AI Career Advisor
An innovative platform leveraging Large Language Models (LLMs) to provide tailored career advice. It analyzes user inputs to offer insights into career pathways, skill gaps, and personalized training recommendations.
A conversational AI system that uses sophisticated prompt engineering and context injection to deliver personalized career advice. The backend dynamically adjusts LLM parameters based on user intent, ensuring optimal responses for both factual queries and creative brainstorming.
The Challenge
The biggest hurdle was 'teaching' the AI to be a helpful coach rather than a generic text generator. The AI needed to avoid giving bland, non-committal advice. This required sophisticated prompt engineering to ensure the AI's 'personality' remained encouraging, professional, and context-aware.
The Solution
The system was designed with a sophisticated context injection layer. Before a user's query is sent to the LLM, the backend injects relevant profile data (like job title and skills) and previous interaction history into the prompt. This ensures the AI's advice is hyper-personalized. I also used few-shot prompting with examples of 'good' and 'bad' advice to guide the AI's tone.
Gerasimos Makris is an AI Web Developer with a background in FinTech operations. He specializes in building secure, scalable web applications that solve real-world financial problems. When he's not coding, he enjoys exploring the intersection of technology, finance, and business strategy.
