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.