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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...

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slash1s

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105,823 次观看 • 3 个月前 •via X (Twitter)

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23 条评论

Chelu Martin 的头像
Chelu Martin3 个月前

If you want to see the full video at your pace, with captions and translated... You have it here

HurpDurp 🟦 的头像
HurpDurp 🟦3 个月前

ok but can you please not let AI write your crap texts? This reads so unnatural

Ridark 的头像
Ridark3 个月前

Started looking forward to release dates each week

slash1s 的头像
slash1s3 个月前

😉

shmidt 的头像
shmidt3 个月前

git hooks are genuinely underrated, gonna watch this

rari 的头像
rari3 个月前

git configs are one of those quiet edges that compound every week

Hussain Hashim | Building SundayBack 的头像
Hussain Hashim | Building SundayBack3 个月前

@slash1sol git hooks are my secret weapon. automating tedious stuff saves so much time. gotta check out those configs and attributes too!

0xbobaa 的头像
0xbobaa3 个月前

I'll save this lecture right now

Antid 的头像
Antid3 个月前

bookmarked the talk

Gipp 🦅 的头像
Gipp 🦅3 个月前

This is a really big trick

cristal💎 的头像
cristal💎3 个月前

git hooks are lowkey a total lifesaver

starmex 的头像
starmex3 个月前

saved, hooks alone change the game

vijn 的头像
vijn3 个月前

but who is this guys ?

leopardracer 的头像
leopardracer3 个月前

thanks for sharing!

Ventry 的头像
Ventry3 个月前

this is definitely worth saving

Bizzi 的头像
Bizzi3 个月前

Guys showed me smth new

Nekt0 的头像
Nekt03 个月前

Top bro

sandybrige 的头像
sandybrige3 个月前

You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs:

Insomnia 的头像
Insomnia3 个月前

just saved this lecture bro

Ken Hadden 的头像
Ken Hadden3 个月前

BOSS: Wait, you guys are still messing with Git? Just tell your AI agent to do it for you. Right?

未知 的头像
未知3 个月前

判断一个人不要听他说什么，要看他做什么。 「TWO ENGINEERS SHOWED THE GIT TRICKS THAT MAKE PEOPLE THINK Y...」

Yarchi 的头像
Yarchi3 个月前

most people fighting git by hand never knew this layer existed

cvxv666 的头像
cvxv6663 个月前

practical tips from true industry veterans - love it

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slash1s

28,133 次观看 • 4 个月前

Harness vs. Graphs, clearly explained! a harness is great, and most people think it is the whole thing: retries, timeouts, a sandbox, a log, the context it assembles before every call. all of that is real work, and all of it wraps exactly one call. run it a hundred times and you have one call, made very safely, a hundred times. Graph engineering fixes this by moving the decision up a layer: not how safely one call is made, but which calls exist to be made at all. you need both, and here is the sentence that resolves the whole confusion: the harness is everything around one call. the graph is everything between them. ↳ around one call: retry, timeout, sandbox, log, assemble the context, hand back a result ↳ between calls: split, fan out, merge, gate, send back Prompts → Context → Harness → Loops → Graphs the harness does not go away when you build a graph. it moves under each node, and now there are five of them, each wrapping a call you would never have made by hand. the trick is knowing which layer a failure belongs to. turn a piece off and run it again. if the call still works, it was the harness. if the wrong step runs at all, it was the graph. people spend weeks hardening a harness around a node that should not have existed. one thing to know before you scale it. most of what people call their agent is a harness with a chat box on it. ↳ it retries, it times out, it logs, it assembles context, it holds one call up beautifully ↳ it has never once decided that a second call should exist, and that is the entire difference that last one catches careful people. a harness that never fails is not evidence the system is right. it is evidence one call went well, which is the smallest possible claim. and the one that eats whole nights: a harness cannot save you from the wrong step running. you can retry a bad decision three times with a clean log and perfect isolation, and all you bought was three copies of it. 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 ↓
0:53

Harness vs. Graphs, clearly explained! a harness is great, and most people think it is the whole thing: retries, timeouts, a sandbox, a log, the context it assembles before every call. all of that is real work, and all of it wraps exactly one call. run it a hundred times and you have one call, made very safely, a hundred times. Graph engineering fixes this by moving the decision up a layer: not how safely one call is made, but which calls exist to be made at all. you need both, and here is the sentence that resolves the whole confusion: the harness is everything around one call. the graph is everything between them. ↳ around one call: retry, timeout, sandbox, log, assemble the context, hand back a result ↳ between calls: split, fan out, merge, gate, send back Prompts → Context → Harness → Loops → Graphs the harness does not go away when you build a graph. it moves under each node, and now there are five of them, each wrapping a call you would never have made by hand. the trick is knowing which layer a failure belongs to. turn a piece off and run it again. if the call still works, it was the harness. if the wrong step runs at all, it was the graph. people spend weeks hardening a harness around a node that should not have existed. one thing to know before you scale it. most of what people call their agent is a harness with a chat box on it. ↳ it retries, it times out, it logs, it assembles context, it holds one call up beautifully ↳ it has never once decided that a second call should exist, and that is the entire difference that last one catches careful people. a harness that never fails is not evidence the system is right. it is evidence one call went well, which is the smallest possible claim. and the one that eats whole nights: a harness cannot save you from the wrong step running. you can retry a bad decision three times with a clean log and perfect isolation, and all you bought was three copies of it. 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

51,536 次观看 • 26 天前

Anthropic engineers finally showed how they actually use Claude Code internally 31 minutes of internal workflow that most Claude users will never see on their own here's what they cover: > how to set up project context files the right way > custom commands that save hours of repeated work > hooks that make Claude behave exactly how you need > subagents and how to actually spec them properly "your agent isn't the problem, your spec is" the people who understand how Claude Code actually works inside Anthropic are shipping things everyone else thinks requires a whole team that's exactly why I put together a breakdown of Claude features most people have never discovered you can find it below
31:22

Anthropic engineers finally showed how they actually use Claude Code internally 31 minutes of internal workflow that most Claude users will never see on their own here's what they cover: > how to set up project context files the right way > custom commands that save hours of repeated work > hooks that make Claude behave exactly how you need > subagents and how to actually spec them properly "your agent isn't the problem, your spec is" the people who understand how Claude Code actually works inside Anthropic are shipping things everyone else thinks requires a whole team that's exactly why I put together a breakdown of Claude features most people have never discovered you can find it below

Anatoli Kopadze

311,928 次观看 • 4 个月前

A DEVELOPER PROVED THAT MOST OF THE CLASSES YOU WRITE SHOULD NEVER HAVE BEEN CLASSES AT ALL 27 minutes from Jack Diederich, a Python core developer, on how much of your code is just a function wearing a costume. -> The moment it lands, the rule is brutal: if a class has two methods and one is __init__, you meant to write a function. Most people add structure to feel like real engineers. It just adds weight no one ever needed. Writing more code was never the skill -> writing less of it is. And when an AI agent happily generates ten classes for a job that needed three lines, the person who knows what to delete is the one who ships something clean. Anyone can add abstraction. Knowing when not to is the whole job. Bookmark it and Watch ↓
27:10

A DEVELOPER PROVED THAT MOST OF THE CLASSES YOU WRITE SHOULD NEVER HAVE BEEN CLASSES AT ALL 27 minutes from Jack Diederich, a Python core developer, on how much of your code is just a function wearing a costume. -> The moment it lands, the rule is brutal: if a class has two methods and one is __init__, you meant to write a function. Most people add structure to feel like real engineers. It just adds weight no one ever needed. Writing more code was never the skill -> writing less of it is. And when an AI agent happily generates ten classes for a job that needed three lines, the person who knows what to delete is the one who ships something clean. Anyone can add abstraction. Knowing when not to is the whole job. Bookmark it and Watch ↓

slash1s

269,515 次观看 • 3 个月前

Peter Jackson talks about AI in Hollywood. Calls it “a tool” like stop-motion or CGI before and what ultimately matters is “imagination, originality” of whoever uses the tool: “I think AI — used in the right way — is a tool like any other tool. [The original] King Kong…was stop-motion and done by a person moving a rubber creature. Why shouldn't somebody on a computer using AI software be able to create their own imagery? They should. It's a tool. It's no different from many other tools that have existed over the years. But the other side of it is that it's always going to come down to the imagination and originality of the person feeding the instructions into the AI program. It's not that you're going to type in an instruction and it's going to generate your shot, and that's that. The question is: is it actually interesting? Is it funny? Is it imaginative? And are you going to stitch it together to make a narrative, a story? Some people will make really great films that way. Some people will do exactly the same process and their film will be crap, just like in the normal film industry. Whether it's AI or anything else, it comes down to whether the person behind it — or the people behind it — have originality, imagination, and an ability to entertain people.”
1:32

Peter Jackson talks about AI in Hollywood. Calls it “a tool” like stop-motion or CGI before and what ultimately matters is “imagination, originality” of whoever uses the tool: “I think AI — used in the right way — is a tool like any other tool. [The original] King Kong…was stop-motion and done by a person moving a rubber creature. Why shouldn't somebody on a computer using AI software be able to create their own imagery? They should. It's a tool. It's no different from many other tools that have existed over the years. But the other side of it is that it's always going to come down to the imagination and originality of the person feeding the instructions into the AI program. It's not that you're going to type in an instruction and it's going to generate your shot, and that's that. The question is: is it actually interesting? Is it funny? Is it imaginative? And are you going to stitch it together to make a narrative, a story? Some people will make really great films that way. Some people will do exactly the same process and their film will be crap, just like in the normal film industry. Whether it's AI or anything else, it comes down to whether the person behind it — or the people behind it — have originality, imagination, and an ability to entertain people.”

Bearly AI

43,816 次观看 • 4 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

435,509 次观看 • 3 个月前

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 why "I'll just push to main" is the fastest way to get fired in your first month. Every junior engineer in 2026 is expected to handle Git on day one - no excuses, no Stack Overflow, no AI hand-holding. Git isn't a "senior dev thing" anymore -> it's the literacy test for being in the room. The agent can ship the feature in 5 minutes. Recovering the repo it broke takes 5 hours - and only if you actually understand what happened. Don't forget to bookmark it.
53:11

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 why "I'll just push to main" is the fastest way to get fired in your first month. Every junior engineer in 2026 is expected to handle Git on day one - no excuses, no Stack Overflow, no AI hand-holding. Git isn't a "senior dev thing" anymore -> it's the literacy test for being in the room. The agent can ship the feature in 5 minutes. Recovering the repo it broke takes 5 hours - and only if you actually understand what happened. Don't forget to bookmark it.

slash1s

253,313 次观看 • 4 个月前