Pratique du Shadowing: The hottest programming skill in 2026 - Apprendre l'anglais à l'oral avec YouTube

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Systems thinking.
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Systems thinking.
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That's it.
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You can end the video right now.
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Every programming era had its own hot skill,
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whether you were writing Java in the 90s,
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PHP in the 2000s, Ruby in 2010,
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and in 2026, aside from token maxing, it's systems thinking.
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But what exactly is systems thinking?
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It's understanding how each part of a system interacts over time.
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Think of it like this.
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You work at the Krusty Krab,
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you can make a banger Krabby Patty,
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but that's only one feature of the Krusty Krab.
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How do they scale to a thousand Krabby Patties per hour.
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What happens when the fryer breaks?
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Or worse, Patrick is your waiter.
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Systems thinking has its roots in biology,
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and it can be applied to many different fields.
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Supply chain management, market dynamics,
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traffic, and of course, software engineering.
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Nowadays, anytime we hear systems and programming,
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we immediately think of system design interview questions.
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But that's only a part of it.
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Systems thinking and software engineering have an old relationship,
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and it's only getting more prominent as time passes.
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And I have some charts to back it A16Z published this graph showing software jobs are going up.
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I personally hate these graphs.
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Not because I'm Mr. Dario,
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I was meant to replace you 24 months ago, agentic pilled.
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But I hate seeing these graphs because it doesn't clarify what kind of software jobs are going up.
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Do you really think the demand for Pascal developers is going up?
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Really, bro?
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Thankfully, there's always a programmer with some spare time and a banger blog that did the research for me.
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This graph shows off the number of job postings by each job title.
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Look at the top three.
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They all develop carpal tunnel, but also systems.
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Look at machine learning engineers.
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They use tools like PyTorch, Kafka, Kubernetes.
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They use these tools to build stuff like fraud detection algorithms,
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which can analyze millions of transactions so your credit card isn't used in Belarus to buy an iPhone.
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The fraud detection algorithm is a system.
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Similarly, data engineers and backend engineers,
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when they're not gluing APIs together, they're building systems.
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The ability to think in systems is so hot right now.
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Anthropic has a section on their careers page just for infrastructure software engineers.
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Even the latest jobs coming out of the GPT wrapper factories.
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They're about making the use of LLMs more efficient, which is a system.
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Hopefully I've sold you on the importance of systems thinking,
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so now you can go learn about it.
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Learning systems is harder than anything else in programming,
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since you can't just replicate the scale of millions of users.
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Except, there is one way.
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Playing Factorio.
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I'm not even kidding.
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Factorio is a game where you learn how to build systems.
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For those that are unaware,
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the premise of the game is that you crash land on a planet,
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you need to build a rocket to escape.
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To build that rocket, you need to get resources.
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To get those resources, you need to build systems and get really good at building them.
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Factorio is the most underrated way to learn about large-scale systems and actually get some experience,
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because it teaches you about impact,
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bottlenecks, and how to continuously improve a large-scale system.
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There's this amazing video by Tony Zhu that goes over the relationship between Factorio and software engineering.
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Another unconventional way of learning about systems thinking is by watching Kevin Fang and reading the Cloudflare outage postmortems.
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If you want a more conventional method,
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you could always read this excellent book called Thinking in Systems by Donella Meadows.
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Now if you're absolutely insistent on building a project,
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you can look up public repositories of massive datasets and use that to stress test your project,
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whether it's by benchmarking how quickly you read and write to the database,
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or seeing if your front-end code can actually handle that much data.
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Fundamentally, systems have always been a part of software engineering,
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and it is the strongest skill you can learn right now,
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whether you're into back-end, front-end, or even game dev.
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Understanding how something as granular as your code fits into the bigger picture will always be valuable.
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And hey, at least you have an excuse to get good at Factorio now.
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You'll also get more time to play Factorio by using the sponsor of today's video,
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Convex, the backend platform that keeps your app in sync.
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In modern programming, you're not really just programming anymore.
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You're spending half your time coordinating between your frontend,
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backend, database, and whatever other shenanigans you have going on.
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I'm not judging, but essentially you've been reduced to the dude in front of the orchestra with the pointy stick.
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Not anymore though, Convex finally lets you build again.
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Instead of gluing services together,
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your backend is just TypeScript functions.
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You write functions to read and write data,
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and Convex handles a database,
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APIs, and syncing between everything automatically.
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And look at this sync bro, so smooth, so crispy.
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And is that real-time updates between two users?
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Convex fits right into the TypeScript ecosystem you're already using,
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and you can also use it it with a few friendly faces.
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No more raw dogging squeal,
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no more glue engineering, no more cash invalidation,
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and no more shadowboxing with your app to keep it in sync.
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You owe it to yourself to go to bigboxsweet.dev slash convex.

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About This Lesson

In this lesson, you will practice your English listening and speaking skills using a transcript related to the programming skill of "systems thinking." As we explore the concept and its applications in various fields, you will enhance your vocabulary, improve your pronunciation, and gain a deeper understanding of how to articulate complex ideas. This practice is ideal for those who want to learn English with YouTube and focus on technical topics related to software engineering and systems design.

Key Vocabulary & Phrases

  • Systems thinking: The ability to understand how different parts of a system interact over time.
  • Supply chain management: The management of the flow of goods and services.
  • Back-end engineers: Programmers who focus on server-side applications and database management.
  • Machine learning: A branch of artificial intelligence that enables systems to learn from data.
  • Fraud detection: Techniques used to identify and prevent unauthorized transactions.
  • APIs: Application Programming Interfaces, crucial for enabling different software programs to communicate.
  • Infrastructure software: Software that provides a foundation for other software applications to run or operate.

Practice Tips

When utilizing this video transcript for practice, consider employing the shadowing technique to improve your spoken English. Here are some tailored tips for effective shadowing:

  • Listen to a section of the video and then pause after each sentence or phrase. Try to repeat it immediately, mimicking the speaker's speed and intonation.
  • Pay attention to the technical vocabulary. Repeat these terms not only for pronunciation but also to internalize their meanings in context.
  • If you find the original speed too fast, use a shadowing app that allows you to adjust the playback speed. Slowing it down can help you catch the nuances of speech.
  • Focus on specific phrases that you find challenging. By shadowing these phrases multiple times, you can improve your fluency and confidence.
  • Practice regularly using this shadowing site for various English videos, refining your skills and building a robust vocabulary across different subjects.

Shadowing this material will not only enhance your speaking abilities but also give you insights into the world of software engineering, empowering you in both language acquisition and technical understanding.

Qu'est-ce que la technique du Shadowing ?

Le Shadowing est une technique d'apprentissage des langues fondée sur la science, développée à l'origine pour la formation des interprètes professionnels. Le principe est simple mais puissant : vous écoutez de l'anglais natif et le répétez immédiatement à voix haute — comme une ombre suivant le locuteur avec un décalage de 1 à 2 secondes. Les recherches montrent une amélioration significative de la précision de la prononciation, de l'intonation, du rythme, des liaisons, de la compréhension orale et de la fluidité.

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