https://github.com/joshtol/caribbean-diving-guide-2025
An interactive, in-depth guide to Caribbean scuba diving in 2025, focusing on reef health, conservation, and eco-tourism. Developed iteratively with a proprietary agentic AI system.
https://github.com/joshtol/caribbean-diving-guide-2025
agentic-development ai-assisted-development caribbean css html javascript marine-conservation scuba scuba-diving tailwindcss travel-guide webd webdevelopment
Last synced: 5 months ago
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An interactive, in-depth guide to Caribbean scuba diving in 2025, focusing on reef health, conservation, and eco-tourism. Developed iteratively with a proprietary agentic AI system.
- Host: GitHub
- URL: https://github.com/joshtol/caribbean-diving-guide-2025
- Owner: joshtol
- License: mit
- Created: 2025-08-08T09:01:17.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-08-08T10:34:41.000Z (12 months ago)
- Last Synced: 2025-08-08T11:24:19.546Z (12 months ago)
- Topics: agentic-development, ai-assisted-development, caribbean, css, html, javascript, marine-conservation, scuba, scuba-diving, tailwindcss, travel-guide, webd, webdevelopment
- Language: HTML
- Homepage:
- Size: 41.9 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# The Caribbean Diving Encyclopedia 2025
An interactive, in-depth guide to Caribbean scuba diving, built entirely by a proprietary AI agent swarm as a case study in human-AI development workflows.
---
---
## The Project: A Dual Mission
This project serves two core purposes:
1. **A High-Quality Travel Guide:** To create a genuinely useful, expert-level resource for scuba divers interested in the Caribbean, especially in the wake of recent ecological challenges.
2. **A Transparent Case Study:** To showcase a sophisticated, human-AI development workflow where a multi-agent AI swarm, guided by a non-expert, can produce a polished, accurate, and commercially viable product.
This repository is a testament to a new paradigm of software development, demonstrating how structured AI collaboration can achieve high-velocity, expert-level results.
## The Case Study: An AI-Powered Workflow
As an AI engineer (and non-diver), I developed this project to rigorously test my proprietary AI agent swarm. The entire application, from research and content generation to coding and design, was executed by the swarm under my guidance.
### The Swarm's Architecture
The development process was driven by a "constitutional" framework, ensuring safety, efficiency, and alignment. The key components included:
- **QUEEN (The Orchestrator):** A high-level reasoning agent responsible for task decomposition, strategy, and orchestrating the other agents.
- **Wild Research:** An automated research system that synthesized ecological and travel data to inform the content.
- **Specialist Agents:** A team of AI agents with specific skills (e.g., Qwen3 Coder for frontend development, expert writers for content) fueled by tools like **Gemini CLI, Google Code Assist, and OpenRouter**.
All AI-generated content was then validated for accuracy by a human subject matter expert—an experienced diver. This workflow demonstrates a powerful model for leveraging AI to tackle complex, domain-specific challenges.
## Technical Showcase
This project isn't just about AI; it's about quality craftsmanship. The final product is a clean, modern, and performant web application.
- **Modern Tech Stack:** Built with semantic **HTML5** and styled with **Tailwind CSS** for a responsive, mobile-first design.
- **SEO & Accessibility:** Comprehensive metadata, Open Graph tags, ARIA roles, and **JSON-LD structured data** are implemented for maximum visibility and usability.
- **Clean Code:** A single, well-commented `index.html` file demonstrates a commitment to readable and maintainable code, even on a small-scale project.
## How to Run Locally
1. Clone the repository:
```bash
git clone https://github.com/joshtol/caribbean-diving-guide-2025.git
```
2. Navigate to the project directory:
```bash
cd caribbean-diving-guide-2025
```
3. To view the project correctly with images, you must run it from a local server. If you are using VS Code, the easiest way is with the **Live Server** extension.
---
Created by joshtol using a proprietary AI agent swarm.
