How I Vibecoded a FREE E-commerce Store With Google Antigravity (No Code No Subcription)

Take a look at this. The entire custom e-commerce store was built with free Google AI tools, premium product visuals, AI lifestyle mockups, and

secure checkout. And not just that,

secure checkout. And not just that, check these ad creatives and ad carousels. Looks great, right? And this

carousels. Looks great, right? And this

is a full e-commerce system running end to end. And we created it all for free.

to end. And we created it all for free.

So, most people still think launching a real store means expensive apps, designers, and subscriptions stacking up before you can make your first sale. But

in 2026, Google's AI ecosystem replaces that entire tech stack. With tools like Noble LM and Gemini, you can plan, design, launch, and optimize [music] a

storefront for zero monthly cost like no coding required. And by the end of this

coding required. And by the end of this video, you have a launch ready e-commerce store AI system you can actually build yourself. To be honest, e-commerce [music] is more crowded than

ever before. And the winners right now

ever before. And the winners right now are not just the prettiest stores, but they are also the most efficient. And

it's already 2026. Of course, more and more people are shopping online. And AI

tools and large language models like Gemini 3.0 O and Opus 4.5 are actually becoming more capable than ever. [music]

And that shift is really huge because it means nontechnical beers can actually now have access to the same infrastructure big brands use. So if you

know how to wire all together, this is so powerful for you. The old way was messy, right? You would stack a bunch of

messy, right? You would stack a bunch of paid apps, hire freelancers, juggle disconnected tools. And it was

disconnected tools. And it was expensive, overwhelming, and built for teams, not for solo founders trying to launch something real. And today we are

going to replace that with a single integrated system. And we will use Noble

integrated system. And we will use Noble Allen for research, Gemini for strategy, Nano Banana for onbrand assets, and anti-gravity for development. And by the

end of this video, you will actually have a serial subscription AI e-commerce workflow that you can actually build yourself using beginnerfriendly [music]

no code tools. Okay, so let's get started. First thing first, we validate

started. First thing first, we validate before building. Right, we are using

before building. Right, we are using Noble LM as our research engine to find real e-commerce opportunities based on evidence, not guesses. So first let's

click the search field and type something like e-commerce in 2026 and once you are done entering your keywords then hit enter. No element will then

gather comprehensive sources and because we selected deep research and this may take some time but it also means that we get better sources. So after some time

it's done looking up sources and let's go ahead and tell the AI about what we are building and a targeted question like what profitable e-commerce niches

are performing well and again we can hit enter. So Nobel LM will analyze only

enter. So Nobel LM will analyze only your collected sources which reduces hallucination [music] and keeps answers grounded and you'll get a list of niches

with real context like trends, behaviors and opportunities. So from here you can

and opportunities. So from here you can just review Nobel LM's research and pay attention to patterns. Are certain

categories repeatedly mentioned. Um do

you see emerging behaviors or underserved markets? And this is where

underserved markets? And this is where you start forming your direction. Okay.

And a [music] common mistake is treating the first answer as final. But instead

we should ask follow-up questions and dig deeper. And you are shaping strategy

dig deeper. And you are shaping strategy not just collecting ideas. This is why Nobel LM is so useful at the research stage. Once your sources are added,

stage. Once your sources are added, every insight is anchored to them and that gives you confidence that what you are seeing is evidence-based. So

therefore, you can honestly spend real time here refining your understanding before committing to anything. So we

have transformed raw web information into actionable market intelligence. So

next we are going to take what we learned here and start turning that validated direction into something concrete we can actually build. But

before we start creating we have to plan first right and that's when Gemini comes in. So now we are in Gemini and this is

in. So now we are in Gemini and this is where we start planning the actual build like how our e-commerce landing page should look feel and function. So first

we click the plus button and select notebook LM and then we can [music] choose the notebook we used earlier for research. This step is critical because

research. This step is critical because by connecting it Gemini now has access to the same knowledge base we validated and that means planning becomes

consistent and you and the AI are literally working from the same information. So now let's ask Gemini to

information. So now let's ask Gemini to help us plan our brand identity and strategy based on the name we already thought of earlier. So we can type that in and hit enter. And after a few

seconds, Gemini gives us a detailed response. And because Noel LM is

response. And because Noel LM is connected, these recommendations are not random. They are actually grounded in

random. They are actually grounded in the same research we used. [music] And

that consistency is what makes this workflow powerful. You're not planning

workflow powerful. You're not planning from scratch and hoping that the AI understand your intent, right? You are

working on [music] validated insights.

So if you want to tweak the output or add specifics, adjust tone, refine positioning, etc., go ahead. This is

your [music] brand. Like you can tweak it until it feels right for you. So once

you are satisfied, we can ask Gemini to generate a PRD or recorded project requirement document and a boiler plate.

And this will serve as our blueprint when we move into development. So clear

structure now means faster more focused execution later. And just like that we

execution later. And just like that we now have the PRD that reflects our brand identity we created. From here you would want to copy these into a Google

document and download it as a mock down or recorded MD file so that we can use it in the next [music] phase. So next we can just take this foundation and start

building the actual landing page. All

right. So we are now ready to start building our e-commerce landing page and we will use Google anti-gravity ID for that. So inside a fresh project we can

that. So inside a fresh project we can go to the agent chat box and type in what we are building and we can ask it to use the boiler plate and PD we

generated earlier. And before you hit

generated earlier. And before you hit enter, place the PRD that was saved as an MD file into the project folder. And

then you can click generate. And after a few seconds, the agent actually gives us this [music] implementation plan. And

this aligns exactly how it plans to execute the PRD. So right now, we could give it the go signal and let it start writing the code. But for us, we would

like to install some anti-gravity agent skills before executing builds. And to

be honest, this step is not mandatory.

You can actually proceed without it. But

here's what skills do. They actually

give the agent specific knowledge and best practices for handling certain tasks. It's like giving it a playbook.

tasks. It's like giving it a playbook.

And honestly, it's a powerful tool to utilize if you want cleaner, more intentional output. So with our landing

intentional output. So with our landing page created, the next thing we need to do is generate mock-ups for our apparel, right? So, first we can ask the agent to

right? So, first we can ask the agent to give [music] us a list of product names in our catalog. And we can type that in and hit enter. And once we get the product names, we are going to ask it to

create prompts for us based on the established PRD. And we can just copy

established PRD. And we can just copy those prompts and then run them in Google Whisk. And that's it. We now have

Google Whisk. And that's it. We now have our first mockup done. Let's do the same for the rest. So, here's how our mockups look. As you can see, Nano Banana is

look. As you can see, Nano Banana is really great at creating product shots.

And now we have our images. We can just simply download the ones you want to use. And after downloading, we can drop

use. And after downloading, we can drop them into anti-gravity and ask the agent to swap the placeholders using the mockups we just made. Simple as that.

But before you check them out first, let's generate more mockups to use for the product galleries on each individual product page. Just like earlier, we

product page. Just like earlier, we simply asked the agent to create the prompts, and it gave us this. So this is how our mockups look. To be honest, Nano

Banana is insane. So let's just go ahead and load them into anti-gravity and we [music] can get the product pages and galleries set up and wait for the agent

to write all the code for us. All right.

So once everything is done, we can just check out the death server again. And

maybe you can take a look at this. Our

hero section looks really, really good right now with the placeholders replaced and the mock-ups bring the whole page to life, right? It actually feels like a

life, right? It actually feels like a real brand now, not just a wireframe anymore. And if you check the product

anymore. And if you check the product pages [music] the gallery also looks really good. The

layout flows naturally. The images are clean. And honestly, this is starting to

clean. And honestly, this is starting to feel like something you would see from an established store. And the

consistency between the mockups and the design language makes a huge difference here. And this is the kind of output

here. And this is the kind of output that makes the whole workflow worth it.

Right? Think about this. We went from research to planning to a fully functioning landing page with custom product officials. And we did it

product officials. And we did it systematically, not by guessing.

Everything is connected and everything is intentional. And next, all we need to

is intentional. And next, all we need to do is to set up our database, secure checkout, and then polish the final details and get this thing ready to ship. Okay, let's get ready. We are

ship. Okay, let's get ready. We are

going to set up our database now. And

this is where we put our [music] product details and user O. And it's very simple to set up. So, first we are going to create a new Superbase project. And

next, [music] we can just copy the project URL and your anonymous key. Both

of these go into an ENV file which means you should not share this with anyone.

All right, keep them secure. And once

you have your keys, we can just go to integrity and ask it to set up superbase. And this is actually already

superbase. And this is actually already in our PLD. So it has been taken care of earlier. And once you get your SQL

earlier. And once you get your SQL schema, we can just copy [music] it and then open base again. We can go to the SQL editor and run the query. And once

that's done, your orth and database should now be fully set [music] up. And

next, we are going to set up a secure checkout with Stripe. And to do this, we are going to Stripe and get your secret key and publishable key. And once you

have those, we can open anti-gravity and ask the agent to set up Stripe checkout.

And normally a good way to do this would be pulling the Stripe document and pasting it into the agent chat box, but we do not need that here because it's

already in our PRD and the agent already set it up earlier. So now we just [music] need to ask it to finish the setup. And once the agent is done, we

setup. And once the agent is done, we can just simply enter your API keys and you're good to go. So now everything is ready and let's just test the O and check up on our landing page before we

deploy it. And just [music] like that,

deploy it. And just [music] like that, it works. Signups flow smoothly, lock in

it works. Signups flow smoothly, lock in is instant, and the Stripe checkout processes without issues. And this is the moment where all the planning,

research, and systematic building pays off. We did not do it by hoping. We

off. We did not do it by hoping. We

built it systematically. And that's why it worked. Clean integration, functional

it worked. Clean integration, functional features, and a polished user experience. And this is production

experience. And this is production ready. So we started with just an idea

ready. So we started with just an idea and now we have built a complete AI powered e-commerce system. So we used Noble LM and Gemini shape strategy, Nano

Banana to generate on brand assets and creatives anti-gravity [music] to build our front and back end. And remember

that is not just a demo. That's a launch ready workflow that takes you from planning to real world execution. And

that's the big takeaway here. The real

power is not [music] any single AI feature. It's how all these tools work

feature. It's how all these tools work together. So when strategy, visuals,

together. So when strategy, visuals, infrastructure and analytics are connected [music] you are no longer building like a solo beginner. You are actually operating

beginner. You are actually operating like a full team. And that shift from casually using AI to intentionally building with an integrated system is

what unlocks professional results. And

that means going forward you are not guessing anymore. You now have a zero

guessing anymore. You now have a zero subscription framework. You can reuse,

subscription framework. You can reuse, remix and scale. You can actually validate ideas faster, launch cleaner storefronts and iterate based on real

data. [music] And that's a really huge

data. [music] And that's a really huge advantage. And we are really excited to

advantage. And we are really excited to see what you're going to build next. So

if you want to go even deeper and that's exactly what we're doing inside our any no code premium community because we break down more real world AI workflows

focus on how to make more money with these tools and you'll be learning alongside professional founders and builders. And of course you can also

builders. And of course you can also have access to our AI website design course that can help you implement things faster. So if you found this

things faster. So if you found this video helpful please drop a like and subscribe for more product AI builds in the future. I'll see you in our next

the future. I'll see you in our next