You have probably seen the videos online. BeatBeat, an AI tool, builds a flawless, full -stack software platform. Yeah, in like 10 seconds on your social feed. Right. It looks absolutely incredible. I mean, it looks like magic. But when you actually sit down at your own keyboard, beat. When you try to build something real. Oh, it is a completely different story. It is usually a very harsh reality check. Two secs silence. Welcome to the deep dive. We are really glad you are here with us
today. Yeah. Thanks for joining us. You know, the landscape of AI tools exploded in 2026. Dozens of new agentic builders launched this year alone. So many. But we want to look past the marketing hype. We are putting three of the most talked about AI builders to a direct test. Right. Side by side. Exactly. We are looking closely at NN, Claude Code, and Base 44. Yeah, we really wanted to see what happens when the rubber meets the road. So we gave all three tools the exact same
core assignment. We asked them to build an AI -powered task manager. Nothing overly bloated. Right, nothing crazy, but it needed specific functionality. It needed to be a place where users can add tasks. They needed to mark those tasks as done. And crucially, they needed an AI -generated priority ranking feature built in. So today, we find out... what they actually build for you. We track exactly how long the process takes. And we figure out which platform
actually fits your specific skill level. I mean, we want to see the real friction. The kind you will actually experience. Yeah. So before we try to build a full house, let's look at the plumbing. Right, the back end. Exactly. How do you handle the back end data securely? That is where our first tool comes into the picture. We looked at innate end. Now, we gave NAN a slightly scoped version of our core assignment. Right.
And we had to adjust that intentionally because NAN is fundamentally an open source workflow automation tool. It is brilliant, but asking it to build a graphical user -facing app just isn't fair. It is outside what the platform is designed to do. Exactly. So we asked it to build the core logic instead. We prompted it to create a workflow for our task lists. A user inputs a raw list of daily to -dos. The AI analyzes and prioritizes that list. Then, the sorted data
comes back to the user. So, we're looking at raw data movement here. You know, Dan and Ken is very famous for using a node -based builder. Right. That means a visual interface where you connect process steps together like map points. Yeah, that is a great way to put it. It's like stacking Lego blocks of data. You connect one service to another service on a digital campus. Exactly. The visual aspect makes complex data flows much easier to understand. You literally
map out the journey of your data. Like a webhook node receives the data over here. It passes it along to an AI node over there. The AI processes it. And then the output flows seamlessly into your database or a spreadsheet. You see the whole pipeline at a glance. But getting those specific blocks to click together smoothly takes real effort. Beat. I still wrestle with connecting APIs myself. Oh, totally. We all do. It can be
incredibly frustrating. You miss one little authorization header, and everything just breaks down completely. The whole pipeline just stops. Exactly. So what exactly did Ang8 deliver in our test? Well, it took about 10 minutes to complete the workflow, and it did succeed. OK, good. It successfully pushed the prioritized tasks directly into Google Sheets. The AI agent looked at the messy list and sorted it logically. But it wasn't perfectly smooth. No, the building process was definitely
not completely smooth for us. The AI's first attempt actually missed a basic input form entirely. Right. It built the sorting logic but gave us no way to actually feed the tasks into it. Yeah, exactly. We had to use another prompt to fix that oversight. And there were several runtime errors we had to solve along the way. Yeah, the data formatting was our biggest hurdle there. The JSON payload load from the AI node was not perfectly aligned with the spreadsheet node.
Right, I remember that. We spent a good portion of those 10 minutes just troubleshooting the data structures. NAN is incredibly powerful at automating complex back -end processes, but you really have to guide it through the exact step -by -step logic. It assumes you understand data schemas. It really does. So the final result was a working back -end workflow system. Yeah. But it was absolutely not a finished application. No, not at all. There was no front -end interface
for a user to interact with. There was no user login or password system provided. Right. It is not something a non -technical user could easily publish or monetize. Beat. Right. Let's talk about the cost of using this platform. Sure. So the pricing model is based mainly on your monthly workflow executions. OK. The starter plan is 20 euros a month. That gives you 2 ,500 workload executions and unlimited users. It scales all the way up to their business plan. That sits
at 667 euros a month. Wow. Yeah, that tier includes 40 ,000 executions and specific self -hosting options. Well, let me push back on this a bit. Sure. If it didn't build an actual app, why use it? Why spend the time troubleshooting JSON formatting? Because it gives technical teams absolute control over backend pipelines. OK. You know exactly where every single piece of data is going. There are no black boxes. If you already have existing services like a CRM, a database, and an email
sender, you just connect them together. Right. You are essentially building the nervous system of your business operations, you do not need it to look pretty on the outside. You just need it to route information flawlessly. Precisely. It handles the invisible heavy lifting securely behind the scenes. So it automates the backend data, not the actual user interface. Vixirate. Two -sec silence. Well, if Anand only handles
the backend pipelines, what happens next? What if you actually want the walls, the roof, and the paint? What if you want an AI to write the entire code base for a real full stack app? Then we step into the world of Claude code. Okay. This is Anthropic's major entry into the developer space. Claude code is an agentic coding tool. Let's define that. Yeah, that means an AI that writes, runs, and fixes code entirely on its
own. Let's unpack that process. You don't have to hold its hand through every single line of code. No, you don't. You accessed it through a terminal interface. Yeah. You give it a plain English prompt, and it starts working autonomously. Whoa. Imagine an AI checking its own errors without human input. It is wild. It really is. It reads your prompt. It plans the architectural build. It starts writing the actual files into your
directory. Then it runs a test. If it sees a bug in the terminal stack trace, it catches it and corrects the code immediately. It loops through this process. Exactly. That is a massive paradigm shift for software development. Well, we gave Cloud Code a A single detailed prompt for our test. We asked for a minimal task manager web app. Right. We specified that we wanted user authentication and our AI prioritization feature included. And it took about 15 minutes to finish
the entire build. Which is fast. Very fast. It returned a working app that it independently named Taskflow, and the front -end results were genuinely impressive to look at. They really were. It built a sleek, dark -themed dashboard with a very clean sidebar menu. It included a solid task input field with a functional date picker. It even added a priority drop -down menu and custom tag support. It built filter tabs so users could toggle between active, done, and
critical tasks. And it successfully integrated working user authentication into the app. But again, the experience was not entirely without friction. Building the code is one thing. Making the external services talk to each other is another. Right, the API setup. Yeah, the AI prioritization feature required manual configuration from us. Claude wrote the function, but we had to source an external API key for the AI model ourselves. We had to plug that key into the local environment
variables manually. The tool could not safely secure or provision that API key on its own. No, it couldn't. And then we hit a significant issue with actually sharing the project. Oh, the GitHub issue? Right. It attempted to push the final code base to GitHub automatically for us, but it was blocked by missing write permissions on our account. Right. And this is a crucial security mechanism. Repositories have strict
OAuth scopes. Security protocols actively stopped the AI from altering the repository directly. It did not have the required authentication token to push the code live. So it gracefully failed that step. Exactly. The app was fully built locally on our machine. It worked beautifully on local hosts. It was not shareable. No, it was not hosted on the live internet. We would have to configure those deployment settings and SSH keys manually ourselves. The pricing for Claude Code is fairly
straightforward right now. It is $20 a month for the pro plan. Right. That seems to be the practical starting point for most active developers utilizing these agentic workflows. But I have to ask, this sounds amazing. But isn't it still just for seasoned developers? Honestly, yes. It really does require existing code base and API management skills. You need to know how environment variables actually work in a local directory. You need to understand how to read and fix GitHub
permission errors when they pop up. Claude code builds the application code itself, but you still have to manage the surrounding infrastructure. Great for developers, but brings its own technical setup hurdles. Precisely. You have to be deeply comfortable navigating a terminal environment. Two sec silence. So we've seen backend automation with NAAN. We've seen local code generation with Claude code. Both of those paths require a distinct level of technical comfort. You have to understand
data structures or terminal commands. Definitely. But what if you just want to skip the infrastructure entirely? What if you just want to ship a live product right now? That is where our third tool, Base 44, enters the conversation today. OK. Base 44 is designed specifically for non -technical builders and founders. It creates full stack web applications entirely from plain English descriptions. And crucially, it handles everything
inside one single unified platform. You know, there is some really interesting business context behind this specific tool. Base 44 was actually acquired by Wix back in June of 2025. Right. They bought the platform for approximately $80 million. million dollars. Which is a huge deal. It is, but it still operates under its own name and domain today. It has not been heavily rebranded into the main Wix ecosystem. Yeah, that is interesting. Well, we gave Base 44 the exact same task manager
assignment. We asked for the user interface, the filter tabs, and the AI sorting button, and the results were incredibly fast compared to the other platforms. Very fast. It took just under five minutes from a single prompt to a finished product. It built a live, complete web app that it named Zenith Tasks. And the experience was remarkably frictionless from start to finish. Completely. Let's talk about the setup. It handled the user authentication automatically at the
platform level. Great. We did not even need to prompt it to build a login screen. It just knew an app needs secure logins. And because it operates in a closed ecosystem, the built -in AI connected perfectly without any external setup. Which is huge. Yeah. There was no need for us to hunt down an external open AI key. There were no complex environment variables to configure locally. There were no GitHub permission issues blocking the deployment process. The hosting was handled entirely
inside the base 44 platform itself. It leverages that massive under underlying hosting infrastructure. Exactly. The resulting interface was polished. It had clear, active, and done tabs for organizing the tasks. It featured satisfying visual strikethroughs for all your completed items. And it placed a very prominent AI prioritize button. Right in corner. Yeah, that button was great. You just click the button, the app thinks for a second, and the list sorts itself immediately based on
urgency. And the app was live immediately. It was previewable and ready to publish instantly. You just copy and share the URL and people can start using your software. The pricing model makes it very accessible for rapid prototyping and testing ideas. It is completely free to start building on the platform. If you want more features, the starter plan is $16 .90 a month billed annually. Sounds incredibly smooth. But let's look at the reality here. If it's this fast and it handles
all the hosting, what are you sacrificing? Well, you are definitely making a fundamental trade -off here. You trade underlying code ownership and custom architecture for pure speed. Okay. You are locked into their specific ecosystem. You cannot easily export the React code base and host it elsewhere like Vercell or AWS. Right. You are tied to their proprietary infrastructure and their database decisions. Fastest to launch, but you do not own the underlying code. Exactly.
You are essentially renting the infrastructure to get your idea live instantly. Let's pause right here. Insert provided mid -roll sponsor read here. Do not pull any promotional material from the newsletter text. And we are back. All right. Let's synthesize everything we have covered in this deep dive today. The landscape of AI tools is evolving incredibly fast. It really is. But testing these three specific platforms
in 2026. is very revealing. Choosing an AI agent tool isn't just about which AI model is technically the smartest anymore. No, it really isn't. The raw intelligence of the major models is somewhat commoditized now. They can all write decent code. The real choice you have to make is about your appetite for infrastructure. It is about how much technical setup and maintenance you are actually willing to handle. You have to match the tool to your own operational capabilities.
Let's break down the core takeaways for you based on this experiment. Sure. If you need to connect existing tools together efficiently, you should use NAN. It gives you ultimate granular control over your backend data flows. It is the absolute clear winner for automating repetitive, invisible backend processes. Right. You just have to be comfortable working with visual logic nodes and troubleshooting data payloads. And if you want full ownership of a custom code base, use Cloud
Code. Yes. It gives you a real exportable, full stack application environment that you... completely control. But you just have to accept some setup friction along the way. You have to manage your own API keys. You have to manage your repository permissions. But at the end of the day, you own every single line of that final generated code. And finally, if you just want to turn an idea into a live URL immediately, use Base 44. Yeah. It is perfectly designed for founders who want
to move incredibly fast. You skip all the complex infrastructure decisions, you deploy a working product in minutes, you sacrifice total code -based ownership, but you gain immediate market validation. And sometimes speed is the most important feature. It is time to put this knowledge into practice today. Pick just one of these tools that matches your skill level right now. Do not try to learn all three platforms at the exact same time. Try building a very simple one page
project this weekend. Yeah. Keep the scope incredibly small for your very first attempt. Right. Build a habit tracker or a simple form. Experience the workflow firsthand and see exactly where you personally encounter friction. Two sec silence. I want to leave you with a final thought to consider. Platforms like Base 44 can spin up fully hosted, authenticated web apps. They do it in five minutes
from simple, plain English prompts. The authentication, the database routing, and the UI are all handled perfectly for you. So what does it actually mean to be a developer in the future? Us. If these tools... handle all the underlying code generation for us is the most valuable technical skill in the world, simply knowing exactly what to ask for. Thank you for joining us on this Keep Dive. Keep questioning, keep exploring, and we will see you next time.