Meet the AI Assistant That Guards My Portfolio

Source: Dev.to

This is a submission for the New Year, New You Portfolio Challenge Presented by Google AI

About Me

Hi everyone! I’m a Software Engineer based in Bangladesh with over 3 years of experience specializing in Java and Spring Boot.

I currently work at Technonext (a sister concern of US‑Bangla Airlines), where I lead a small team building complex backend architectures for a ride‑sharing application similar to Uber. While my “home base” is backend engineering with some Angular on the side, I believe a modern developer should never stop learning.

This challenge pushed me to dive into Google Cloud Platform for the first time — and I’m glad it did. Deploying to Cloud Run, configuring containers, and integrating Gemini AI opened up a whole new world.

Beyond the tech, I wanted my portfolio to have personality. Not just another skills grid and project list. Something that talks back.

Enter DS‑7 — an AI assistant that knows my entire career and adapts its tone based on who’s asking. Recruiters get professional answers. Developers get witty terminal responses.

This portfolio represents that journey — combining my backend roots, frontend skills, and the power of Google’s AI tools.

Portfolio

💡 Pro tip: Click the pulsing terminal icon in the bottom‑right corner. Try typing ls, sudo, or just ask “Why should I hire him?”

(Note: The embedded site above is live on Google Cloud Run. Click the chat icon to ask the AI about my skills!)

How I Built It

1. The “AI‑First” Development Process

This project was born in the cloud.

• Starting with Antigravity: I used Google Antigravity, Google’s AI‑first development environment, to generate the initial project structure. It instantly set up the boilerplate for a Spring Boot backend and Angular frontend, saving me hours of setup time.
• Refining with Gemini: Once the foundation was laid, Gemini served as my primary co‑pilot. I relied heavily on it to “furnish” the project—refining the TypeScript logic, debugging Docker networking issues, and optimizing the Spring Security configurations.

2. The Tech Stack

• Frontend: Angular (built as a responsive SPA)
• Backend: Spring Boot (Java 17)
• Containerization: Docker (multi‑stage builds)
• Cloud: Google Cloud Run (serverless deployment in the asia-south1 region)
• CI/CD: Google Cloud Build (configured to auto‑deploy from GitHub)

3. Google AI Integration

Beyond development, AI is at the core of the user experience:

• Gemini API: Integrated to power a chatbot that answers questions about my work history and projects. Recruiters can simply ask, “Does he know Spring Boot?” instead of reading a resume.
• DevOps Automation: Used Gemini to generate the specific gcloud deployment scripts and set up the CI/CD pipeline, ensuring a smooth path to production.

What I’m Most Proud Of

I am most proud of the seamless integration of new AI tools into a professional DevOps workflow.

Taking a project generated by Antigravity, polishing it with Gemini, and having it deploy automatically to Cloud Run via a CI/CD pipeline felt like the future of software engineering. Seeing the “Hello World” turn into a fully functional, AI‑powered application running on Google’s infrastructure was the perfect start to 2026!