Prompt Engineering - lesson 8 | HackIndia Skills

Key point

Ship the proof

Your project is not done when the prompt works once. It is done when another person can run the demo, understand the user task, and see evidence that you tested real cases.

What judges need

A reliable AI feature needs three things in the submission: a working flow, clear limits, and test proof. Keep it simple. A small feature that works is stronger than a large app with hidden failures.

Your demo should show one real user task. For example: summarize a hostel complaint, draft a UPI payment reminder, classify student helpdesk tickets, or extract fields from an invoice photo after OCR.

Your to-do

Submission checklist

Do each one yourself, then tap it to tick it off. The ticks are only a checklist for you: they are not marked or scored.

Create a public GitHub repository with clean setup steps.
Add a README that explains the user problem, demo flow, and model usage.
Include your prompt file or prompt-building code in the repo.
Add test cases with inputs, expected behaviour, and actual results.
Record or host a short demo where the full flow works.

0 of 5 done

Common mistake

Avoid demo theatre

Do not paste one perfect model answer into your README and call it tested. Judges and recruiters look for how your feature behaves across messy inputs.

Also avoid hiding safety limits. If your feature cannot handle medical, legal, or financial advice, say so in the app and README.

Example

README proof block

Add a short test evidence section. It helps someone review your work fast, even on mobile.

Project: Campus Helpdesk Ticket Router

User task:
Students paste a complaint. The app returns a category, priority, and next action for the admin team.

Demo flow:
1. Open the app.
2. Paste a student complaint.
3. Click Classify.
4. Check the returned JSON.
5. Admin can copy the result into the ticket system.

Model use:
The language model classifies the complaint into fixed categories only.
It does not make final admin decisions.

Prompt tests:
- tests/prompt-cases.json contains 12 real-style student complaints.
- Cases include short text, mixed Hindi-English, angry tone, missing details, and unrelated requests.
- 10 of 12 cases matched the expected category.
- 2 failures are listed in tests/failures.md with planned fixes.

Known limits:
The app does not verify documents.
The app should not be used for emergencies.

Tip

Use AI carefully

You can ask ChatGPT, Gemini, or Claude to improve your README. Give it your actual repo details and test results. Do not ask it to invent metrics, users, screenshots, or accuracy.

Check every generated line. If you cannot prove it from your repo or demo, remove it.