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LEARNABLE / MODULE 1 / GUIDED BUILD

Your first dinner conversation loop

Load an example, inspect its fields, and answer a follow-up. Then break something on purpose and repair it. You are learning to explain what the application does.

Practice simulation. These are authored sample responses, not AI-generated results. This page makes no model or DoorDash calls, stores no personal information, and cannot place an order.

1. Inspect a sample response

Edit a value to test meaning. Delete a comma to test format. Loading a sample replaces the current practice edits.

Load a sample to begin.

2. Read what the app understood

A summary appears only after structural validation succeeds.

3. Answer one useful question

Validate the sample first.

For dietary restrictions, enter “none” only when explicitly intended. Budget amounts must be positive numbers; fee answers must be yes or no.

4. Make it yours

  1. Load the worked case and validate. Enter a fictional delivery area. Confirm the budget stays at 25.
  2. Change 25 to 250. Validate again. Explain why a format pass is insufficient, then repair the value.
  3. Load the broken case. Repair the missing comma and validate again.
  4. Download this starter. Open it in a text editor and search for nextQuestion. Change the delivery-area question wording. Save and open your copy in a browser.
  5. Return to Product Academy and save your test results and check-in.

The starter is a single HTML file. No installation, credentials, or paid service is required. For help, ask your coding assistant to explain the nextQuestion function before changing it.

Extraction prompt for a later live-model experiment
Task: extract dinner preferences from the supplied request.
Rules: preserve explicit requirements and corrections. Do not guess missing details.
Use null for unknown values; use [] for dietary restrictions only if the user explicitly says none.
Do not invent restaurant availability, prices, currency, or location.
Return these JSON fields:
cuisine_preferences: list of strings or null
spice_preference: string or null
budget_amount: positive number or null
currency: string or null
includes_fees: boolean or null
dietary_restrictions: list of strings or null
delivery_area: string or null
If the request specifies party size or a per-person budget, preserve those separately as party_size and budget_basis.
Input: [place the user request here]

Prompting alone is not validation. A live version will need a model connection, server-held credentials, response checks, and measured behavior.