Ignacia Portfolio engine V!
Source: Dev.to
Submission for the New Year, New You Portfolio Challenge Presented by Google AI
About Me
Based in Gloucester, Massachusetts, I am Ignacia Heyer – a creative technologist, Web3 entrepreneur, and wellness‑driven builder.
My work sits at the intersection of AI, rapid prototyping, brand identity, and decentralized digital experiences. I love turning abstract ideas into clean, scalable systems that are intentional, human‑centered, and future‑focused.
This portfolio isn’t a static website; it’s a living, generative system that evolves alongside me. Through it I aim to convey three key aspects:
- Identity – a digital presence that genuinely reflects my voice, energy, and vision.
- Clarity – a clear demonstration of who I am, what I build, and the value I deliver.
- Momentum – an expression of the speed and creativity I apply to the prototyping process.
Portfolio
(Content generated dynamically – see “How I Built It” for details.)
How I Built It
I re‑architected my portfolio as an AI‑powered engine rather than a conventional website. Instead of manually crafting each page, I built a system that can generate, on demand and via a single API call, the following assets:
- Complete multi‑page portfolio websites
- Single‑page, PDF‑style resumes
- Professional pitch decks
- Judge‑ready introductory scripts
- Social‑media announcements
This dynamic identity layer instantly adapts its format and content for diverse audiences.
Tech Stack Overview
Frontend / Output Layer
- Markdown‑based content generated by Gemini
- Renderable into websites, PDFs, or slides
Backend
-
Python (Flask) API
-
Custom endpoints:
/generate – create content /status – health check /health – health check /tasks – list available tasks /connect – connection info /demo – demo output -
Structured logging + error handling
-
Versioned service architecture
Infrastructure
- Google Cloud Run (serverless, auto‑scaling)
- Docker container for portability
- Environment variables for secure API‑key management
AI Layer
-
Google AI Studio (Gemini)
-
Custom system prompt trained on:
- My bio
- Skills
- Projects
- Brand voice
- Social‑media links
- Output formats
Technical Architecture Overview
| Layer | Technology | Purpose |
|---|---|---|
| AI & Content Generation | Google AI Studio (Gemini) | Core generative engine; custom system prompt encodes my bio, projects, voice, links, and desired output formats. |
| Backend & API | Python (Flask) | Handles request routing, calls Gemini, returns clean Markdown. |
| Infrastructure & Deployment | Google Cloud Run + Docker | Serverless, auto‑scaling, secure, portable environment. |
| Output Layer | Markdown | Flexible source that can be rendered to websites, PDFs, slides, or social posts. |
AI‑Powered Portfolio Engine: Design & Development
Core Design Principles
-
Generative over Static – The portfolio evolves automatically, eliminating manual updates.
-
Universal Markdown Output – One format for all assets, easily convertible to:
- Websites
- PDFs
- Slide decks
- Social‑media posts
-
Clear Task‑Based Architecture – Each asset is generated based on a specified
task_type. -
Human‑Centered Tone – A dedicated system prompt enforces a consistent, professional, and engaging voice:
- Confident
- Clear
- Professional
- Creative
- Future‑focused
-
Serverless Deployment (Cloud Run) – Provides:
- Instant scaling
- Public HTTPS endpoint
- Seamless integration with AI Studio
Development Workflow
| Step | Description |
|---|---|
| 1. Identity Definition | Draft a detailed system prompt capturing my story, skills, projects, tone, and social links. |
| 2. AI Logic Building | Build and iterate on Gemini prompts in Google AI Studio until outputs (websites, decks, PDFs, scripts, posts) are consistent and high‑quality. |
| 3. Backend Creation | Develop a Flask API that receives a task, forwards it to Gemini, and returns clean Markdown. |
| 4. Professional Endpoint Implementation | Add production‑ready endpoints: /status, /health, /version, /tasks, /connect, /demo. |
| 5. Deployment | Containerize with Docker and deploy securely to Google Cloud Run, using environment variables for secrets. |
| 6. Final Testing & Refinement | Validate all endpoints with curl and polish generative outputs for perfection. |
Google AI Tools Utilized
- Google AI Studio (Gemini) – Core generative model, fine‑tuned via custom system prompt.
- Google Cloud Run – Serverless hosting for the Flask API.
- Google Cloud Build – Automated container builds (optional).
- Google Secret Manager – Secure storage of API keys (via environment variables).
Google AI and Cloud Technologies
Tools
| Tool | Function |
|---|---|
| Google AI Studio (Gemini) | Used for defining the custom system prompt, task‑based generation, multi‑format content testing, and overall iteration environment. |
| Gemini API | The core generative engine integrated into the Cloud Run backend, responsible for creating all portfolio assets, handling structured prompts, and producing Markdown. |
| Google Cloud Run | The hosting platform for the API, providing serverless scaling, automatic HTTPS management, logging, and deployment infrastructure. |
Together, these tools form a modern, flexible, and fully automated AI‑powered portfolio engine tailored to my unique identity.
What I’m Most Proud Of
My greatest achievement is the development of a portfolio system that goes beyond simply showcasing my work; it embodies my forward‑thinking philosophy. Rather than a traditional, static website, I engineered a dynamic, generative identity layer that constantly adapts alongside my evolution. This project reflects my core belief that design must be adaptive, intentional, and profoundly human. It’s an intersection of artistic expression and technical execution—precisely where I find myself doing my most impactful work.