/chatgpt-app-builder

Discovery Workflow

Goal: Idea maturation, not speed.

Proceed in phases. Even if the user provides details, complete each phase through conversation. Do not infer or assume but discuss and validate with user. Proceed one phase at a time—do not write SPEC.md nor proceed to implementation until all phases are validated.

Phase 1: Value Proposition

1. Problem + User: What problem? For whom?
2. Pain: How solved today? What's painful?
3. Core actions: 1-3 focused actions (not a full app port)

Phase 2: Why LLM?

1. Conversational win: Where does "just say it" beat clicking?
2. LLM adds: What does the LLM contribute? (intent, generation, reasoning)
3. What LLM lacks: Your data? APIs? Ability to take real actions?

Fail patterns (stop if any match):

• Long-form or static content better suited for a website
• Complex multi-step workflows that exceed display modes
• Dashboards (use tables, lists, or short paragraphs instead)
• Full app ports instead of focused atomic actions
• No clear answer to "why inside an AI assistant vs standalone?"

→ If fails: explain gap, suggest different interface or narrower scope.

Phase 3: UI Overview

Describe the user journey through core actions:

1. First view: What does the user see when they start?
2. Key interactions: What happens at each core action?
3. End state: How does the experience conclude?

Phase 4: Product Context

Gather: existing products, APIs/data, auth method, constraints.

Phase 5: Create SPEC.md

Only after phases 1-4 are discussed and validated with the user. Do not write SPEC.md from the initial query alone.

Assemble from phases. Target: cwd if empty, else {app-name}/.

Example

# Pizza Ordering App

## Value Proposition
Order pizza through conversation. Target: PizzaCo customers wanting quick orders. Pain: navigating menus is slower than describing what you want.

**Core actions**: Browse menu, customize order, track delivery.

## Why LLM?
**Conversational win**: "My usual but with mushrooms" = one sentence vs. multiple screens.
**LLM adds**: Intent from natural descriptions, handles modifications.
**What LLM lacks**: Real menu and pricing data, order placement.

## UI Overview
**First view**: Popular pizzas with quick "reorder last" option.
**Browsing**: Menu with categories, filters, and customization options.
**Checkout**: Order summary, confirm, and place order.
**Tracking**: Live delivery status with ETA and map.

## Product Context
- **Existing products**: Mobile app, website
- **API**: REST at api.pizzaco.com (OAuth2, 100 req/min)
- **Auth**: PizzaCo account (OAuth2)
- **Constraints**: Payment via existing account only

After SPEC.md is created, confirm with user before proceeding to implementation.