Shadowing Practice: The hottest programming skill in 2026 - Learn English Speaking with Video

Systems thinking.

That's it.

You can end the video right now.

Every programming era had its own hot skill,

whether you were writing Java in the 90s,

PHP in the 2000s, Ruby in 2010,

and in 2026, aside from token maxing, it's systems thinking.

But what exactly is systems thinking?

It's understanding how each part of a system interacts over time.

Think of it like this.

You work at the Krusty Krab,

you can make a banger Krabby Patty,

but that's only one feature of the Krusty Krab.

How do they scale to a thousand Krabby Patties per hour.

What happens when the fryer breaks?

Or worse, Patrick is your waiter.

Systems thinking has its roots in biology,

and it can be applied to many different fields.

Supply chain management, market dynamics,

traffic, and of course, software engineering.

Nowadays, anytime we hear systems and programming,

we immediately think of system design interview questions.

But that's only a part of it.

Systems thinking and software engineering have an old relationship,

and it's only getting more prominent as time passes.

And I have some charts to back it A16Z published this graph showing software jobs are going up.

I personally hate these graphs.

Not because I'm Mr. Dario,

I was meant to replace you 24 months ago, agentic pilled.

But I hate seeing these graphs because it doesn't clarify what kind of software jobs are going up.

Do you really think the demand for Pascal developers is going up?

Really, bro?

Thankfully, there's always a programmer with some spare time and a banger blog that did the research for me.

This graph shows off the number of job postings by each job title.

Look at the top three.

They all develop carpal tunnel, but also systems.

Look at machine learning engineers.

They use tools like PyTorch, Kafka, Kubernetes.

They use these tools to build stuff like fraud detection algorithms,

which can analyze millions of transactions so your credit card isn't used in Belarus to buy an iPhone.

The fraud detection algorithm is a system.

Similarly, data engineers and backend engineers,

when they're not gluing APIs together, they're building systems.

The ability to think in systems is so hot right now.

Anthropic has a section on their careers page just for infrastructure software engineers.

Even the latest jobs coming out of the GPT wrapper factories.

They're about making the use of LLMs more efficient, which is a system.

Hopefully I've sold you on the importance of systems thinking,

so now you can go learn about it.

Learning systems is harder than anything else in programming,

since you can't just replicate the scale of millions of users.

Except, there is one way.

Playing Factorio.

I'm not even kidding.

Factorio is a game where you learn how to build systems.

For those that are unaware,

the premise of the game is that you crash land on a planet,

you need to build a rocket to escape.

To build that rocket, you need to get resources.

To get those resources, you need to build systems and get really good at building them.

Factorio is the most underrated way to learn about large-scale systems and actually get some experience,

because it teaches you about impact,

bottlenecks, and how to continuously improve a large-scale system.

There's this amazing video by Tony Zhu that goes over the relationship between Factorio and software engineering.

Another unconventional way of learning about systems thinking is by watching Kevin Fang and reading the Cloudflare outage postmortems.

If you want a more conventional method,

you could always read this excellent book called Thinking in Systems by Donella Meadows.

Now if you're absolutely insistent on building a project,

you can look up public repositories of massive datasets and use that to stress test your project,

whether it's by benchmarking how quickly you read and write to the database,

or seeing if your front-end code can actually handle that much data.

Fundamentally, systems have always been a part of software engineering,

and it is the strongest skill you can learn right now,

whether you're into back-end, front-end, or even game dev.

Understanding how something as granular as your code fits into the bigger picture will always be valuable.

And hey, at least you have an excuse to get good at Factorio now.

You'll also get more time to play Factorio by using the sponsor of today's video,

Convex, the backend platform that keeps your app in sync.

In modern programming, you're not really just programming anymore.

You're spending half your time coordinating between your frontend,

backend, database, and whatever other shenanigans you have going on.

I'm not judging, but essentially you've been reduced to the dude in front of the orchestra with the pointy stick.

Not anymore though, Convex finally lets you build again.

Instead of gluing services together,

your backend is just TypeScript functions.

You write functions to read and write data,

and Convex handles a database,

APIs, and syncing between everything automatically.

And look at this sync bro, so smooth, so crispy.

And is that real-time updates between two users?

Convex fits right into the TypeScript ecosystem you're already using,

and you can also use it it with a few friendly faces.

No more raw dogging squeal,

no more glue engineering, no more cash invalidation,

and no more shadowboxing with your app to keep it in sync.

You owe it to yourself to go to bigboxsweet.dev slash convex.

✨ Recomendar Video

262 oraciones

Vocabulario y notas de pronunciación para esta lección

Esta lección de conversación de nivel C1 se basa en el vídeo “The hottest programming skill in 2026”. Las palabras que más se repiten: thinking, software, Factorio, build, convex. Este vídeo tiene 96 frases y 909 palabras para practicar shadowing. La parte hablada dura 4:15. El hablante habla rápido, unas 214 palabras por minuto, así que espera sonidos enlazados y reducidos. Solo el 79 % de las palabras está entre las 3.000 más comunes del inglés, por lo que el vocabulario es exigente.

Vocabulario clave de este vídeo

Las 15 palabras más avanzadas del vídeo, con su pronunciación y significado:

Palabra	Pronunciación	Significado
convex adjetivo	/ˈkɑn.vɛks/	convexo
graph sustantivo	/ɡɹæf/	gráfico, gráfica
glue sustantivo	/ɡlu/	cola, goma
banger sustantivo	/ˈbæŋ.ə/	temazo, rolona
algorithm sustantivo	/ˈælɡəɹɪðm̩/	algoritmo
detection sustantivo	/dɪˈtɛk.ʃən/	detección
anthropic adjetivo	/ænˈθɹɒp.ɪk/	antrópico
bottleneck sustantivo		cuello de botella
crispy adjetivo	/ˈkɹɪs.pi/	crujiente
granular adjetivo	/ˈɡɹæn.jə.lə(ɹ)/	granuloso
outage sustantivo	/ˈaʊ.tɪd͡ʒ/	apagón, corte
pointy adjetivo	/ˈpɔɪnti/	puntudo, puntiagudo
repository sustantivo	/ɹɪˈpɒz.ɪ.t(ə.)ɹɪ/	repositorio
shenanigans sustantivo	/ʃɪˈnæn.ɪ.ɡənz/	ocurrencias, travesuras
squeal verbo	/skwil/	chillar

Phrasal verbs que vas a escuchar

Palabra	Pronunciación	Significado
go up verbo		subir
go over verbo		sentar, pasar
look up verbo	/ˌlʊk ˈʌp/	mejorar
show off verbo		chulear, lucir

Gramática en este vídeo

Las estructuras que más usa el hablante, con las palabras exactas del vídeo:

Estructura	En el vídeo
Present perfect have/has + participio pasado — una acción pasada que sigue importando ahora	I've sold · have always been · you've been reduced
Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace	can be applied · was meant · you've been reduced

Pronunciación a tener en cuenta

El hablante usa 17 contracciones y formas reducidas, como you're, I'm, they're. Dilas en su forma corta, tal como las oyes.

Los sonidos de “th”: algorithm /ˈælɡəɹɪðm̩/, anthropic /ænˈθɹɒp.ɪk/
Los sonidos de “sh” y “zh”: detection /dɪˈtɛk.ʃən/, invalidation /ɪnˌvæl.əˈdeɪ.ʃən/, shenanigans /ʃɪˈnæn.ɪ.ɡənz/, benchmark /ˈbɛn(t)ʃmɑːk/
Palabras largas — cuida el acento: invalidation /ɪnˌvæl.əˈdeɪ.ʃən/, repository /ɹɪˈpɒz.ɪ.t(ə.)ɹɪ/, shenanigans /ʃɪˈnæn.ɪ.ɡənz/, underrated /ʌn.dɚˈɹeɪ.təd/, ecosystem /ˈikoʊˌsɪstəm/

Sonidos difíciles para hispanohablantes:

s + consonante al inicio — sin añadir una “e” delante: squeal /skwil/, sponsor /ˈspɒn.səː/
/v/ — no es /b/: los dientes tocan el labio inferior: convex /ˈkɑn.vɛks/, invalidation /ɪnˌvæl.əˈdeɪ.ʃən/
/z/ — sonora, no /s/: repository /ɹɪˈpɒz.ɪ.t(ə.)ɹɪ/, shenanigans /ʃɪˈnæn.ɪ.ɡənz/, analyze /ˈæn.əˌlaɪz/

Cómo practicar con este vídeo

Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
Empieza a velocidad 0,75×, haz shadowing frase por frase y vuelve a la velocidad normal cuando te resulte fácil.
Grábate y compara con el original, prestando atención a palabras como convex, graph, glue.

¿Qué es la Técnica de Shadowing?

Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.

Técnica de shadowing: lee la guía completa paso a paso →

Shadowing Practice: The hottest programming skill in 2026 - Learn English Speaking with Video

Don't choose the wrong tech career in 2026

8 Most Important System Design Concepts You Should Know

Why Coding Agents Keep Making Your Codebase Worse

80% of programmers are NOT happy… why?

Is Embedded Systems Still a Good Career in 2026?

how AI broke the SWE Career Ladder

The End of Human Mathematics? AI's Recent Breakthrough -- And What's Next

8 New CSS, JS and HTML Features You Should Know

New Skills! v1.3 brings /pr, /implement-spec, and /retro

The Engineering that Runs the Digital World 🛠️⚙️💻 How do CPUs Work?

AI biết code, vì sao vẫn phải học lập trình? | đi-code ep 35

How demand for workforce skills will change with automation: A minute with MGI