💡 My Philosophy
- AI tools are the new Stack Overflow — an accelerator for learning and shipping
- They can make developers faster and more productive, but only with deliberate practice
- Like learning a new programming language, there’s a steep learning curve:
- How to prompt effectively
- When to provide or clear context (e.g., using
/clear to refocus)
- Understanding model limitations and strengths
- I’m a strong believer and adopter, but also mindful:
- Not “vibe coding” → everything must be production-grade
- Security-first → careful with data, code sharing, and compliance
⚡ Context
- Driving AI adoption inside engineering at Crystal Intelligence
- Exploring how to leverage AI personally & professionally to enhance productivity, automation, and coding best practices
🛠 Professional Use
- Leading AI adoption program for 40+ engineers:
- Split into 3 phases → pilot, ongoing, steady
- Currently finishing pilot phase: access to GitHub Copilot, Cursor, and Claude Code
- Stimulating engagement and collecting feedback so developers form their own opinions
- Monitoring adoption & productivity with Jellyfish AI adoption features
- Goal: determine the best AI coding tools for Crystal engineers and understand their impact on workflows
🧑💻 Personal Use & Exploration
- Daily user of ChatGPT and Claude for work and personal projects
- Coding journey: started with Windsurf (ex-Codium) → moved to Claude Code
- Heavy use of n8n combined with OpenAI/Claude for automations
- Example: automated billing reports for on-call engineers (incidents → overtime → compensation)
- Researching Lovable’s stack (generated code platform) → experimenting with GPT Engineer (repo)
- Next goal: fine-tuning a model or experimenting with fine-tuned models to understand boundaries & capabilities
📈 Impact
- Kickstarting a culture of AI-augmented engineering at Crystal Intelligence
- Personally building expertise in AI coding assistants, workflow automation, and model customization