visualization makes a big difference... 2) most grads have minimal experience with practical necessities -&gt; GIT, versioning, coding standards, etc... 3) college creates tech debt monsters -&gt; who skip design &amp; never diagram anything 🤯

Profilbild von Bitchin’ Groyper
Bitchin’ Groypervor 3 Monaten

I taught myself by reading articles about understanding git and using it.

Profilbild von cristal💎
cristal💎vor 3 Monaten

recloning the repo is so junior

Profilbild von Sergy Skripal: HABEAS CORPUS!
Sergy Skripal: HABEAS CORPUS!vor 3 Monaten

BS. Git is a travesty, an ego trip of Linus T. It's a fantastically complicated tool to solve problems that only a small subset of developers have. Its complication doesn't flow from its power but from its chaos - it's largely non-orthogonal, with many islands of cmd groups

Profilbild von Kyle
Kylevor 3 Monaten

during early experiments and git worktrees with orchestrating agent I saw the most tangled git mess concievable - and a single agent was unable to untangle the entire thing in 15minutes which would have taken me hours.

Profilbild von Eplurubusnullus
Eplurubusnullusvor 3 Monaten

Meh. I know how git works underneath, it's simple and elegant. The syntax always crashes me out, though. The problem most devs have is that they only have a surface level understanding of everything. It's why even AI can code.

Profilbild von Brandon Smith
Brandon Smithvor 3 Monaten

If so many people have problems with git then git is the problem.

Profilbild von Adel Bucetta
Adel Bucettavor 3 Monaten

that's where most ai agents are too, memorizing rules without understanding what they're optimizing for

Profilbild von Atenov int.
Atenov int.vor 3 Monaten

But what if you dont have 85 minutes to learn git internals - can you learn as you go?

Profilbild von Gipp 🦅
Gipp 🦅vor 3 Monaten

It's very interesting to hear about repositories

Profilbild von Codes for lattes ☕️
Codes for lattes ☕️vor 3 Monaten

Yeah no shit that’s why we use the tool so we don’t have to know the internals 😂

Profilbild von Lummox
Lummoxvor 3 Monaten

Have watched almost 85 minutes,really smart lecture

Profilbild von Peter S
Peter Svor 3 Monaten

Good content, but the low resolution makes the text in the video hard to read and tiring to watch. Is it available anywhere else?

Profilbild von Andrew Voelker
Andrew Voelkervor 3 Monaten

just have claude do the source-control crap.

Profilbild von Rob Williams
Rob Williamsvor 3 Monaten

Better idea: adopt jujutsu.

Profilbild von Nekt0
Nekt0vor 3 Monaten

Very interesting post

Profilbild von vijn
vijnvor 3 Monaten

1 hour of alpha

Profilbild von AI Mastery Guide
AI Mastery Guidevor 3 Monaten

"Four commands, blind faith, and a prayer before every merge" is the most accurate description of how most people use git 😭

Profilbild von Anthony Porcano
Anthony Porcanovor 3 Monaten

In 2026 Claude handles git for me.

Profilbild von Michael Farnet
Michael Farnetvor 3 Monaten

GitCraft!

Profilbild von rari
rarivor 3 Monaten

the person who understands the data model is the one who saves the repo

Profilbild von Suzanne Atkinson, MD
Suzanne Atkinson, MDvor 3 Monaten

a post bashing ai written with ai. nice.

Profilbild von shmidt
shmidtvor 3 Monaten

this is how it should be taught honestly, understanding the graph changes everything

Profilbild von EMOTION CRYPTO
EMOTION CRYPTOvor 3 Monaten

This lecture is very useful, I think the students will learn this lesson.

Profilbild von leopardracer
leopardracervor 3 Monaten

wow, nice share👍🏽

Profilbild von Kekko D’Amato
Kekko D’Amatovor 3 Monaten

The git-as-DAG mental model changes everything. Once you see commits as immutable snapshots and branches as just pointers, 'scary' operations like rebase stop being incantations you copy from Stack Overflow and become obvious graph manipulations. The AI angle makes this even more urgent — agents that mess up git history need a human who actually understands the model to clean it up. "I'll just reclone it" doesn't cut it when an agent has been autonomously committing for hours.

Profilbild von 0xbobaa
0xbobaavor 3 Monaten

very interesting lecture

Profilbild von Gustavo J. Alessandri
Gustavo J. Alessandrivor 3 Monaten

Once you see governance as a graph of decisions, approvals and reversals, the distinction between "software" and "organization" starts to disappear. Git versioned code. I'm interested in versioning governance itself. Repo ↓

Profilbild von Bizzi
Bizzivor 3 Monaten

Worth watching 100%

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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 Aufrufe • vor 3 Monaten

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 ↓
46:04

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 ↓

slash1s

28,052 Aufrufe • vor 3 Monaten

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 Aufrufe • vor 3 Monaten

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 ↓
43:30

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 Aufrufe • vor 2 Monaten

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):
1:27

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):

Sahn Lam

65,209 Aufrufe • vor 2 Jahren

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.
1:05:58

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

253,218 Aufrufe • vor 4 Monaten

you numbered the steps so it could not get lost it does not get lost that list was written for a model that wandered, and this one plans better than the list does, so every number you added is a place where it is no longer allowed, to be smarter than you state the goal, the constraints, and how you will know it worked keep the numbers only where exactly one sequence is safe, which is deletes, auth and compliance the procedure felt like rigour it is a cage built to the dimensions of a model that is not in the room
1:21

you numbered the steps so it could not get lost it does not get lost that list was written for a model that wandered, and this one plans better than the list does, so every number you added is a place where it is no longer allowed, to be smarter than you state the goal, the constraints, and how you will know it worked keep the numbers only where exactly one sequence is safe, which is deletes, auth and compliance the procedure felt like rigour it is a cage built to the dimensions of a model that is not in the room

Lagosaur

14,857 Aufrufe • vor 27 Tagen

Orchestrators vs. Graphs, clearly explained! orchestrators are great, and everyone builds one first. here is the ceiling: an orchestrator sits above the work and routes every message. five agents report to it. it reads all five. it decides what each one does next, and reads all five replies. that is ten trips through one context, and by the fifth agent that context has read four reports, five instructions and its own reasoning about all of them. Graph engineering fixes this by removing the seat: not a better router, but no router at all. you need both, and here is the sentence that resolves the whole confusion: an orchestrator sits above the work and holds all of it. a graph is the shape of the work, and holds none of it. ↳ above the work: one context that has to see everything before anything ships ↳ inside the work: a splitter that hands out and lets go, and a merge that reads nothing Prompts → Context → Harness → Loops → Graphs the coordination did not disappear. it moved into the edges, where it costs nothing and cannot get tired. the trick is noticing what you actually built. if one node has to see every result before the run can finish, you did not remove the bottleneck. you hired it, gave it the longest context in the system, and made it the thing you were counting on to stay sharp. one thing to know before you scale it. an orchestrator degrades in the one way nothing catches. ↳ it does not crash, time out or return an error. it stays up and keeps routing ↳ it just starts routing worse, somewhere around the fifth report, and every downstream agent does exactly what it was told that last one catches careful people. you can have perfect isolation on every worker and still have one window quietly drifting at the top, and the traces will all look clean because each worker did its job. and the one that eats whole nights: the merge is where this shows up first. ranking five findings is not judgment, it is a sort. if a model is doing it, you are paying a model to read five reports so it can put them in an order that three lines of code would have got right, and now that model has read everything too. below i have quoted my full guide on graph engineering. it covers the three topologies, the verifier patterns, and where the gate should actually open. save this and read it below ↓
0:47

Orchestrators vs. Graphs, clearly explained! orchestrators are great, and everyone builds one first. here is the ceiling: an orchestrator sits above the work and routes every message. five agents report to it. it reads all five. it decides what each one does next, and reads all five replies. that is ten trips through one context, and by the fifth agent that context has read four reports, five instructions and its own reasoning about all of them. Graph engineering fixes this by removing the seat: not a better router, but no router at all. you need both, and here is the sentence that resolves the whole confusion: an orchestrator sits above the work and holds all of it. a graph is the shape of the work, and holds none of it. ↳ above the work: one context that has to see everything before anything ships ↳ inside the work: a splitter that hands out and lets go, and a merge that reads nothing Prompts → Context → Harness → Loops → Graphs the coordination did not disappear. it moved into the edges, where it costs nothing and cannot get tired. the trick is noticing what you actually built. if one node has to see every result before the run can finish, you did not remove the bottleneck. you hired it, gave it the longest context in the system, and made it the thing you were counting on to stay sharp. one thing to know before you scale it. an orchestrator degrades in the one way nothing catches. ↳ it does not crash, time out or return an error. it stays up and keeps routing ↳ it just starts routing worse, somewhere around the fifth report, and every downstream agent does exactly what it was told that last one catches careful people. you can have perfect isolation on every worker and still have one window quietly drifting at the top, and the traces will all look clean because each worker did its job. and the one that eats whole nights: the merge is where this shows up first. ranking five findings is not judgment, it is a sort. if a model is doing it, you are paying a model to read five reports so it can put them in an order that three lines of code would have got right, and now that model has read everything too. below i have quoted my full guide on graph engineering. it covers the three topologies, the verifier patterns, and where the gate should actually open. save this and read it below ↓

Hanako

43,078 Aufrufe • vor 4 Tagen

AI is not trying to teach you. It is not trying to tell you the truth. It is trying to trick you. ChatGPT takes everything on the internet. Finds the most popular answer. And presents it in a way that makes you think it is talking directly to you. It is a magic trick. The same magic trick that worked in 1966 when MIT created a chatbot that said two things: "Tell me more." "This is interesting." And people genuinely believed they were talking to a human. Nothing has changed. The technology is bigger. The trick is the same. AI does not know what it is saying. It cannot judge what it is saying. It is just trying to keep you engaged. That is all it has ever been.
2:10

AI is not trying to teach you. It is not trying to tell you the truth. It is trying to trick you. ChatGPT takes everything on the internet. Finds the most popular answer. And presents it in a way that makes you think it is talking directly to you. It is a magic trick. The same magic trick that worked in 1966 when MIT created a chatbot that said two things: "Tell me more." "This is interesting." And people genuinely believed they were talking to a human. Nothing has changed. The technology is bigger. The trick is the same. AI does not know what it is saying. It cannot judge what it is saying. It is just trying to keep you engaged. That is all it has ever been.

Predictive History

20,184 Aufrufe • vor 4 Monaten