Inspiration

Students often manage coding practice, personal projects, and internship applications across different platforms. It can be difficult to understand how the work they do translates into evidence for a particular opportunity. I wanted to build a workspace that connects these pieces and helps students identify what to work on next.

What it does

Student Career OS is a prototype for evidence-based career preparation. It brings together:

  • Profile & Practice: View coding practice progress and topic coverage.
  • Project Workspace: Organize project details, milestones, documentation, and testing evidence.
  • Verification Gate: Run deterministic checks on submitted evidence to identify missing or inconsistent details.
  • Opportunity Fit: Compare available evidence with opportunity requirements and highlight remaining gaps.
  • Next Actions: Surface practical next steps, such as collecting deployment evidence.

The demo uses a sample student profile, synthetic opportunities, and local sample data to demonstrate the workflow.

How I built it

I built Student Career OS as a web application using React, TypeScript, Vite, and CSS. I used a coding agent to help implement and refine the application, working through the features and connecting the different workspaces into a single user journey.

Rather than treating a project milestone as proof that a skill has been demonstrated, the prototype emphasizes submitted evidence and explicit verification checks. For example, its CampusCart demonstration shows an incomplete containerization evidence bundle failing two checks, followed by a complete sample passing all eight checks.

These checks validate the completeness and consistency of the submitted evidence. They do not build or run the Docker container.

Challenges I faced

One challenge was connecting several related workflows without making the interface feel disconnected or overwhelming. I also needed to make verification results understandable and show how additional evidence can affect an opportunity-fit assessment.

Another important consideration was being clear about the prototype's limitations. The current demo uses synthetic opportunities and sample data, and its verification logic is deterministic rather than a live assessment of a running project.

What I learned

This project helped me practice breaking a broad idea into manageable features, using a coding agent iteratively, and thinking about how evidence should flow between different parts of an application. I also learned the importance of making verification results transparent and distinguishing between recorded progress and evidence that has actually passed a check.

What's next

Future improvements could include secure student profiles, integrations with coding and project platforms, live opportunity data, and stronger verification that can execute project tests in a controlled environment.

My goal is to make career preparation more organized, transparent, and actionable by helping students connect the work they do with the evidence opportunities require.

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