The Future of Cloud Coding | 2026 Trends - video Dailymotion

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Transcript

00:00Cloud and coding are going to look very different in the next few years.

00:03AI isn't just helping us write simple lines of code or prototype front-end applications anymore.

00:08It's changing the way that developers work end-to-end.

00:11If you're like me and went to college before AI tools existed,

00:14you'll know how much time we spent grinding through coding assignments or even thousand-word essays.

00:18But now, the kind of work that used to take hours can be done in a few seconds using AI.

00:23And if you don't adapt to this shift, you'll get left behind.

00:26In fact, Sam Altman, CEO of OpenAI, said that students should master AI tools

00:31the way that his generation learned to code.

00:33That's why in this video, I'll be sharing with you the top three trends

00:37that will reshape the future of cloud and coding.

00:39I'll also be sharing with you a cloud project I built last week completely using AI

00:43and how you can do the same with a tool called Warp.

00:46Let's get into it.

00:47Alright, trend number one is the growing partnership between humans and AI agents.

00:51For decades, coding has been centered on humans typing every line.

00:54Even with autocomplete or co-pilot style suggestions, you are still doing most of the work.

00:59But nowadays, the model is changing.

01:01We're moving towards a true partnership where humans and agents work together.

01:05AI agents aren't just going to be assistants that can spit out code snippets anymore.

01:09They can now plan entire technical projects, map dependencies,

01:12and refactor code across multiple files.

01:14It's almost like having a bunch of developer teammates,

01:17except they can work an unlimited amount of hours without getting tired.

01:20They do need your help from time to time, but the more you work with them,

01:23the better they get at the tasks.

01:25And with that, your role as a human shifts from how do I implement this function,

01:29to how do I prompt and direct an agent to build exactly what I want.

01:33This shift also applies to the cloud.

01:34If you're a cloud engineer and you're looking to build a cloud native application,

01:38you no longer have to manually write lambda functions or type in CLI commands.

01:42Instead, you can just describe what you want in plain language,

01:45and your AI agent will generate the entire application.

01:48They will ask you follow-up questions and certain permissions to perform the tasks in order to achieve this.

01:53And of course, this means more free time,

01:55so that you can focus on things like scaling architecture or managing security,

01:59both of which need human judgement and decision making.

02:01The problem is, most people still think of AI as a single assistant,

02:05but the real power comes from multiple agents working together,

02:08each focused on different aspects of a project.

02:10Let me show you what I mean through this cloud services comparison tool I built last week using Warp.

02:15Alright, so here's the AWS service comparison tool I built using Warp.

02:19You can see here that it compares AWS services with detailed information about categories, features, and pricing.

02:26Let's check it out.

02:27So, I just have a list of 10 AWS services to start off with,

02:31but of course, I can always add to this catalogue.

02:33Here's all the categories I can filter by,

02:35and I can also see if the service is within the free tier or not.

02:39Let's say I filter by a database.

02:41Cool, so here's the two AWS databases in my catalogue.

02:44It lists the key features as well as the pricing models.

02:47What I can also do is choose to compare two AWS services side by side.

02:52So let's say EC2 and S3, and I'm going to click on show comparison.

02:57Nice, so there's category, launch here, if it's in the free tier.

03:01I mean, this application is pretty cool, right?

03:03Now, what if I told you that I didn't have to code at all to come up with this application

03:07and to deploy it onto Vercel?

03:09I use this tool called Warp, which is pretty much an agentic development environment.

03:13Like it says here, you can go from prompt to production.

03:16Many of my developer friends love it,

03:18and it's trusted by over half a million engineers at these leading companies.

03:21Alright, let's take a look inside Warp to check out all of its features.

03:25As you can see here, I'm in my cloud service comparison tool.

03:28If you want to see the full tutorial,

03:29you can check out this build with me video where I walk through exactly how I built the tool.

03:34But yeah, let me show you some of the features.

03:36Let's say I want to expand my cloud services comparison tool beyond AWS.

03:40I also want to add in Azure services as well.

03:42What I can simply type is add Azure services to my application.

03:49And you can see the steps that it's taking.

03:50By the way, you can see that it's going through each step quite quickly,

03:53and I don't really need to do anything.

03:55And that's actually because of the way I've set up the permissions.

03:58Apply code diffs, read files, create plans, execute commands are on always allow.

04:03But if you want to review the changes every time the agent performs an action,

04:07you can change it to always ask.

04:09Cool, so now it comes up with a list of tasks to perform

04:11in order to add in Azure services to our cloud comparison tool.

04:15It's going to take a few minutes to complete, so let's wait for a bit.

04:18Amazing. Okay, so our application includes now both AWS and Azure services.

04:24The cool part is that I can choose an AWS service and an Azure service,

04:28and then I can compare it side by side.

04:30From this demo, you can clearly see the collaboration between humans and agents.

04:35The agent handles the heavy lifting, but you're always in control of what actually gets shipped.

04:39Alright, trend number two is that cloud and AI will start blending together into one skill set.

04:44Now, this is especially important for my cloud learners out there,

04:46because this will impact what you'll need to learn and upskill in.

04:49So traditionally, cloud and AI have felt like two separate paths.

04:53You have cloud engineers focusing on AWS, Azure, and Google Cloud.

04:57And then you have AI and machine learning engineers working on models and training pipelines.

05:01Companies had cloud teams, and they had AI teams.

05:04But going forward, these two worlds are going to intersect.

05:07Cloud and AI won't be siloed skills anymore.

05:10Instead, they'll form one combined toolkit.

05:12Companies will expect cloud engineers to use AI in their day-to-day work,

05:15spinning up cloud resources with AI, integrating AI agents into their workflow, and so on.

05:20According to Gartner, one of the research firms out there,

05:23the rise of agentic AI will mark one of the fastest transformations

05:26in enterprise technology since the adoption of public cloud.

05:29But the good news is that AI pretty much runs on the cloud.

05:32The more demand there is for AI resources,

05:35the more job openings there will be in the cloud space.

05:37My recommendation is to build strong foundations in both areas.

05:41Learn how AI agents can help you automate cloud tasks,

05:44and at the same time, understand how cloud infrastructure supports AI.

05:47In the future, instead of bouncing between five different tools,

05:51you'll likely be using a single environment where cloud, coding, and deployment are unified.

05:56Let me show you an example of what I mean.

05:58With Warp, I can plan my projects, use it as a code editor,

06:02work with AI agents, as well as deploy it to the cloud.

06:05I've already shown you how to work with AI agents in Warp,

06:08but let me now show you how you can edit code directly while the agent makes the changes.

06:12So I've noticed in my cloud service comparison application that Amazon Aurora is missing.

06:17Let's add that in now. I'm going to click on proceed with plan.

06:20So Warp has realized that Aurora is not currently in the database,

06:23and it's going to add it in to the root level.

06:25So now it's asking me for permission to add Amazon Aurora in.

06:29Let's click on execute.

06:30Nice! Amazon Aurora has been successfully added to the cloud services comparison tool.

06:35On the left hand side, I can view the changes that have been made,

06:38and on the right hand side, I actually have the code editor open,

06:42so that I can access and edit the files directly.

06:44Let's say I want to list an additional feature.

06:47What I can simply do is type in Aurora supports global databases.

06:54And so what I can do is simply save it, and then I can close this code editor section.

07:00Okay, let's move on to trend number three, and that is debugging will become mostly automated.

07:04Now debugging has always been one of the slowest and most frustrating processes in software development and cloud.

07:10If you've ever deployed a cloud formation stack only to get back a vague rollback failed message,

07:15you know exactly what I mean.

07:17Or maybe you've written a simple script, ran it, and all you saw was an error saying that something went

07:22wrong.

07:23Starting from now, that's all going to change.

07:25I mean, we're already seeing the trend.

07:27There's a lot of tools out there that can help you catch errors faster.

07:30But what's new is that AI agents can now step in.

07:32With AI, instead of just showing you the errors, the agent can analyze the logs in real time,

07:37explain the problem in plain English, and even generate a suggested fix.

07:41What's powerful here is that you still stay in control.

07:44Agents will propose the fixes, but you can be the one to review them,

07:47refine them, and decide what actually gets shipped.

07:50Let me show you how cool automated debugging is.

07:52So what's happening here is that I'm trying to debug my application.

07:56I want to run it locally in my computer, but you can see here that this site can't be reached.

08:00So here's what's happened with the debugging.

08:03It's noticed that the data.py file defines AWS services,

08:07but that the main.py file is trying to import cloud services.

08:11On warp, you can see the direct code differences.

08:13And yeah, let's try to see if it can get it running.

08:17Okay, I'm going to apply this change.

08:19I like how it's updating me on every step of the process.

08:22Apply changes again.

08:23Now I'm going to set it on auto-approve.

08:26So this arrow right here.

08:27Cool, so I could just walk away from my computer now, and in a few minutes,

08:31it's probably going to help me finish resolving my issue.

08:33Now, while that runs, let me share with you why I'd recommend using warp for your technical projects.

08:38First, warp's performance is top-notch.

08:41It's rig number one on terminal bench and 75% on SWE Bench Verified,

08:45scoring higher than tools like ClaudeCode on coding benchmarks.

08:49Next, it has the best UX for coding.

08:51Warp combines everything into a unified developer workbench,

08:54so that includes coding, AI agents, and CLI tools all in one place.

08:59You've seen this in action during the demos.

09:01And thirdly, you get flexibility.

09:03Unlike ClaudeCode, warp isn't limited to just the terminal.

09:06And unlike tools like Cursor, warp works entirely across the development lifecycle.

09:10Perfect!

09:11Warp has successfully helped me debug my application,

09:14and if we scroll down a bit, you'll be able to see Amazon Aurora listed as a service.

09:19If you want to explore warp for yourself, I'll leave a link to it in the description below,

09:23where you can get warp pro for just $1 in your first month using my code Lucy.

09:27So, those are the top 3 trends I see shaping the future of cloud and coding.

09:32What are your thoughts? Let me know in the comments below.

09:34Overall, I believe that the future of cloud and coding is going to be a pretty exciting one.

09:39Like many major tech transformations we've seen,

09:41AI is definitely disrupting the industry and will continue to do so.

09:45It's going to be de-placing some jobs, but also creating new opportunities.

09:48The key isn't to fear the change, but to build skills that will let you work alongside these new tools.

09:53If you want to keep up to date, you can subscribe to my channel for more videos like this.

09:57Thanks for watching, and I'll see you in the next one. Bye for now!

The Future of Cloud Coding | 2026 Trends

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