ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: I Tested The Viral Reverse Engineering Repo

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182 ประโยค

หากประโยคสั้นหรือยาวเกินไป กดที่ Edit เพื่อปรับแก้

I want you to look at these two apps on my screen.

Now, one of them is a real production application called MongoDB Compass, which is built by MongoDB, is open source and is pretty popular.

Now, another one was a clone of this that I built with AI in 30 minutes and cost me $13.

Now, I built this clone using reverse engineering anything, which I'm going to talk about in this video, but right now, honestly, try to guess.

You can see one app on the side here.

I can click into different database fields, right?

I can see all the different entries, same one over here.

And to be honest with you, even though I know the answer, it's almost impossible for me to tell.

So can you figure out which one is which?

Well, on the right -hand side, we have the clone that I built with AI.

And on the left -hand side, we have the actual MongoDB Compass application.

Now, again, this took me 30 minutes to clone and just $13 in AI credits using a very popular package.

Now we're plug -in called Reverse Engineering Anything, which I want to get into.

So this is the GitHub repo for Reverse Engineer Anything.

Now it's been going viral over the past few days here.

It has over 344 ,000 stars, and basically it does what it says.

It allows you to reverse engineer anything using AI.

And I'm going to explain exactly how it works, but to install it is literally as easy as just copying this GitHub URL,

going to your agent and telling it, Hey, I want you to install reverse engineering anything, add all of the tools to cloud code,

and then it will add the tools and you can start using it to make clones like I just showed you.

So before we go into the details, let me start with how re or reverse engineer anything actually works.

Now when you install an app, you just get the finished product, you don't get the source code.

Now reverse engineering is the process of working out how that finished product works and the tools for doing that, things like decompilers and debuggers,

have been around for years now.

Now they're just really slow and they're pretty difficult to use by hand if you don't know what you're doing.

Now what re does is it sits in the middle.

So on one side, you have your coding agents like CloudCode, Codex, Cursor, whatever.

On the other side, you have these real reverse engineering tools like Gidara, EDA, Frida, GDB, whatever.

I'm probably mispronouncing them because I don't even know how to use them, but I don't have to because I now can use this tool.

Now, basically, you can add them into CloudCode using things like MCP servers, and then we can run all of these on your own computer,

do everything locally, decompile, understand the application, and give you back answers.

And every answer comes back with evidence.

So what it found, where in the app it found it, which tool found it, and what's still unknown.

So the agent doesn't need to guess.

It can actually rebuild something by looking at the exact way that it was already built.

Now, this is really interesting because you don't just need to do this on web apps.

You can do this on really any type of application, even desktop apps that typically are pretty difficult to reverse engineer.

So what can the agent actually do with re?

Well, it gets 207 different tools.

Now, the biggest group, which is 79 of them, is for compiled programs.

So things like reading decompiled code, searching for text, and finding who calls what.

Then there are tools for Android apps, websites, and Electron apps.

There's also live debugging with Frida and GDB, and a whole group for tracking evidence and checking that a rebuild actually matches the original.

Now, one tip if you want to try this here is

that those 207 tool descriptions can add up to around 270 ,000 tokens with every single message.

Now in Claude code, you're actually able to set an enabled tool search to true.

I'm going to show you how to do this in one second.

And that will mean the tools only load when the agent actually needs them.

Now for me that cut each message to about 28 ,000 tokens, which makes a massive difference when you're running this at scale.

Let me quickly show you.

So I'm just going to tell Claude code, this set enabled tool search to true for your tool calls.

And now this way it will start searching through the tools

and figuring out

which one it needs to use rather than looking at all of them every single time it calls an AI model.

So you can see it was able to update this year in our settings.

Now, what I want to do is show you how I ran this,

because again, this is the cloned application that we got here using re which is just absolutely crazy.

And I want to dive more into the mechanics of how this actually works.

So you understand where it will be useful for you.

Okay.

So to run everything that you're about to see,

I actually use today's sponsor open router now it's a really good fit for this because reruns can get extremely expensive.

Now the agent actually loops over and over again

and I've seen people spend you know hundreds of dollars on a single rebuilt product.

So what I wanted to do was compare an expensive model with a cheap one

which I'm going to show you the results of in a minute

and to do that I used open router

which gives me one API key and one endpoint for covering over 400 different models.

Now I simply just pointed cloud code at open router by changing two simple environment variables.

And then after that, I was able to switch to different models and see all of the pricing directly in my dashboard.

So you can see that every request actually shows this exact cost here in the activity page.

And that mattered a lot for this video because Claude Code's own estimate really overstates the cost.

And in this example, it overstated it by up to four

and a half times what it actually cost me to run this.

So every number that you see in this video comes directly from OpenRouter.

And even if a model gets rate limited halfway through a long run,

I can have a fallback model and move over to something else that my program doesn't completely stop.

If you want to try Rhea for yourself, OpenRouter is linked in the description.

I use it for pretty much anything where I need an API key.

And I have a ton of usage.

It's a great platform and really the best way to use AI models.

You also can call image, video, voice, everything from one single API key.

All right, so once you've got Rhea installed inside of CloudCode, you can simply just ask it to use Rhea

and rebuild pretty much any app that's on your computer where they can access from the web.

Now, if you go into your terminal -based environment to use CloudCode, you'll be able to see the MCP server.

So if you type

Cloud here, just go, yes, I trust this folder, and then type slash MCP,

you'll see the Rhea MCP server shows up here with 207 different tools.

Now, it also has some prompts and some other stuff inside of here, and basically it's ran through this kind of NPM package.

However, if you try to look at the MCP server from the desktop application, after you add it, you probably won't see it.

That's fine.

It's still there, but it will just appear when you start asking it to do something.

So if I say, Hey, rebuild the OBS application using reverse engineer, anything.

Then if I press enter here, it should find that connector.

So you see Rhea pops up right here and it will start building that out.

Now I won't wait for all of this to finish because I already built MongoDB Atlas,

but basically that's as easy as it is to start doing this.

So now I want to discuss what Rhea is actually doing behind the scenes, specifically when it's looking at compiled programs.

So things like a Windows executable file like OBS.

100

So first what the agent will do is open the binary and try to get an overview of the program.

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So what kind of file is it?

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What libraries it uses?

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Where does it start?

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Then it needs a starting point.

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So it's going to search for text that you can actually see in the application.

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It's like a button, a label, an error message, and it's going to jump to the code that uses that reference.

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Then it reads that function.

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So the decompiler is going to turn machine code back into C -like pseudocode, which the model will actually be able to read.

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Then it's going to follow all of the calls.

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So what calls this function?

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What calls that function?

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Where is the data flowing throughout the application?

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Now, anything that it can't prove, it's going to write down as an unknown instead of just guessing.

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And at the end of it, it's going to compare the rebuilt code against the original to check if they behave the same way.

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Now for compiled programs, you will need a decompiler installed.

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However, it can automatically install it for you if you just put it in bypass permissions mode.

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Now Compass, the one that I did here, is actually a JavaScript app.

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So it skips the decompiler because the code ships as JavaScript instead of plain machine code.

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So for MongoDB Compass, which Claude was able to remake, I pointed Rhea at a single 49 megabyte file.

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Now this is basically the entire app that just packaged together

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and in under three minutes it was able to map the entire thing.

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So it had 530 different files, over 3 ,500 code modules

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and over 13 ,000 findings including how the app's windows actually talked to the back end

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and how all of the communication occurred.

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So here's what these models actually built and I say models because I ran this with two models,

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Opus 5 .5 and Haiku 5 .5 to see what actually was the difference with an expensive, and a cheap model.

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Now, here's exactly what happened.

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Well, first we set everything up, right?

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Then I gave both models the exact same prompt.

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So I said, use RIA to figure out how

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Compass works, how it's styled, and then rebuild it as a desktop application with these eight features.

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This is what I included in the prompt.

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So I wanted the ability to connect a database sidebar, browsing documents with filters and pages, inserting, editing, and deleting, schema the tab,

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aggregations tab, and then the indexes tab.

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And I wanted it to look exactly the same as Compass, as you guys already saw.

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I also gave it a small test database that it could load up here that I already had built with MongoDB.

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So here's the results that I actually got that I had Claude's screenshot.

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So you can see Opus 5 .5 costs $13.

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Haiku 5 .5 costs $0 .85.

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With Opus, it took 42 minutes.

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With Haiku, it took about 15 minutes.

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And you can see that they look pretty similar here.

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Now Haiku has some visual differences compared to the real compass version.

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You can see it's a little bit simpler.

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The icons aren't quite there, but generally it gave me pretty much the exact same stuff.

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Just again, like a little bit of small issues with kind of the spacing and the indexes, and it wasn't quite as clean,

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but you get the idea, right?

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We're able to build the entire thing.

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And when we used Opus 5 .5, it gave us a near identical clone.

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Again, just to open this up and show you, like I can go to aggregations, I can run queries, I can view specific schemas,

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I can look at the index.

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I can connect to different databases.

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Like, like how crazy is that, that this actually just works.

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I can directly even like edit a value here and change this and save it.

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And it works properly.

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And this is just all done with AI with literally two or three prompts.

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So with all of that said, what does this actually mean?

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Well, to be honest with you, I don't really know.

159

I mean, this is super cool.

160

It's obviously very interesting that we can do this.

161

And it really shows

162

that the value of software is no longer just in writing a bunch of code like it used to be.

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It's really more in making something that's legitimately valuable that solves a problem and then people actually want to use.

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This leads me to believe that more and more software will just de facto become open source.

165

And the companies are probably going to be less protective of trying to guard all of their secretive code bases.

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Because really, there's just less value in doing that now than there used to be in the past.

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I can remember when code was sacred

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and you wouldn't want to share certain modules or files

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or what you're doing because you don't want anyone to get in on your secret

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and rebuild this really technically complex app that you made.

171

Now we literally have an AI tool that can rebuild pretty much anything in a matter of few minutes and even decompile,

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go through, run all of the compiled code.

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It's just crazy where we're at now in 2026.

174

So I think it shapes what we use software for, what the value of software is and what we're going to look at going forward

175

but I don't believe this wipes out software engineers.

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And to be honest, the more cool tools we get like this, the more interesting software we can build.

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And again, in my opinion, the value of software is knowing what to build, not just building it itself,

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having that judgment, building a nice UI, solving a legitimate problem.

179

Now, more than ever, the code is not that valuable, but being able to know what to code and having that judgment is becoming more valuable.

180

That's my opinion.

181

I don't know if you guys agree with me.

182

Let me know in the comments down below, and I will see you in another video.

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คำศัพท์และข้อสังเกตด้านการพูดสำหรับบทเรียนนี้

บทเรียนฝึกพูดนี้ใช้วิดีโอ “I Tested The Viral Reverse Engineering Repo” เป็นสื่อ คำที่ถูกพูดซ้ำบ่อยที่สุด: code, tool, model, app, reverse วิดีโอนี้มี 182 ประโยค และ 2437 คำ สำหรับฝึกพูดตาม ช่วงที่มีเสียงพูดยาว 11:23 ผู้พูดพูดเร็ว ประมาณ 214 คำต่อนาที จึงมีการเชื่อมเสียงและลดเสียงค่อนข้างมาก 85% ของคำอยู่ใน 3,000 คำที่ใช้บ่อยที่สุดในภาษาอังกฤษ ส่วนที่เหลือควรดูไว้ก่อนเริ่มฝึก

คำศัพท์สำคัญในวิดีโอนี้

คำที่ควรเรียนรู้ 15 คำจากวิดีโอ พร้อมคำอ่านและความหมาย:

คำศัพท์	คำอ่าน	ความหมาย
compass คำนาม	/ˈkʌmpəs/	เข็มทิศ
clone คำนาม	/kloʊn/	โคลน
server คำนาม	/ˈsɝvɚ/	เซิร์ฟเวอร์
database คำนาม	/ˈdeɪtəˌbeɪs/	ฐานข้อมูล
cloud คำนาม	/ˈklaʊ̯d/	เมฆ
package คำนาม	/ˈpæk.ɪd͡ʒ/	หีบห่อ, ห่อ
desktop คำนาม	/ˈdɛsktɒp/	พื้นโต๊ะ
compare คำกริยา	/kəmˈpɛɚ/	เปรียบเทียบ
solve คำกริยา	/sɒlv/	แก้, แก้ไข
connect คำกริยา	/kəˈnɛkt/	เชื่อม, ต่อ
edit คำกริยา	/ˈɛdɪt/	แก้ไข
module คำนาม	/ˈmɑd͡ʒul/	มอดูล, โมดูล
occur คำกริยา	/əˈkɜː/	เกิด
label คำนาม	/ˈleɪ.bəl/	ฉลาก
plain คำนาม	/pleɪn/	ที่ราบ

กริยาวลีที่คุณจะได้ยิน

คำศัพท์	ความหมาย
show up คำกริยา	โผล่

ประโยคที่ควรฝึกพูดซ้ำ

ประโยคสั้น ๆ ที่สมบูรณ์จากวิดีโอ ซึ่งนำไปใช้ในบทสนทนาประจำวันได้:

You can see it's a little bit simpler.
We're able to build the entire thing.
It's obviously very interesting that we can do this.
I don't know if you guys agree with me.

ไวยากรณ์ในวิดีโอนี้

โครงสร้างที่ผู้พูดใช้บ่อยที่สุด พร้อมคำพูดจริงจากวิดีโอ:

โครงสร้าง	ในวิดีโอ
“used to” used to + กริยา — นิสัยหรือสภาพในอดีตที่ตอนนี้ไม่เป็นแล้ว	used to be
Passive voice be + กริยาช่อง 3 — เน้นสิ่งที่เกิดขึ้น ไม่ใช่ผู้กระทำ	is built · was already built · is linked
Relative clauses who / which + อนุประโยค — ข้อมูลเพิ่มเติมเกี่ยวกับคนหรือสิ่งของ	Compass, which is · group, which is · tokens, which makes
Present perfect have/has + กริยาช่อง 3 — เหตุการณ์ในอดีตที่ยังเกี่ยวข้องกับปัจจุบัน	have been · I've seen

การออกเสียงที่ควรระวัง

ผู้พูดใช้รูปย่อและรูปลดเสียง 38 ครั้ง เช่น don't, I'm, you're ให้พูดแบบสั้นตามที่ได้ยิน

เสียง “sh” และ “zh”: screenshot /ˈskriːn.ʃɑt/, aggregation /æɡɹəˈɡeɪʃən/, dashboard /ˈdæʃˌboɹd/
คำยาว — ลงเสียงหนักให้ถูกพยางค์: legitimate /lɪˈd͡ʒɪt.ɪ.mət/, technically /ˈtɛk.nɪˌkəl.i/, decompiler /diːkəmˈpaɪlə(ɹ)/, aggregation /æɡɹəˈɡeɪʃən/, executable /ˈɛksəkjutəbl/

เสียงที่คนไทยมักออกเสียงยาก:

เสียงท้ายคำ — ออกเสียงให้ครบ ไม่เปลี่ยนเป็นตัวสะกดแบบไทย: reverse /ɹɪˈvɝs/, compass /ˈkʌmpəs/, database /ˈdeɪtəˌbeɪs/, install /ɪnˈstɔl/, package /ˈpæk.ɪd͡ʒ/
/v/ — ไม่ใช่ /w/ ให้ฟันบนแตะริมฝีปากล่าง: reverse /ɹɪˈvɝs/, server /ˈsɝvɚ/, solve /sɒlv/, protective /pɹəˈtɛk.tɪv/, dive /daɪv/
/r/ กับ /l/ — แยกให้ชัด: rebuild /ɹiːˈbɪld/, variable [ˈvæɹ.i.ə.bl̩], viral /ˈvaɪɹəl/, decompiler /diːkəmˈpaɪlə(ɹ)/

วิธีฝึกกับวิดีโอนี้

ฟังวิดีโอให้จบหนึ่งรอบโดยยังไม่ต้องพูด แล้วจดคำที่ยังไม่รู้จัก
เริ่มที่ความเร็ว 0.75× พูดตามทีละประโยค แล้วกลับไปใช้ความเร็วปกติเมื่อเริ่มคล่อง
อัดเสียงตัวเองแล้วเทียบกับต้นฉบับ โดยสังเกตคำอย่าง compass, clone, server เป็นพิเศษ

เทคนิค Shadowing คืออะไร?

Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ

เทคนิค shadowing: อ่านคู่มือฉบับเต็มทีละขั้นตอน →

ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: I Tested The Viral Reverse Engineering Repo

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คำศัพท์สำคัญในวิดีโอนี้

กริยาวลีที่คุณจะได้ยิน

ประโยคที่ควรฝึกพูดซ้ำ

ไวยากรณ์ในวิดีโอนี้

การออกเสียงที่ควรระวัง

วิธีฝึกกับวิดีโอนี้

เทคนิค Shadowing คืออะไร?