Tools: Meet the AI Assistant That Guards My Portfolio

About Me ## Portfolio ## How I Built It ## 1. The "AI-First" Development Process ## 2. The Tech Stack ## 3. Google AI Integration ## What I'm Most Proud Of New Year, New You Portfolio Challenge Submission This is a submission for the New Year, New You Portfolio Challenge Presented by Google AI Hi everyone! I'm a Software Engineer based in Bangladesh with over 3 years of experience specializing in Java and Spring Boot. Currently, I 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 like 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. But 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. 💡 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!) I didn't want just a static HTML page. As a backend engineer, I wanted to showcase a full-stack architecture that is robust, scalable, and "smart." This project was born in the cloud. Beyond development, AI is at the core of the user experience: 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! Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse - 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. - 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). - Gemini API: I integrated the Gemini API 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: I even used Gemini to generate the specific gcloud deployment scripts and set up the CI/CD pipeline, ensuring a smooth path to production.