The Speed of AI-Assisted Development: From Python to Infrastructure in Minutes

The Speed of AI-Assisted Development: From Python to Infrastructure in Minutes

I’ve been experimenting with AI coding agents recently, and the speed at which I can move between different layers of the stack is mind-blowing. Today, I sat down with an AI agent (Google Antigravity in my case but can be any like Cursor or Claude Code) to tackle a laundry list of tasks that would normally take me half a day. We finished them in under an hour.

Here’s a breakdown of the “flow” and what we accomplished in a single session.

1. Fixing Legacy Code (Python/AWS Lambda)

I started with a bug in the email forwarder for cloudyeti.io, my personal cloud project. It was sending emails as attachments instead of inline text.

  • The Task: Modify a Python Lambda function to parse MIME parts and reconstruct the email body.
  • The AI’s Role: I didn’t have to look up the email.message library docs or remember how to traverse multipart payloads. The agent just wrote the code, zipped it, and updated the Lambda function.

2. Debugging CI/CD Pipelines (GitHub Actions)

Next, I switched context completely to blog.bipratech.com, a site for my dad’s company. The deployment workflow was stuck.

  • The Fix: The agent identified we were using an old macOS runner and switched it to ubuntu-latest. It also fixed a subtle S3 bucket naming error and removed a deprecated ACL flag that was causing the build to fail.
  • The Result: A green build and a successful deployment to CloudFront.

3. Frontend & Design (Saurav.io)

Then came the creative part. I wanted a new, sleek portfolio for saurav.io.

  • The Build: I gave the agent a rough idea (“minimalist, dark mode, sleek”). It generated a single-page HTML/CSS site with a premium feel, “Inter” typography, and a responsive design.
  • The Deployment: We synced it to S3 and invalidated the CloudFront cache.
  • The “Oops” Moment: I realized the site wasn’t updating. The agent investigated Route53, found that saurav.io was actually pointing to a different S3 bucket (sauravsharma.net), and corrected the deployment target instantly.

4. Rapid Iteration

Finally, I wanted to tweak the content—remove the fluff, keep it minimal (“Cloud Technologist • AI Builder • Indie Musician”), and add a profile picture.

  • The Speed: These changes happened in seconds. No context switching, no “where is that file again?”, no “what’s the CSS for a circular image?”. Just intent -> execution.

The Takeaway

Tools like Google Antigravity, Cursor, and Claude Code aren’t just “autofill” anymore. They are context-aware collaborators. They allow me to be a “Cloud Engineer” one minute, a “DevOps Engineer” the next, and a “Frontend Designer” right after.

The bottleneck is no longer writing the code; it’s having the clarity of what you want to build. When you have that, the AI handles the rest.