Prática de Shadowing: The hottest programming skill in 2026 - Aprenda a falar inglês com o 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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Por que praticar a fala com este vídeo?

Praticar a fala em inglês utilizando vídeos, como este sobre "a habilidade de programação mais quente em 2026", oferece uma oportunidade única para melhorar suas habilidades de comunicação. Ao falar sobre um tema atual e relevante, você não apenas desenvolve seu vocabulário, mas também aprende a articular ideias complexas de forma coerente. A prática de conversação em inglês se torna mais eficaz ao emparelhar o aprendizado teórico com situações do mundo real, como discutido no vídeo. Isso resulta em uma compreensão mais profunda e uma maior fluência.

Gramática & Expressões em Contexto

O vídeo apresenta algumas estruturas importantes que podem enriquecer seu vocabulário e suas habilidades comunicativas. Aqui estão três exemplos notáveis:

  • ‘Think of it like this’: Uma expressão útil para introduzir ilustrações ou exemplos. Esta construção pode ajudar a clarear ideias em uma conversa.
  • ‘What happens when’: Usado para introduzir situações hipotéticas, permitindo que você pratique a construção de perguntas e cenários.
  • ‘This is only a part of it’: Essa expressão pode ser usada para enfatizar que o que foi discutido é apenas um aspecto de um tópico maior, útil para discussões mais complexas.

A implementação dessas expressões em sua fala diária pode torná-la mais envolvente e dinâmica.

Armadilhas Comuns de Pronúncia

Durante o vídeo, algumas palavras e frases apresentam desafios de pronúncia que podem ser complicados para falantes não nativos. Preste atenção nos seguintes pontos:

  • ‘Systems thinking’: A pronúncia do som duplo 's' pode ser confusa, então pratique a articulação clara do ‘s’ e do ‘th’.
  • ‘Algorithms’: Esta palavra contém uma sequência de sons que pode ser difícil; pratique lentamente, enfatizando cada sílaba.
  • ‘Efficiency’: A acentuação na sílaba correta é crucial. A prática de sombras ("shadow speak") pode ajudá-lo a dominar essa palavra.

Utilizando um site de shadowing, como os que incentivam a prática de conversação em inglês como o “shadowspeak”, você poderá trabalhar essas armadilhas de forma mais eficaz.

O que é a Técnica de Shadowing?

Shadowing é uma técnica de aprendizado de idiomas com base científica, originalmente desenvolvida para o treinamento de intérpretes profissionais. O método é simples, mas poderoso: você ouve áudio em inglês nativo e repete imediatamente em voz alta — como uma sombra seguindo o falante com 1-2 segundos de atraso. Pesquisas mostram melhora significativa na precisão da pronúncia, entonação, ritmo, sons conectados, compreensão auditiva e fluência na fala.

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