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MBA candidate @ Kellogg targeting PMM/GTM roles (and PM roles focused on AI workflows). I design and ship AI-enabled products end-to-end, from customer problem to deployed system and go-to-market narrative.

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Featured project

Architecture: Lovable (frontend) → Railway (Node backend) → Claude API (LLM orchestration)

• STARLprep.AI — AI behavioral interview coach that helps candidates craft polished STARL-formatted answers with instant feedback.
  • Live demo: https://starlprepai.lovable.app/
  • Case study → STARLprep.AI Product Case Study
  • GitHub repo: https://github.com/giangps?tab=repositories
  • Demo video → Coming soon
• What this proves:
  • Designed an AI workflow that converts unstructured user stories into structured, interview-ready outputs
  • Built and deployed a production AI system using Lovable frontend, Railway backend, and Claude API
  • Implemented guardrails to prevent hallucinated metrics and ensure output reliability
  • Created a structured scoring rubric to evaluate answer strength and guide user improvement
  • Defined ICP, user workflow, and GTM positioning for an AI-native product

Projects

Untitled

Links

• LinkedIn: https://www.linkedin.com/in/giansenaja/
• Github: https://github.com/giangps