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HARVARD HAS A FULL 53-MIN GIT LECTURE FROM DAVID MALAN BECAUSE 90% OF NEW DEVELOPERS STILL DON'T KNOW WHAT A COMMIT ACTUALLY IS 53 minutes of no-nonsense version control from the instructor whose course became the largest class in Harvard history. -> The moment you watch it, you realize...

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slash1s

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253,313 次观看 • 3 个月前 •via X (Twitter)

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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.
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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

252,969 次观看 • 3 个月前

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 data model underneath -- the thing that makes every command finally make sense. -> The moment it clicks, git stops being scary magic. You stop memorizing "The incantation that fixed it last time" and start actually knowing what's happening. Most people learn just enough git to not get fired. Four commands, blind faith, and a prayer before every merge. In 2026 that's not enough anymore -> git is the literacy test for being in the room, and "I'll just reclone it" is the fastest way to look junior. An AI agent will branch, commit and rebase faster than you can read. When it tangles the history, untangling it runs on understanding the model MIT teaches in this one hour. Anyone can run git push. The person who understands the graph underneath is the one who saves the repo when it breaks. Bookmark & Watch it ↓
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459,113 次观看 • 3 个月前

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A DEVELOPER PROVED YOU CAN FIND THE EXACT COMMIT THAT BROKE YOUR CODE IN A HISTORY OF 10,000 -- IN ABOUT 13 STEPS, AUTOMATICALLY.. 33 minutes from a Google engineer on git bisect: the built-in command that binary-searches your entire history to hunt down the one commit that introduced a bug. -> The moment it lands, "When did this break?" stops being an afternoon of guessing. You hand git a good commit, a bad one, and a test and it finds the culprit while you watch. Most people debug a regression by reading diffs by hand, blaming the obvious file, and hoping. Bisect doesn't hope. It cuts the search in half, then in half again, until only the guilty commit is left standing. Reading history by hand was never the skill -> letting git do the binary search for you is. And when an AI agent dumps hundreds of commits into your repo and one quietly breaks production, bisect is what finds the needle without you reading a single line. The bug isn't hiding. It's sitting in one exact commit. Most people just never learned to make git point at it. Bookmark & Watch it today ↓

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MICROSOFT PUT THE ENTIRE SOURCE CODE OF WINDOWS INTO A SINGLE GIT REPO -- 300 GIGABYTES, 3.5 MILLION FILES AND MADE IT CLONE IN SECONDS 31 minutes from the Microsoft engineer who actually did it, bending the tool you use for a 50-file side project to hold the biggest codebase on the planet. -> The moment it lands, every excuse dies. You've heard "Git doesn't scale, use something else" your whole career. They ran git status on the largest repo alive and it came back instantly. The secret wasn't a different tool. It was understanding what git actually stores and realizing you never need the whole thing on disk. Pull only the files you touch. Ignore the 3.4 million you never will. Knowing the commands was never the ceiling -> understanding how git stores and moves things is what lets you do what everyone swears is impossible. And as AI agents spin up repos that balloon overnight, knowing how git scales is what keeps you from drowning in your own history. Everyone treats git like it maxes out at a hobby project. One team quietly proved it can hold an operating system. Bookmark & Watch it today ↓

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237,718 次观看 • 3 个月前

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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 rods right in front of you. -> The moment he snaps the first pieces together, Git stops being scary command-line magic and becomes what it really is: a chain of tiny objects pointing at each other. Branches, merges, rebase, the staging area -- every concept that's ever burned you at 2am -- he rebuilds with toys until a four year old could follow. He calls Git a two-trick pony. After this you'll see exactly why. Memorizing commands was never the skill -> holding the graph in your head is. And with an AI agent now committing and rebasing on your machine all day, that mental model is the only thing between you and a history you can't read. Scroll the comments and you'll see the same thing over and over: this is the talk that finally made Git click and made people the one their whole team comes to when it breaks. Bookmark & watch it today. It's the 1.5 hours that pays you back for the rest of your career ↓

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AN MIT RESEARCHER PROVED GIT ISN'T HARD BECAUSE YOU'RE BAD AT IT -- IT'S HARD BECAUSE IT WAS DESIGNED THAT WAY 27 minutes from a PhD researcher in MIT's Software Design Group, using actual design theory to show why the tool that confuses everyone confuses everyone for a reason. -> The moment it lands, years of feeling stupid evaporate. The gap between what git's commands say and what they actually do was never in your head. It's baked into the tool. He maps the difference between what you think a command does and what git really does underneath. Once you see that gap, the confusion finally has a name and it stops being yours to carry. Struggling with git was never a skills issue -> it's a design issue, and knowing where the model lies to you is what turns panic into control. And as AI agents fire off commits and rebases you didn't write, the person who understands where git misleads is the one who untangles the mess. You were never bad at git. You were just never shown where it was built to trip you. Bookmark & Watch it today ↓

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138,043 次观看 • 3 个月前

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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 • 2 个月前

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 ↓
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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 ↓

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28,052 次观看 • 3 个月前

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 ↓
54:10

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 ↓

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10,864 次观看 • 3 个月前

TWO ENGINEERS SHOWED THE GIT TRICKS THAT MAKE PEOPLE THINK YOU'RE A WIZARD -- THE ONES 95% OF DEVELOPERS HAVE NEVER ONCE TOUCHED 42 minutes from Johan Abildskov and Jan Krag, bending git with custom configs, attributes and hooks most people don't even know exist. -> The moment it lands, git stops being four commands you repeat in fear. The same tool you've used for years turns out to have a whole layer built to bend to you. Hooks that run your checks before a bad commit ever lands. Attributes that end the "it works on my machine" merge wars. Config that makes the painful parts just stop happening. Memorizing commands was never the ceiling -> shaping git to do the work for you is. And while everyone else fights the tool by hand, the person who set it up right is shipping clean three times faster. Most people use 5% of git and call it a day. This is the other 95% nobody showed you. Bookmark it and Watch today ↓
42:40

TWO ENGINEERS SHOWED THE GIT TRICKS THAT MAKE PEOPLE THINK YOU'RE A WIZARD -- THE ONES 95% OF DEVELOPERS HAVE NEVER ONCE TOUCHED 42 minutes from Johan Abildskov and Jan Krag, bending git with custom configs, attributes and hooks most people don't even know exist. -> The moment it lands, git stops being four commands you repeat in fear. The same tool you've used for years turns out to have a whole layer built to bend to you. Hooks that run your checks before a bad commit ever lands. Attributes that end the "it works on my machine" merge wars. Config that makes the painful parts just stop happening. Memorizing commands was never the ceiling -> shaping git to do the work for you is. And while everyone else fights the tool by hand, the person who set it up right is shipping clean three times faster. Most people use 5% of git and call it a day. This is the other 95% nobody showed you. Bookmark it and Watch today ↓

slash1s

105,656 次观看 • 3 个月前

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 ↓
1:08:17

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 次观看 • 3 个月前

Excited to announce Viktor in Microsoft Teams. This week we crossed $20M in annualized revenue run rate. In Slack. One app, no sales team, no rollout. Now Viktor goes where the rest of the working world actually is. 320 million people work in Microsoft Teams. The biggest org chart on earth – departments, approval chains, the manager and the manager's manager. Here's what we actually built for them: the first AI where the barrier to entry is zero. You don't learn it. You don't prompt it. You don't even have to understand what AI can do. You Mention Viktor like a coworker, and the finished work comes back. In fact, you don't even need to mention Viktor. Viktor makes everyone AI-native. No course, no manual, no learning curve – the value comes to you, you don't reach for it. That's the mission: bring our rebellious optimist to the people who need him most. The operators and managers buried inside big companies. The frontline. The ones who were never shown what this could actually do for them – until today. Workspaces are where agents belong. Not apps. Viktor is live in Microsoft Teams. $100 in credits to start, no card. The AI for the rest of us – now where the rest of us report to someone.
1:21

Excited to announce Viktor in Microsoft Teams. This week we crossed $20M in annualized revenue run rate. In Slack. One app, no sales team, no rollout. Now Viktor goes where the rest of the working world actually is. 320 million people work in Microsoft Teams. The biggest org chart on earth – departments, approval chains, the manager and the manager's manager. Here's what we actually built for them: the first AI where the barrier to entry is zero. You don't learn it. You don't prompt it. You don't even have to understand what AI can do. You Mention Viktor like a coworker, and the finished work comes back. In fact, you don't even need to mention Viktor. Viktor makes everyone AI-native. No course, no manual, no learning curve – the value comes to you, you don't reach for it. That's the mission: bring our rebellious optimist to the people who need him most. The operators and managers buried inside big companies. The frontline. The ones who were never shown what this could actually do for them – until today. Workspaces are where agents belong. Not apps. Viktor is live in Microsoft Teams. $100 in credits to start, no card. The AI for the rest of us – now where the rest of us report to someone.

Fryd Wiatrowski

691,628 次观看 • 2 个月前

A LINUX KERNEL DEVELOPER PROVED THE THING YOU PUSH CODE TO IS SECRETLY A DATABASE THAT CAN VERSION ALMOST ANYTHING AND THAT MOST DEVS HAVE ONLY EVER TOUCHED A TENTH OF IT 42 minutes from Josh Triplett -- a longtime Linux kernel and Debian developer -- showing that Git is a general-purpose, tamper-evident versioning engine that just happens to be famous for code. -> The moment it clicks, Git stops being "Where my code lives" and becomes what it really is underneath: a content-addressable store that can version almost anything -- your configs, your notes, your servers' state, entire datasets. People run whole wikis on it. They version their entire machine's configuration with it. They ship websites by pushing to it. They track data too big to email. None of it is a hack -- it's the same handful of objects you already use for code, pointed somewhere new. Treating Git as a code-only tool was never the ceiling -> it's a versioning engine for anything, and the people who see that automate what the rest of the team still does by hand. And as AI agents start spitting out not just code but configs, docs and data, the one system that can version and audit all of it at once is already sitting on your machine. You learned five commands to survive. This is the talk that shows you were standing on top of a database the whole time. It changes what you think the tool is even for. Bookmark & Watch it today ↓
42:24

A LINUX KERNEL DEVELOPER PROVED THE THING YOU PUSH CODE TO IS SECRETLY A DATABASE THAT CAN VERSION ALMOST ANYTHING AND THAT MOST DEVS HAVE ONLY EVER TOUCHED A TENTH OF IT 42 minutes from Josh Triplett -- a longtime Linux kernel and Debian developer -- showing that Git is a general-purpose, tamper-evident versioning engine that just happens to be famous for code. -> The moment it clicks, Git stops being "Where my code lives" and becomes what it really is underneath: a content-addressable store that can version almost anything -- your configs, your notes, your servers' state, entire datasets. People run whole wikis on it. They version their entire machine's configuration with it. They ship websites by pushing to it. They track data too big to email. None of it is a hack -- it's the same handful of objects you already use for code, pointed somewhere new. Treating Git as a code-only tool was never the ceiling -> it's a versioning engine for anything, and the people who see that automate what the rest of the team still does by hand. And as AI agents start spitting out not just code but configs, docs and data, the one system that can version and audit all of it at once is already sitting on your machine. You learned five commands to survive. This is the talk that shows you were standing on top of a database the whole time. It changes what you think the tool is even for. Bookmark & Watch it today ↓

slash1s

385,976 次观看 • 3 个月前

Andrej Karpathy spent 70 minutes breaking down how top AI users actually work with LLMs. The reality is simpler than people expect. You tell the model what you want in plain language and let it run. No 40-line system prompts. No secret tricks. By 2026 the engineer who writes off LLMs loses to the junior who just set one up properly. 70 minutes. Free. A rare straight look from an OpenAI co-founder. Bookmark it and watch.
1:10:03

Andrej Karpathy spent 70 minutes breaking down how top AI users actually work with LLMs. The reality is simpler than people expect. You tell the model what you want in plain language and let it run. No 40-line system prompts. No secret tricks. By 2026 the engineer who writes off LLMs loses to the junior who just set one up properly. 70 minutes. Free. A rare straight look from an OpenAI co-founder. Bookmark it and watch.

Andrew

351,823 次观看 • 2 个月前

OpenClaw is the fastest growing open-source project in history, but it can be a pain to set up. We (Aethir ) built Aethir Claw so you can deploy your AI agent on our decentralized VPS infrastructure in minutes. No DevOps degree required. Hit play. I'll walk you through the full onboarding, start to finish in under 5 mins! This is just the beginning...
6:00

OpenClaw is the fastest growing open-source project in history, but it can be a pain to set up. We (Aethir ) built Aethir Claw so you can deploy your AI agent on our decentralized VPS infrastructure in minutes. No DevOps degree required. Hit play. I'll walk you through the full onboarding, start to finish in under 5 mins! This is just the beginning...

Mark

43,140 次观看 • 5 个月前

Joe Blitzstein, Harvard statistics professor: "Jane Street pays $600K for people who can do one thing in their head: compute the expected value of a bet before they take it. I teach it free at Harvard. skip it and you're the casino's favorite customer." this free lecture holds the entire "edge" every casino and every fund quietly runs on, and the man teaching it put his whole Harvard probability course online for free, where millions have watched it. at the board it's simple. expected value is every outcome times its probability, added up into one number that tells you what a bet is worth on average. the roulette wheel sits at minus 5.26 percent, so every dollar you push across the table is worth about 94 cents back to you and the rest to the house. it never changes and it never has to. that's the whole "edge", minus the marketing. expectation goes back to Pascal, Fermat and Huygens in the 1650s. it has been free for almost 400 years. same point as my casino piece above: the house wins because its number is positive and yours is negative, trade after trade. the calculation is free and every fund runs it on every position. what they cannot sell you is the honesty to compute your real edge instead of the one you wish you had. that is the number that actually decides who goes broke, and no course can make you face it.
50:22

Joe Blitzstein, Harvard statistics professor: "Jane Street pays $600K for people who can do one thing in their head: compute the expected value of a bet before they take it. I teach it free at Harvard. skip it and you're the casino's favorite customer." this free lecture holds the entire "edge" every casino and every fund quietly runs on, and the man teaching it put his whole Harvard probability course online for free, where millions have watched it. at the board it's simple. expected value is every outcome times its probability, added up into one number that tells you what a bet is worth on average. the roulette wheel sits at minus 5.26 percent, so every dollar you push across the table is worth about 94 cents back to you and the rest to the house. it never changes and it never has to. that's the whole "edge", minus the marketing. expectation goes back to Pascal, Fermat and Huygens in the 1650s. it has been free for almost 400 years. same point as my casino piece above: the house wins because its number is positive and yours is negative, trade after trade. the calculation is free and every fund runs it on every position. what they cannot sell you is the honesty to compute your real edge instead of the one you wish you had. that is the number that actually decides who goes broke, and no course can make you face it.

Voltex

388,503 次观看 • 1 个月前

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 次观看 • 2 年前

"The model isn't the point. The understanding is." coatue.thomas joined Coatue in 2003 with no formal analyst training. One rule that is still a non-negotiable: build every cell of the model yourself. No inherited spreadsheets. No shortcuts. The only way to actually know what you own. TBPN
0:52

"The model isn't the point. The understanding is." coatue.thomas joined Coatue in 2003 with no formal analyst training. One rule that is still a non-negotiable: build every cell of the model yourself. No inherited spreadsheets. No shortcuts. The only way to actually know what you own. TBPN

COATUE

135,090 次观看 • 4 个月前