Hey everyone! I've been working as a GenAI developer for a year at a service-based company after graduating, but lately, I've been feeling a bit lost about where to head next. I've dabbled with technologies like FastAPI, LangChain, LangGraph (including human-in-the-loop flows), and built simple RAG systems with hybrid search. I've also played around with Streamlit for chat interfaces and tried connecting MCP servers to Claude, mostly working locally.
The problem is that most of my tasks have been small proof-of-concept projects, and I've lacked strong mentorship, leaving me feeling like I'm only scratching the surface. Recently, I started learning frontend technologies, hoping to become a full-stack GenAI developer, but now I'm even more confused about what to focus on. With only about an hour a day to improve, I'm wondering whether I should delve deeper into ML fundamentals, concentrate on backend systems, or stick with GenAI frameworks. Any advice from those who've faced a similar situation would be greatly appreciated!
2 Answers
Honestly, focus on a single, solid end-to-end project. Take your existing RAG setup, deploy it with proper authentication, database management, and logging. This approach will give you a much deeper understanding and solve real-world problems instead of just theoretical knowledge.
I totally get the PoC struggle! Instead of hopping around different frameworks, try building a complete project from scratch. It could be as simple as taking your RAG setup and deploying it on cloud infrastructure. That hands-on experience will teach you way more than just learning new tools.
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