I Built a Complete Cloud Solution Just One Prompt — Here’s How Google Antigravity Changed Everything
Hello friends! 👋
I just explored Google’s brand new Antigravity platform, and I have to tell you — I’m genuinely excited to share what I discovered!
You know that feeling when you have a great idea but then think about all the work involved — writing code, setting up infrastructure, testing everything, fixing bugs… and you’re like “ugh, this is going to take forever”? Well, what if I told you that you could just describe what you want to build, and an AI would handle everything from start to finish?
That’s exactly what I just experienced, and honestly, it felt like getting a sneak peek into the future of software development!
Let me share my journey where I built a complete, ready-to-use serverless web app & data pipeline on Google Cloud Platform — and I did it with just ONE prompt. I used Google’s brand-new AI development tool called Antigravity, which is powered by their smartest AI model yet, Gemini 3.
Trust me, what happened next blew my mind, and I can’t wait to walk you through it! 🚀
Want to know what’s crazy? From designing the architecture to creating a brand new GCP project, writing frontend code, building backend APIs, setting up BigQuery schemas, managing all the security roles and permissions, AND testing the entire UI with documented results — ALL of this happened with just ONE single prompt!
Yeah, you read that right. One prompt. 🤯
How did all this magic happen? Well, meet the two superheroes behind this: Google’s brand new Antigravity platform and their latest genius AI model, Gemini 3! Let me introduce you to these game-changers.
Meet Google Antigravity: A New Way to Build Software
Antigravity is what Google calls an “agent-first development platform.” Think of it less like a helpful coding buddy and more like having a smart software engineer working with you. The platform gives AI agents direct access to three important tools: your code editor, your terminal, and your web browser. This means agents can plan tasks, write code, run commands, deploy apps, test them, and even check their own work — all without you holding their hand every step.
The platform is built on VS Code, so it feels familiar to developers right away. But where it really stands out is how it changes the developer’s role. You’re no longer just writing code line by line — you’re working as an architect, guiding smart agents that do the heavy work while you focus on the big picture.
Gemini 3: The Smart Brain Behind It All
What makes Antigravity so powerful? That’s Gemini 3 — Google’s smartest AI model yet, and the results speak for themselves.
Gemini 3 isn’t just a little better; it’s a big jump forward in how AI thinks and understands different types of information. It shows expert-level thinking and got top results on almost every major AI test. We’re talking about a model that can understand tricky contexts, pick up on small details, and think through problems step by step with great accuracy.
But here’s what really matters for developers: Gemini 3 is great at what Google calls “vibe coding” — taking simple descriptions in everyday language and creating full, interactive web apps.
What makes Gemini 3 special is how deeply it can think. The model doesn’t just create code; it understands what you want, thinks about possible problems, remembers context throughout long conversations, and can even explain why it made certain choices. When you combine this with Antigravity’s smart agent system, you get a development experience that feels less like programming and more like working with a really smart teammate.
My Challenge: One Prompt to Do Everything
Alright, enough talk. Let me show you what this actually looks like.
I decided to test Antigravity’s power with a big challenge: build a complete, end-to-end serverless data pipeline on Google Cloud Platform. But here’s the twist — I wanted to do it with just one well-written prompt.
Here’s exactly what I asked for:
“Build a complete, cost-effective, serverless data pipeline solution that retrieves product data from the public API https://fakestoreapi.com/products and loads it into BigQuery. The solution should include: Creating a new GCP project, Setting up a BigQuery dataset and table, Designing a managed/serverless data pipeline for ingestion, Building a web application to display the ingested BigQuery data along with product images — make it modern and polished. Add a header with a logo and title, apply a clean color theme, and improve spacing and styling. Display products in card layout with mock images. Add a simple search bar and sorting options. Ensure the UI is responsive and visually consistent. Use Nano Banana to generate product images. After deployment, perform end-to-end validation, including: Application functionality testing, BigQuery data verification, Pipeline run status checks, Data quality checks. Finally, create High Level Architecture diagram and publish the resources created and test results as part of the final output.”
That’s a lot to ask, right? Normally, this would take days or weeks of work with multiple people, countless terminal commands, config files, debugging, and lots of testing.
Watching Antigravity Do Its Thing
What happened next was really cool to watch. The Antigravity agent didn’t just start coding right away. It started by thinking through the problem step by step — exactly like an experienced engineer would.
Step 1: Getting Ready
First, it checked what tools were on my computer. Did I have Terraform? Python? The needed GCP tools? When it found missing stuff, it didn’t ask me to install them — it just did it on its own. Downloads started, missing pieces were added, and in moments, everything was ready to go.
This might seem small, but anyone who’s dealt with “it works on my computer” problems knows how valuable automatic setup is.
Step 2: Planning and Design
Here’s where Gemini 3’s smart thinking really showed. The agent created a detailed task list, breaking down my big request into smaller, manageable pieces:
It even made a clear architecture diagram showing how all the pieces would work together. Before writing any code, I could see the whole solution.
Step 3: Writing Infrastructure Code
Watching the agent write Terraform code was really cool. It didn’t just create basic templates — it followed Google Cloud best practices for:
- Clear resource naming
- Security settings (IAM roles, service accounts)
- Network safety where needed
- Keeping costs low (serverless setup, smart data storage)
- Good organization and labeling
The Terraform files were clean, easy to read, and ready for real use. It created separate files for variables, main setup, and outputs — exactly how experienced cloud engineers do it.
Step 4: The Allowlist/Denylist Feature — You Stay in Control
Here’s one of Antigravity’s smartest features: the allowlist and denylist system. This lets you control what the agent can do on its own versus what needs your OK.
For my project, I set it up like this:
Allowlist (Work freely):
- terraform init – Safe step, just sets up the working folder
- terraform plan – Read-only step that shows what changes will happen
- Opening URLs for testing — Needed to check if things work
Denylist (Ask me first):
- terraform apply – This actually creates/changes cloud resources and costs money
- Any steps that delete or destroy things
- If command is not in allowlist bydefault ask for approval.
This meant the agent could move fast through safe steps, but stopped to get my clear approval before making any changes that would affect my actual GCP setup or cost money. This balance of speed and control is exactly what teams need.
Step 5: Building the Code
With infrastructure ready and approved, the agent started building the actual app:
Data Pipeline Code:
- Created Python Cloud Functions to get data from the Fake Store API
- Added error handling and retry logic
- Set up BigQuery client with proper security
- Designed smart ways to insert data
Web Application:
- Built a modern, mobile-friendly frontend
- Created a clean, polished UI with:
- Professional header with logo
- Card-based product display
- Search bar
- Sorting options
- Works great on phones and computers
The code quality was really good — well organized, following best practices, and with helpful notes.
Step 6: AI-Generated Product Images with Nano Banana
Here’s where it got really cool. For product images, the agent used Nano Banana, Google’s image creation model. Instead of using placeholder images or links from other sites, it created custom product images that matched each item’s description.
Watching it call the image creation tool, get the images, and add them to the web app was like watching a skilled developer work through a tricky task — except this happened in minutes, not hours.
Step 7: Deployment and Testing
This is where Antigravity really stood out from regular development. The agent didn’t just write code and stop. It:
- Set up the infrastructure using the approved Terraform setup
- Put the app code online to Cloud Run or Cloud Functions
- Started the data pipeline to get and load first batch of data
- Checked BigQuery data by running queries to make sure data looked good
- Opened the web app in a browser
- Tested the UI by trying search, sorting, and other features
- Took screenshots of each feature working
- Made video recordings showing the app in action
- Created test reports documenting everything that worked
All of this happened on its own. The agent opened Chrome by itself, used the app, took screenshots, and even recorded videos — all as proof that I could check to make sure everything worked right.
Step 8: Documentation and Final Results
When everything was done, Antigravity gave me a complete set of results:
- Infrastructure Code: Well-organized Terraform files
- Application Code: Frontend and backend files
- Screenshots: Visual proof of working features
- Video Recordings: Walkthroughs of the app in action
- Test Results: Detailed reports on what was checked
- Deployment Logs: Complete record of what was created and where
Everything was neatly organized, making it easy to review, share with team members, or hand off to operations.
Humans Are Still Very Important
Now, before this starts sounding like “AI will replace developers,” let’s be clear — that’s not what’s happening.
What’s changing is the type of work we do, not the need for humans.
Think about calculators.
When they arrived, they didn’t replace mathematicians or accountants — they removed repetitive manual calculation so humans could spend more time on logic, strategy, creativity, and decision-making.
AI tools like Antigravity are the modern calculator for software development.
They automate the repetitive parts — boilerplate code, setup, integrations — so developers can focus on architecture, innovation, user experience, and solving real problems. I:
- Decided what was needed and what limits to set
- Reviewed and approved cloud changes
- Checked that the solution met my needs
- Made tough choices on trade-offs
- Made sure the final product matched business goals
The agent was very capable, but it still needed human thinking, real-world knowledge, and decision-making power. The difference is that my time was spent on high-value work instead of boring repetitive tasks.
What I Learned and Tips for You
If you’re thinking about trying Antigravity yourself, here are some tips from my experience:
Write Clear, Complete Prompts
The better your first prompt, the better the results. Include:
- Specific technical needs
- Quality expectations (modern, polished, mobile-friendly)
- How to check if it works
- What you want to see at the end
Use Allowlist/Denylist Smartly
Start careful — ask for approval for anything that costs money or makes permanent changes. As you trust it more, you can let it do more on its own.
Check Results Carefully
The screenshots, videos, and test results are there for a reason. Take time to look at them before saying a task is done.
Keep Improving
Don’t expect perfect results on the first try. Think of the agent’s output as a strong first version that you can improve with more instructions.
Know What’s Happening
Even though the agent can work on its own, it’s important to understand what it’s building. This helps you maintain, change, and fix the solution later.
Looking Ahead: The AI Agent Era
Google’s release of Antigravity, powered by Gemini 3, signals a notable shift in how we think about software development. We’re moving from “AI assists with coding” toward “AI can assemble full solutions while humans review, refine, and steer.”
It’s still early — features are evolving, reliability will improve over time, and there are moments where human intervention is absolutely required. But the direction is clear.
This isn’t just about speed. It’s about accessibility. Tools like this make it easier for more people to build and test ideas. Someone who understands a business problem but doesn’t write code can now describe what they need and get a usable starting point.
For experienced developers, the role shifts upward. Instead of spending time on repetitive tasks or boilerplate logic, we can focus more on architecture, reasoning, user needs, and higher-level decision-making — the parts AI still struggles with.
The Verdict: Promising, But Early
I went into this experiment curious — and honestly, a bit skeptical. Could an AI agent truly build an end-to-end workflow? Would the results be production-worthy? Would it save time, or would reviewing and fixing code create new overhead?
The outcome was encouraging. Gemini 3 combined with Antigravity generated a functional, tested solution faster than I could have manually — and with fewer structural errors than expected.
Is it perfect yet? Not at all. Common issue I observed when left idle for longer time is Agent stuck in processing & loading state
Does it require review, refinement, and guardrails? Absolutely.
But the shift is noticeable: from hands-on coding to solution guidance, from implementation details to system-level thinking.
Ready to Try It Yourself?
Google Antigravity is available now for free (in preview) for individuals, and works on macOS, Windows, and Linux. If you’re a developer, I really encourage you to try it yourself. Start with a small project, get comfortable with how it works, and slowly tackle bigger challenges.
The future of development isn’t about AI replacing developers — it’s about developers working with smart AI agents to build better software, faster. And having tried it myself, I can tell you: that future is already here.
Watch My Live Demo
Want to see all of this in action? I’ve created a complete video walkthrough showing the entire process from start to finish. Watch how Antigravity and Gemini 3 built this complete data pipeline solution with just one prompt:
🎥 Watch the Full Demo Video Here
https://medium.com/media/2deee0900810f83198a2c3239ce3d0c3/href
In the video, you’ll see:
- The complete prompt I used
- Antigravity planning and creating the architecture
- Live infrastructure deployment with Terraform
- The agent writing and testing code
- AI-generated product images with Nano Banana
- End-to-end testing and validation
- Screenshots and recordings the agent captured
- The final working application
Have you tried Google Antigravity or other AI development tools? I’d love to hear about your experiences in the comments below. What projects are you planning to build with this new approach?
Resources
- Google Antigravity: antigravity.google
- Gemini 3 Documentation: Google DeepMind
- Getting Started Guide: Google Codelabs — Antigravity
- Developer Documentation: Google AI Studio
Disclaimer: This blog represents my personal experience and opinions. Google Antigravity is currently in preview as of today (27th November 2025), and features/capabilities may evolve.
About Me
As an experienced Fully certified (12x certified) Enterprise Architect, Google Developer Expert (GDE), with over ~10 years of expertise in Google Cloud Networking,Data ,Devops, Security and AI/ML, I am passionate about technology and innovation. Being a Google Developer Expert(GDE) and Google Cloud Architect, I am always exploring new ways to leverage cloud technologies to deliver innovative solutions that make a difference.
If you have any queries or would like to get in touch, you can reach me at Email address — vishal.bulbule@techtrapture.com or connect with me on LinkedIn at https://www.linkedin.com/in/vishal-bulbule/. For a more personal connection, you can also find me on Instagram at https://www.instagram.com/vishal_bulbule/?hl=en.
Additionally, please check out my YouTube Channel at https://www.youtube.com/@techtrapture for tutorials and demos on Google Cloud.
I Built a Complete Cloud SJust One Prompt — Here’s How Google Antigravity Changed Everything was originally published in Google Cloud – Community on Medium, where people are continuing the conversation by highlighting and responding to this story.
Source Credit: https://medium.com/google-cloud/i-built-a-complete-cloud-sjust-one-prompt-heres-how-google-antigravity-changed-everything-5b4d35432a57?source=rss—-e52cf94d98af—4
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