Q&A is where I learn the most as an evaluator, because a team's answers reveal what the demo hid. Teams that prepare for these questions look like engineers; teams that improvise look like they got lucky. Prepare all fifteen; you will be asked five.
About the demo
- Which part of what we just saw is real, and which is mocked? Answer precisely. Judges reward honesty and punish discovered mocks.
- Can you try it with this input? Say yes. If it fails, explain why technically.
- What happens when the external API is down or slow? Strong: a fallback or a clear error. Weak: "it wouldn't be".
About the technology
- Why this model, database or framework? Strong answers mention the constraint that drove the choice, not the popularity.
- How did you evaluate the AI part? Even five test cases with expected outputs is a strong answer; "it seemed good" is not.
- Where does user data go, and who can see it? Every team using AI APIs should be able to answer this.
- What was the hardest bug, and how did you find it? This is the question that identifies who built what.
About the user and the problem
- Who did you talk to? Names or roles, and one thing they said that changed the design.
- How does the user do this today, without you? If you cannot answer, you have not understood the problem.
- Why would they switch? The honest answer is usually about time or money saved, stated in numbers.
About the team and what is next
- What did you cut, and why? The best question on the sheet. Have a proud answer.
- Who built which part? Match your answer to who answers the technical questions.
- What would you do with another week? Specific and small beats grand and vague.
- What did you learn that you did not expect? Judges are teachers; they love this one.
- Would you keep working on this? Only say yes if it is true; they can tell.
Rehearse these with your mentor before the freeze. When I run a mock pitch for a team, this is the list I use.
GenAI engineer and AI product builder with 2+ years shipping production-grade AI systems: RAG pipelines, fine-tuned LLMs, hybrid retrieval and multi-modal apps across vision, speech and OCR, architected end to end from ingestion to deployment. Leads engineering for SCULT INDIA's 14-member team, founded the 500+ member TechVerse Enclave community and has mentored 200+ students. Three hackathon first prizes: Changethon 2025 (IIT Roorkee), Product Genesis at Vividhotsava 2025 (CSJMU Kanpur) and BYTEBATTLE (MeetKats).
Open to GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges. Email pranjulrathour41@gmail.com.
