feat: Add CLAUDE.md for project guidance and update project files

- Created CLAUDE.md to provide development commands, architecture overview, and environment variables for the Nuxt 3 portfolio website.
- Refactored project pages to remove unused color mappings and improve project filtering logic.
- Updated content.config.ts to enforce stricter project type definitions and added short descriptions for projects.
- Deleted outdated project files and added new projects related to hackathons and academic research.
- Enhanced existing project descriptions with short summaries for better clarity.

content/projects/hackathon-natixis.md

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+---
+slug: hackathon-natixis
+title: "Natixis Hackathon: Generative SQL Analytics"
+type: Hackathon
+description: An intensive 4-week challenge to build an AI-powered data assistant. Our team developed a GenAI agent that transforms natural language into executable SQL queries, interactive visualizations, and natural language insights.
+shortDescription: A team-based project building an NL-to-SQL agent with Nuxt, Ollama, and Vercel AI SDK.
+publishedAt: 2026-03-07
+readingTime: 4
+status: completed
+tags:
+  - Nuxt
+  - Ollama
+  - Vercel AI SDK
+  - PostgreSQL
+  - ETL
+icon: i-ph-database-duotone
+---
+
+## The Challenge
+
+Organized by **Natixis**, this hackathon followed a unique high-intensity format: **three consecutive Saturdays** of on-site development, bridged by two full weeks of remote collaboration. 
+
+Working in a **team of four**, our goal was to bridge the gap between non-technical stakeholders and complex financial databases by creating an autonomous "Data Talk" agent.
+
+## Core Features
+
+### 1. Data Engineering & Schema Design
+Before building the AI layer, we had to handle a significant data migration task. I led the effort to:
+* **ETL Pipeline:** Convert fragmented datasets from **.xlsx** and **.csv** formats into a structured **SQL database**.
+* **Schema Optimization:** Design robust SQL schemas that allow an LLM to easily understand relationships (foreign keys, indexing) for accurate query generation.
+
+### 2. Natural Language to SQL (NL-to-SQL)
+Using the **Vercel AI SDK** and **Ollama**, we implemented an agentic workflow:
+* **Prompt Engineering:** Fine-tuning the agent to translate complex business questions (e.g., "What was our highest growth margin last quarter?") into valid, optimized SQL.
+* **Self-Correction:** If a query fails, the agent analyzes the SQL error and self-corrects the syntax before returning a result.
+
+### 3. Automated Insights & Visualization
+Data is only useful if it’s readable. Our Nuxt application goes beyond raw tables:
+* **Dynamic Charts:** The agent automatically determines the best visualization type (Bar, Line, Pie) based on the query result and renders it using interactive components.
+* **Narrative Explanations:** A final LLM pass summarizes the data findings in plain English, highlighting anomalies or key trends.
+
+## Technical Stack
+
+* **Frontend/API:** **Nuxt 3** for a seamless, reactive user interface.
+* **Orchestration:** **Vercel AI SDK** to manage streams and tool-calling logic.
+* **Inference:** **Ollama** for running LLMs locally, ensuring data privacy during development.
+* **Storage:** **PostgreSQL** for the converted data warehouse.
+
+## Impact & Results
+
+This project demonstrated that a modern stack (Nuxt + local LLMs) can drastically reduce the time needed for data discovery. By the final Saturday, our team successfully presented a working prototype capable of handling multi-table joins and generating real-time financial dashboards from simple chat prompts.
+
+---
+
+*Curious about the ETL logic or the prompt structure we used? I'd be happy to discuss how we optimized the LLM's SQL accuracy.*