Discover Career Success: Using the TechLeap Career Coach App with PartyRock

The world around us is changing rapidly and with the introduction of AI, it seems to be accelerating even faster, creating job uncertainty.  At the same time the opportunities within the tech industry are many and diverse and growing; but for those outside the sector how do they find suitable roles to get a foothold? 

How cool would it be if AI could take a person’s job skills, interests and personality traits and match them to suitable roles within the tech industry? Not only suggesting roles but providing them with a pathway to success!! 

Welcome to TechLeap Career Coach, your one-stop AI tool for those wanting to find roles in the Tech Industry. 

By leveraging existing capabilities, career changes can feel confident they have the necessary skills to change careers and become involved in the ever-changing world of tech. 

I would envision the tool being used as a front door for our company to gain a far wider entry reach in showcasing technology roles to those with no prior experience improving the richness that a more diverse workforce provides. 

PartyRock provides early and experienced professionals with an opportunity to understand what roles are possible within the realm of cloud computing. But we can enhance the app with BedRock even further.

We can integrate BedRock with an AWS storage service to store users' data. Unlike PartyRock, which doesn't store output or user's personal data, BedRock allows users to pick up from where they left off each time they use the app. Additionally, for an improved user interface, we can develop the app using React or other front-end tools.

Using BedRock allows us to customize models, enabling the development of TechLeap Career Coach with our specific data. This flexibility allows us to provide users with the information they need, and we can also set boundaries for tech job roles if necessary.

Unlike PartyRock's model has some limitations, BedRock allows us to use the latest version of each model. We also can pre-train the model to anticipate the app's information for users and avoid random inputs and outputs. With Guardrails for Amazon Bedrock, we can selectively reject inputs containing Personally Identifiable Information (PII).

Whilst PartyRock provides an extensive array of information concerning the various job roles related to cloud computing and technology in general, improvements can be made. For example, attempting to utilise the Career Coach for advice on how to become a Solutions Architect (SA) is informative (as it sets out the steps needed to move towards an SA role) but for an individual seeking resources (videos, whitepapers or otherwise) its offerings may sometimes be out-of-date or no longer accessible.  

PartyRock shines because it provides a great way for people to discover new jobs in an ever-changing, cloud-centric society. However, it is also just as important to ensure that as technology shifts rapidly and new approaches to cloud computing reveal itself the information which we’re provided with is also able to meet these demands. PartyRock fulfils many of these demands, it still falls short of some.  

As we delve further into generative AI, and the like it’s important to ensure that tools such as PartyRock can provide offerings which can not only satiate our curiosities but provide us with a guiding hand to traverse these unknown unknowns. 

The TechLeap Career Coach app is created by Team Tesskasaurus, including Akira Allman, EJ Shin, Samuel Ijegbulem, Simon Harrison, Tom Werner, and Vishakha Doshi.