How I Turned an Ugly Spreadsheet into an AI Assisted App with Antigravity

I have a confession to make. Up until now, I wasn’t that much into “vibe coding.” I used AI all the...

I have a confession to make.

Up until now, I wasn’t that much into “vibe coding.” I used AI all the time for Python coding, but I never really built a whole app from scratch in a language I knew nothing about.

That changed today. I encountered a really annoying problem: I had to review a massive amount of talk submissions for a conference. We’re talking about a massive spreadsheet. Staring at those tiny cells was literally making my eyes hurt.

My initial thought was, “Hey, let’s create a really sharp UI for the submission review.” But then I thought, why stop there? Why not let AI provide me valuable inputs from social media to help me with the review itself?

So, I decided to build TalkScout. And since I wanted to test drive Google Antigravity (Google’s new AI-powered coding agent), I figured this was the perfect opportunity.

Here is how I went from a painful CSV to a fully deployed Cloud Run app-without writing a single line of React code myself.

Step 1: The “Meta-Prompt” (Asking Gemini to Talk to Antigravity)

I didn’t start by coding; I started by chatting. I used meta-prompting to get started.

So, what is meta-prompting, you may ask? It’s actually when you go to Gemini 3 and ask it to write the prompt for the coding agent.

I explained my problem to Gemini 3 in simple words. Gemini 3 acted as my architect. It turned my “brain dump” requirements into a technical spec, defining the component structure and data model. I didn’t have to guess the right words, I just pasted that polished spec into Antigravity.

Step 2: Ditching the Spreadsheet for a Dashboard

With that prompt, Antigravity built the app of my dreams. It allowed me to:

• Upload the CSV with all the conference talks.
• Get a dashboard showing the status of each talk.
• See a beautiful, high-contrast UI to review abstracts and demo plans without squinting at cells.

The “Vibe” Fix: It wasn’t all smooth sailing — I actually hit a nasty React hydration error. This can take hours to debug, especially if you’re not a frontend developer… But I simply provided the error message to Antigravity and the coding agent pinpointed the mismatch in the DOM and fixed it in minutes.

Step 3: Integrating Grounded Intelligence

I didn’t just want a UI; I wanted to overcome my own bias. How do I know if a niche topic is actually hot?

I added a button to get an AI Assessment. But I didn’t want hallucinations. I used Google Search Grounding so the AI could search through Reddit, X (Twitter), and LinkedIn for real-world developer signals. That provided me inputs based on the current developer audience mindshare.

Step 4: Calibrating the “Strict” Reviewer

Initially, the AI was way too nice. It was giving high scores to anything with trendy keywords.

I used what’s called few-shot prompting to calibrate it. I gave examples of my scores vs. its scores and introduced what I call the “Marketing Fluff Penalty”.

• If a submission reads like a documentation/marketing page? Points docked.
• If the submission was way too short? We capped the score at a hard 2.
• If it includes war stories and actual learnings — increase rating. After a few examples, it became more calibrated to my taste.

Step 5: The Pivot to Batch Mode

I realized it was taking me too long to ask the AI to evaluate each talk individually while I reviewed it.

So, I asked Antigravity to refactor the backend for Batch Mode. Now, TalkScout processes the entire submission pool in the background. By the time I grab a coffee, the “AI Draft” column is full of insights, allowing me to focus only on the final decisions.

Step 6: Sharing the Goodness (Deploy to Cloud Run)

TalkScout was working great for me, but I thought, “It would be great to share this with the other reviewers.”

This is where Antigravity really showed off. I simply asked it to deploy the app. It automatically recognized my Google Cloud Project ID, handled the containerization, generated the exact deployment commands, and deployed it to Cloud Run.

One simple ask, and minutes later, I had a URL to share with the team.

It Was Pretty Fun!

It was pretty fun to actually solve a real problem I had using Antigravity and vibe coding. I built a tool that handles ingestion, provides a distraction-free rating interface, and provides valuable inputs for my reviews.

I would love to hear from you all - have you recently solved a problem using vibe coding?

If you haven’t already - try playing around with Antigravity and easily deploy your apps to Cloud Run.