शैडोइंग अभ्यास: Cloud Providers are changing RAPIDLY [REUPLOAD] - वीडियो के साथ अंग्रेजी बोलना सीखें

Cloud providers like Vercel, Cloudflare, but even AWS, to some extent, are changing rapidly, at least some of them, rapidly.

And I think that's good for us developers.

It's also worth a closer look. Now, cloud providers are changing because we are changing as developers because, of course, what's changing right now is what we're building and also how we're building. Both things are changing right now. What we're building is, of course, to some degree what we built before, software, web apps, and so on. So that, of course, to some degree has not changed, but we're building more because AI agents make it easier to build stuff. And let's be honest, there's a lot of stuff, a lot of applications and demos in there that will or at least should never see the light of day.

But we're building more because AI agents make it easier.

White coding, of course, is a thing.

Maybe not the thing you wanna use primarily for serious projects, for serious software, which you plan on selling or distributing, but of course, white coding can be absolutely fine for your own little internal tools, some throw-away software that solves specific problems where you don't care about covering all niche cases or about security or anything like that. So we got that, and therefore, we are of course building more. And then, of course, we are building AI agents and agentic apps, whatever that means. But in the end, it means applications or tools, workflows, whatever you wanna call it that wrap large language models, that wrap AI and then do something potentially agentic where you potentially are building something where an AI can call tools, dispatch tasks, work with a file system and so on. So, that's the what part that is changing. But, of course, the how is also changing because we are, or at least many of us I guess, no longer are writing the code by hand. We're not doing that anymore, at least not 100% of the code. Instead, we are using AI agents like Claude or Codex or whatever you are using, and of course, we're letting those agents do more and more. So, you may use them to write code but maybe you also let them run all kinds of CLI commands and tools on your system, starting with Git for committing and pushing, which is relatively trivial and easy, all the way up to deployment maybe.

You may not just be using those agents for generating the code.

You may also be using them to generate docker images or to use CLI tools that push the code, that push the applications to some hosting provider. And that takes me back to the cloud and how cloud providers are changing.

Vercel itself rebranded itself to be all about agentic infrastructure.

If you visit vercel.com, that is the first thing you read right now. And on the right, you see "For coding agents, to ship apps and agents automated by agents." So (laughs) here we got the word "agents" in that box three times and they are clearly talking about being the platform for anything built by agents, including agents themselves. Now, it's pretty similar for Cloudflare.

If I visit cloudflare.com right now, I see this message where I learn that "Cloudflare is one platform for my apps, agents and workforce." So, definitely a bit less agentic-first or AI-first, but we got the word "agents" right here in the main messaging as well. And we'll also see it when we take a look at the services offered by these cloud providers that they're changing quickly. Now, Netlify is also mentioning AI but not the word "agent" here.

They are still mostly about serving your apps, your web apps, that may have been built with AI but not so much about running AI agents in the cloud and I'll get back to why that matters. And if we take a look at AWS as a last example here, I also right now when I visit this, have the word "agent" in the, in the main message I see, that I can "move at the speed of agents." Now, what is important here or what's interesting and what is of course related to what we're building and how we're building, is that all these cloud providers, I would say, nowadays have three main pillars.

The, the first pillar is about apps and that is of course what they were always about. Now, a little side note, of course, AWS is a bit hard to compare to Vercel and so on because it's more complex. It's more about having tons of primitives and managed services. It's about all those enterprise customers, not to say that Vercel doesn't have enterprise customers, but AWS is all about giving you all the building blocks you could potentially ever want to build any kind of system in the cloud.

And therefore, they were never primarily or only about running web apps or... ...

other pieces of software in the cloud.

They were about giving you the tools you need to do anything in the cloud, to store any kind of data there, run any kind of workflow. Vercel, Netlify, and also Cloudflare, of course, were more about, "Hey, you got a web application? Run it here." Not just about that, of course, but that was definitely more of their focus.

So I'll primarily talk about apps here, and when I mean apps, I mean, of course, web apps, websites, whatever you wanna call it.

So that is what we use these cloud providers for, and that, of course, has not really changed. You can and you will still use them for that, and it doesn't really matter how you built those apps, right?

If you use Cloud Code or Codex, the thing that maybe is a bit easier now, and where I actually like AI a lot, is that deployment gets easier because you can point Cloud Code or whatever at the relevant documentation pages.

You can install the CLIs. You can install the Vercel CLI, the Cloudflare Wrangler tool, and so on, and if you get that installed, if you give the agent some, some hints at where to search for, for deployment details and instructions, it can do the deployment for you, or at least it can prepare it for you.

It can write configuration files.

That all gets a bit simpler because, let's be honest, deployment can be a bit of a pain if it gets a bit more complex, and AI can definitely help a bit there. Now, just as with web coding, obviously, you still wanna understand what's going on, at least I want to understand what's going on, but it can help there. So that pillar, of course, still exists.

Now, the second pillar, which we now have, however, which is new, is agents or AI agents, that you run those in the cloud because, of course, we're at this point in time where we're, for one, still trying to figure out how exactly we'll work with AI as developers.

But we're also at this point where we're all, or where all the companies are, about building AI agents, and it's sometimes hard to grasp what exactly you wanna build and what exactly those agents should be doing for you.

But at least from the perspective of a CEO, you might have an, a marketing agent. You might have an agent that, uh, does customer support, a finance agent that helps out in your finance department, and so on.

And as a developer, you may have an agent that tackles open issues on your GitHub repository.

You may have another agent that does research, and these agents need to run somewhere. Now, obviously, they can run on your system.

That will be a bit harder if you're working in some bigger company where you don't have unlimited privilege and can't install everything you want on your system. But even as a small developer, running everything on your system has, of course, some security implications.

If you have an AI agent roam around on your system, it can potentially do damage accidentally or because of prompt injections and so on. So you may want an environment where it can safely operate or where it can't do as much damage. Now, there are loads of different solutions out there. You could look into tooling like Just Bash, which is, interestingly enough, also by Vercel, by the way.

They are releasing many tools, uh, that aim to make development with AI easier. And Just Bash essentially is a, a sandboxing solution, which you can run on your system to run an agent inside of a virtual bash with limited privilege and so on.

So you could use tools like that, but, of course, you could also run those agents in the cloud, or you could have a combination and have an agent that runs locally offload certain tasks to the cloud. So the Cloudflare Sandbox SDK, for example, aims to simplify the process of running tasks, agentic tasks, with an AI agent doing its thing in the cloud, where you can then potentially expose R2, Cloudflare R2, which is their S3 equivalent, as a file system and so on, so that you have a throwaway environment where an agent can do whatever you wanna do.

If it breaks stuff, it doesn't matter because you can just restart the Sandbox and you don't expose your entire system.

And that, of course, therefore is a brand-new category of things you wanna deploy to the cloud or you wanna run in the cloud, and that is definitely where Vercel and Sandbox are moving towards. They want to not just make it easy for you and your agents to push web apps and apps to the cloud. That's also something they wanna do, but not just. But instead, they also wanna make it easy for you to run AI agents you may have built in the cloud.

And then there is a third pillar, I think, and that's the AI gateway pillar, or however you wanna call it.

You know, we got all these AI providers.

We got proprietary providers, obviously, like OpenAI, Anthropic, Google, and then we got some open-source models, which may be open source or open weight, but running them on your system can be tricky depending on the size.

Now, I do have various courses, obviously, including on ChatGPT, uh, the advanced guide, Cloud Code, but I also have a course about running local large-language models because I'm a big fan of those open-weight models where you can really just run them with Ollama or LM Studio or other tools on your system. But, of course, for most systems at least, you are limited to the smaller models, which can still be helpful as I show in this course.

But if we're talking about bigger models, you will still likely want some provider that hosts them for you so that you can access them through the cloud.

And no matter if we're talking about those open models, which you can't or don't want to run on your system, or if we're talking about many of the proprietary models, these providers, like Cloudflare, but also Vercel and also AWS, they offer services...

That could be called AI Gateway in the case of Cloudflare or for AWS, it's Amazon Bedrock. But these are simply services that are all about accessing AI through one uniform API where you can basically just switch one value and switch to a different provider, where billing is done through Cloudflare or AWS. And where it's, therefore, easier to access a broad variety of AI models which are easy to monitor, easy to switch, where you don't need to create, uh, tons of accounts with OpenAI, with Anthropic, with Google, with whatever other provider you want.

Think of it as OpenRouter!, essentially.

OpenRouter!, of course, is a service that makes it easy to switch between different models and Cloudflare, Vercel, AWS, they essentially have their own OpenRouter!-like solution, you could say. There are some differences because OpenRouter!

is really just a router, which is about funneling your request to different providers. Whereas, Cloudflare and AWS, for example, they also provide hosting for these models. So with Amazon Bedrock, for example, you can access Anthropic models that are hosted on AWS infrastructure, whereas a customer you can control in which region it should be hosted, where you have greater, uh, control over where your data gets stored or who gets access to your data.

And that, of course, can matter to enterprise customers.

So it's actually a combination of things here.

It's convenience, obviously, because it's easier to switch between different models. You can even set up routing rules where different requests may get different models automatically.

You have a, a unified billing experience.

But besides the convenience, it's also about more control over where the model is hosted and so on, at least for some of these providers. And I think, therefore, these are the main pillars we see right now for these major cloud providers, and I find it quite interesting that, for example, Netlify is still mostly about that first pillar here. It's their decision, their strategy, whereas Cloudflare and Vercel and AWS and many others, by the way, are, of course, branching out and are trying to cover all three pillars.

Now, I think, as a developer, no matter if you're building AI agents or not or... and, and no matter if you're working with AI or not, these are great developments. Because one s- nice side effect is that these cloud providers, in their effort to make it easier for AI agents to use them, are giving us more ways of accessing their services. They are improving their CLI tools, their documentation to provide (laughs) all that information to agents, which, spoiler, you as a human can also read.

So that's pretty nice. And they're building more useful primitives. I mean, Cloudflare alone...

And just to be super clear, this is not some paid advertisement or anything like that. These are really just services I'm using.

But Cloudflare alone, they released so many new nice services, like dynamic workers, where one worker, which is like a, a serverless solution provided by them, where you can execute code in the cloud, where one worker can spin up more workers to offload certain tasks. No matter if you're building AI agents or not, this can be a useful feature. If you're building any kind of service or tooling where your customers can maybe share some data or code with you or where you wanna execute some code that involves customer data or customer code, it's nice to have primitives where you can securely do so in throwaway environments. And therefore, these new capabilities are pretty nice to have, even if you don't care about AI at all, even if you're not building AI agents.

And that's why I'm pretty excited about these changes in cloud providers and why I think it's more interesting than ever to play around with different providers.

If you've used Netlify forever, maybe give Vercel or Cloudflare a try and dive back into their docs, maybe together with AI to understand what they offer and how you can build on top of them.

Anyways, that's just something I'm observing, something I'm pretty excited about. And as always, I'm interested in hearing your perspective on that and what I maybe missed or what you think about this transformation of cloud providers and where we're heading to.

✨ अनुशंसित वीडियो

257 वाक्य

संदर्भ और पृष्ठभूमि

हाल के वर्षों में, क्लाउड सेवा प्रदाताओं में तेजी से बदलाव आ रहा है। वर्चुअल प्लेटफार्मों, जैसे कि Vercel और Cloudflare, के विकास से यह स्पष्ट होता है कि डेवलपर्स की जरूरतों के अनुसार ये सेवाएं कैसे अनुकूलित हो रही हैं। जैसे-जैसे हम नई तकनीकों और एआई के साथ प्रयोग कर रहे हैं, यह सवाल उठता है कि हम अपने एप्लिकेशन और टूल्स को कैसे विकसित कर सकते हैं। यह वीडियो इसी बदलाव को समझाने का प्रयास करता है, जिसमें बताया गया है कि हम किस प्रकार से कोडिंग कर रहे हैं और कैसे एआई एजेंटों के प्रयोग से हमारे काम में आसानी हो रही है।

दैनिक संचार के लिए शीर्ष 5 वाक्यांश

“चलो इसे क्लाउड पर चलाते हैं।” - यह वाक्यांश बताता है कि आप अपने एप्लिकेशन को क्लाउड पर तैनात कर रहे हैं।
“यह एआई एजेंट बहुत मददगार है।” - एआई एजेंटों की उपयोगिता को दर्शाता है।
“मैं कोडिंग में एआई का उपयोग कर रहा हूँ।” - यह वर्तमान में कोडिंग में एआई को शामिल करने की प्रक्रिया को संक्षेप में बताता है।
“क्या आपको इस प्लेटफार्म की जानकारी है?” - किसी विशेष सेवा के बारे में पूछने का एक तरीका।
“हम इसे और बेहतर बना सकते हैं।” - विकास के दौरान सुधार की संभावनाओं को दर्शाता है।

स्टेप-बाय-स्टेप शैडोइंग मार्गदर्शिका

इस वीडियो से सीखने के लिए, शैडोइंग तकनीक का उपयोग करना बेहद प्रभावी हो सकता है। यहाँ एक सरल प्रक्रिया है जिसे आप अनुसरण कर सकते हैं:

वीडियो को ध्यान से सुनें: पहले वीडियो को सुनें और उसके मुख्य विचारों को समझें।
मूक शैडोइंग: वाक्यांशों को सुनने के बाद, बिना आवाज़ के उन्हें दोहराएँ। इससे आपकी उच्चारण में सुधार होगा।
ध्यान केंद्रित करें: उन वाक्यांशों पर ध्यान दें जो आपको अधिक चुनौतीपूर्ण लगते हैं। ये आपके अभ्यास में महत्वपूर्ण होंगे।
आवाज़ के साथ शैडोइंग: अब वीडियो को फिर से चलाएँ और एक निश्चित गति से बोलने का प्रयास करें।
रिकॉर्डिंग करें: अपनी आवाज़ रिकॉर्ड करें और सुनें। इससे आपको अपने उच्चारण में सुधार करने में मदद मिलेगी।

इस प्रक्रिया के माध्यम से, आप न केवल अपने अंग्रेजी उच्चारण में सुधार कर सकते हैं, बल्कि रोज़मर्रा की बातचीत में बेहतर तरीके से आत्मविश्वास से बोलने का अभ्यास भी कर सकते हैं। यूट्यूब से अंग्रेजी सीखें और अपनी भाषा कौशल में निखार लाएँ।

इस वीडियो का व्याकरण

वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:

संरचना	वीडियो में
Relative clauses who / which + उपवाक्य — व्यक्ति या वस्तु के बारे में अतिरिक्त जानकारी	pushing, which is · however, which is · Bash, which is
Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता है	have been built · could be called · are hosted
Present perfect have/has + past participle — बीता हुआ काम जिसका असर अभी भी है	has not changed · has not really changed

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

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शैडोइंग अभ्यास: Cloud Providers are changing RAPIDLY [REUPLOAD] - वीडियो के साथ अंग्रेजी बोलना सीखें

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इस वीडियो का व्याकरण

शैडोइंग तकनीक क्या है?