TechLeap Career Coach

TechLeap Career Coach Widget 1-3
TechLeap Career Coach Widget 4-6
TechLeap Career Coach chatbot

Inspiration

The idea for the app originated from the struggles of some of our team members who did not have formal technical training or work experience in the tech industry, as they sought inspiration to start their tech job search journey.

They faced challenges in finding inspiration to begin searching for their first tech jobs. There was insufficient guidance on how non-technical work experience and studies could be valued in the tech sector. It felt like hitting a brick wall.

This app aims to encourage individuals who may not currently have technical skills but bring diverse experiences and talents to consider a tech career.

What it does

The TechLeap Career Coach is an AI-assisted personalized guide, ensuring that career changers feel prepared and supported on their journey to success. It provides personalized tech role recommendations, showing how their previous non-technical work experience or skills will contribute to their success in their tech career. Additionally, it offers an overview of the chosen tech role and a success guide. Users can ask as many questions as they want with the Career Chatbot as well.

How we built it

In the PartyRock app generator, we used Jurassic-2 Ultra for LLM to offer 'Tech Role Recommendations,' referring to the user's input from [1. Education & Work Experience] and [2. Technical and Non-technical Skills]. For the 'Your Chosen Tech Career Overview' and 'Navigate Your Tech Career: A Guide for Success,' related to the user's input from [4. Type the Tech Role you want to explore], we used Claude for the chatbot.

Challenges we ran into

We encountered challenges like the app providing random answers, lacking user input filters, having a limited user interface, being unable to train the AI app, and not supporting the inclusion of videos/links.

Accomplishments that we're proud of

Before creating the app using PartyRock, our practical experience with generative AI was limited. Now, we're more confident using generative AI and understand the differences between various LLM models. We're proud of achieving significant progress with our Proof of Concept (POC), establishing a strong foundation for developing a real-world app.

What we learned

We've learned that it's crucial to identify the problems to solve and understand the strengths and weaknesses of AI. Getting feedback from peers has proven valuable for spotting issues and improving app functionality. We've also gained the skill of prompt engineering for better answers, along with the ability to improve responses by adjusting temperature and Top P.

What's next for TechLeap Career Coach

Our goal is to evolve the app into a TechLeap Career Coach throughout the entire user journey. We also need to test it with real users, gather feedback, improve the UI, and include videos of interviews or written articles featuring individuals in tech roles.