The Only AI Coding Tools Worth Learning in 2026

Software development has fundamentally changed. We've now entered the era where there is a new tool every few weeks, and it's really a matter of keep up or get left behind. So that's why in this video, I'm going to explain to you the tools that I actually use every single day for coding in 2026. These are the best AI coding tools for developers. Let's dive in.

Now the first tool on my list is open claw clawed bot. More bot, whatever you want to call it. I'm sure you guys have all seen this all over the internet. Effectively, this is an orchestration layer on top of an AI agent that you can run locally on your own computer that is capable of essentially running autonomously in the background. Now, it's actually not as impressive as a lot of people like to make it out to be, but in my case, I spent about ten hours setting it up. I connected a bunch of different tools to it, so for example, if we just go to skills, you can see I kind of have a long list of tools that I have connected. I connected it to a bunch of sandbox accounts that are specific for this. I deployed it on a virtual private server, and right now I actually had it create, for example, like a YouTube dashboard with some outliers. I had it create a logging system for itself. So I can see all of the things that it's currently working on, when it's working, how long it's working, you know, the usage, the number of tokens, the GitHub commits that it's making. And effectively, I now have this 24 over seven AI assistant that is running on a virtual private server that I can message via telegram, and that I can monitor through all of these different dashboards. So I also connected this using a VPN so that it is secure. And then I'm tunneling the traffic between my computer and it. And it is not open on the internet so it is not going to get hacked. Now I'm going to make a video on how to set this up properly. So if you guys want this, you don't get hacked. So if you're looking for that, leave a comment down below. But overall, this is definitely worth playing with. Just be very, very careful because you can set it up in a way where you're leaking all of your own data, and really, it's much more of a security risk than it is a productivity tool. But for me, it's been incredible. Again, we'll talk more about it on the channel. That's tool number one.

Now the next tool on my list is Cloud Code. Now cloud code is one of the best coding agents out there. It's also extremely lightweight, runs directly inside of the terminal, and is capable of producing production level software assuming that you prompt it correctly. This is one of my favorite tools to use for generating code. I like the fact that it uses my Pro subscription. And then of course, if I go over, which happens all the time, I can buy additional credits. Now, I do like to use a lot of different models and play around with different tools. Personally, I don't find the cloud code is the best one out there, you know, by a mile. Like a lot of other people talk about on YouTube, and I still do use other tools like the next one on my list, which is cursor.

So cursor is an AI code editor. This is actually a fork of Visual Studio Code, which means everything you see is effectively the exact same as the predecessor to this VS code, which was the most popular editor for a long time before I became a very popular thing. The only edition is that it has all of these AI enabled features. So in cursor you can toggle this agent tab, and you can see some examples of things that it's done here. And you can effectively just prompt it and ask it to do something. I much prefer using cursor for making small changes, smaller edits, small refactoring, not massive huge, you know, projects like I might make with cloud code, for example. And when I'm working on something that's a lot more professional, that needs to be a structured code base. And what I actually want to review line by line, everything that it's doing. This is my go to editor. It's what I use most of the time when I'm doing AI development. Not for every project, but specifically for front end related stuff or more simple frameworks and tasks. I will almost always open up cursor. I will toggle it to the best model. So right now you can see I'm using opus 4.5 and then I will start prompting away. I'll go through various different conversations. I'll review the code myself. You don't connect it to GitHub or connect up some MCP servers or some other tools. And if you're someone who is a professional developer, this is likely what you are going to be using, or at least something similar to it. For me, I like using this because I'm very familiar with this editor already. I can search for files, right? I can open up the command palette, I can run my workflows and it really doesn't change how I'm developing, other than adding this AI agent that doesn't feel like it gets in the way, like it does in a lot of other tools. I can still search through my files, I can still audit the structure, and I can make sure that I'm generating something that I'm going to be happy reviewing in one, two, three, four years from now.

Moving on. The next tool on my list is warp. Now, warp is a full fledged AI terminal that is capable of writing code, generating commands, and running particularly backend infrastructure or DevOps related tasks. Now, warp, unlike cloud Code, is its own desktop application that you download. So you can see that I have this full kind of AI terminal open. This is the warp interface. And unlike cloud code, where you just run it as a process in your existing terminal, this takes up its own application. Now the reason for that is not only does it act as a full code editor, as you can kind of see here, but it also allows you to auto autofill things like terminal commands, for example. So I could say something like, you know, install the new Debian package or whatever, right. And I can have this in agent mode where it will automatically infer what the command is that it needs to run, and then go ahead and run that for me. But at the same time, I can also just directly run a terminal command so I can run like ls, for example, and it will print out all of the files that are currently here. So I like this particularly when I'm working on something that's very backend heavy, where I have a lot of Docker containers, where I have commands that I don't necessarily know how to run, and I can just have it autocomplete and directly spit out inside of the terminal. So especially when I have four or 5 or 6 different terminal instances open, I like to have those open inside of warp. I like to be able to kind of view the files without it being overwhelming, like it might be in something like cursor. However, if I'm going to be reviewing massive amounts of code, I would go back to something like cursor where. So I'm doing a lot more like DevOps automation running in the back end. Then I like to have this AI terminal. I feel it just gives me some extra productivity and some more gains. It's not revolutionary. It doesn't completely change the workflow, but it's just a nice kind of added feature that I have on my computer that gives me an enhanced terminal that I think works pretty well.

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Now the next one on my list here is a whisper flow. You may have heard of it before, but this is effectively a really powerful dictation tool, which I use all the time when I'm coding. This allows me to avoid having to manually type something and actually just speak into my microphone, or even into my phone, or whatever, and have the prompt just be generated extremely fast. So you can see my average word speed 160 words per minute. You know, I've written 30,000 words in the last three weeks or whatever, and you can see a bunch of the different prompts that I've set. Now, the interesting thing about whisper is that it automatically formats the text and gives you much better dictation. And what is it? Audio transcription. Then you normally get if you just use like the built in windows feature or the one on Mac or whatever, it has a built in dictionary as well. So it learns about like different words that you have. If you kind of see them differently or spell them differently, you can put in snippets like automatic commands, where if you say docker run, it will like, you know, populate this command. You can have different styles. I don't set up one to other stuff. I mostly just use it for the dictation. But I'll quickly show you that if I go into like cursor for example, you can actually even tag files. So I can do something like, you know, go read the connection.py file and tell me what it's about. And let's give this a second and you can see it automatically tags connection.py. And then gives me the transcription extremely quickly. I'm not here to advertise it, it's just what I use every single day. So if you want the best transcription tool that I would definitely check that out.

All right. So the next tool on my list is an obvious one. But I still use it all the time. And that is ChatGPT. Now at this point ChatGPT just knows so much about me. It's a sleek, easy interface to get to. I can run it on my phone easily. I can open it in a browser tab and I find that it just gives me consistent responses. I definitely don't use this for generating massive amount of code, but I do use it for optimizing prompts, especially if I don't want to mess up. You know my current instance that I have set up where I'll just paste in or even dictate to it, you know, using whisper something that I want to create, have it kind of generate a better prompt for me, and then pass that into another AI model. I also oftentimes go back and forth that idea. Sometimes I put it in voice mode and I just chat with it, kind of like a partner or like a coworker, or especially about architectural and design decisions, because it's able to do some quick research and kind of compare what other people have done and give me decent ideas. Again, it is not the most powerful tool, but it's just something that I use every single day. So I felt like I had to mention it. And again, the context that it has is super powerful. It knows so much about me that a lot of times I just know it's going to give me a decent response because of those memories and kind of the training that I've given it.

What I have next for you is definitely something that is more on the enterprise side, and that I probably wouldn't use as a solo developer, but that is extremely powerful and that I've been really fortunate to work with a lot recently, and that's glitzy. And this is effectively a tool that's capable of generating extremely large pull requests to take multiple days to run, and autonomously analyzing your code base and just completing tasks without the back and forth of the traditional AI agent. So I'm going to quickly show it to you. I have it set up for a bunch of different repos, but what it does, is it starts by ingesting your entire project, creating a detailed technical specification file for it, which I'll go through here in a second, and then documenting the entire code base and allowing you to build on top of it. Refactoring, generate, you know, 100,000 line plus pull requests and effectively replace the role of like a junior or mid-level engineer by spending a lot of time upfront writing a prompt and then having it go away, work on it for like 2 or 3 days and then give you the result. So if I scroll through here, you can see that this is the technical specification document that it generates when it first ingested code base. It usually works on an existing code base. It's not something that you're usually going to use to spin something up completely from scratch. And it creates these like really detailed charts and graphs and goes over the architecture and explains everything extremely in-depth. And then what you're capable of doing is once you have that tech spec, you can go here and ask it to build something so you can get it to make a feature, to fix bugs, to add testing, to document the code, whatever. Right. And then you can see all of the code that's generated. In my case, it's generated 61,000 lines. Because I've been very specific with what I wanted to do, I had it actually refactor an entire code base. There was a bunch of I slob into something maintainable. I had to build new features, I had to add advanced documentation. And testing is very, very cool. And again, it's designed for enterprises because it is quite expensive to use. But if you haven't seen it before, I definitely would recommend checking it out. It is objectively the most powerful tool I have used for generating code, but again, it's very expensive. It takes a long time to run, and it requires a lot of upfront work in terms of building kind of, you know, really detailed advanced prompts. And then it goes, spends a few days working and spits out a PR with like hundreds of commits and hundreds of files. That completes the task. You asked it.

Then the next tool on my list here is one of my favorites for creating simple landing pages. And this is lovable. Now, you've probably heard of lovable before, but this is particularly good at design and frontend related tasks. Well, it can do full stack applications and connect to databases, super base, etc. I don't usually use it for that, but actually I was able to create the entire landing page. Let me just pop it up for you of my Dev Launch Resource vault by purely using lovable. So this whole page that you see right here was, made with lovable. It took me maybe ten minutes to do that. I just put, you know, a quick like, VSL that I had here, told it what I want, gave it some color themes, gave it the logos and it just split it up and deployed it, like, instantly. So if I just want a simple landing page, I always turn to lovable because it's super fast. The deployments built in, it's very easy and quick to get it up and running, but I don't really use it for much more than that other than some of the test stuff you kind of seen here that I was building with lovable.

Now, last on my list, I'm actually going to bundle two tools together. And this is GitHub Copilot and Juni. Now Juni, if you're in the JetBrains ecosystem, which I know a lot of people prefer, and GitHub Copilot, if you're working in the Microsoft ecosystem or something like Visual Studio Code, Visual Studio, etc. Now I like to use git GitHub copilot. Sorry for like automated pull requests, running GitHub actions. You know, reviewing the code, things along those lines. I don't typically use it in my code editor because I think there's just better agents out there. It just work better, especially in like a VS code type fork, but it is notable. It is very good. And again, on the GitHub side it works really well. And then Juni, this is JetBrains AI coding assistant. I have used it a fair amount and it is pretty good. Obviously it's native inside of the Ides like PyCharm, which I use all of the time, and specifically if I'm doing Python coding tasks where I want to work in a JetBrains ID like PyCharm, then I flick on Juni, I use it, and it's capable of doing pretty much the same stuff that a lot of the other AI coding editors can as well. It's not as great in projects with mixed languages, but specifically for Python. When I want all of those other development tools, then it is a great kind of companion here, just on the side bar where I can, you know, ask it to do something and it does that using AI.

Okay guys. So those are the tools that I had for you in this video. I hope that you found at least one new one that you haven't used before. Let me know what AI coding tools you are using right now, and I look forward to seeing you in another video.