EngineerIt

EngineerIt is a hackathon project that turns a rough product idea into a practical engineering plan. A user writes a plain-English idea, the app interprets it, asks follow-up questions, proposes feature and architecture directions, compiles a structured specification, generates prompt packs for AI coding tools, and exports the whole package as a ZIP.

Idea

The project is built around a simple problem: non-technical founders and early teams often know what they want to build, but they struggle to convert that idea into something developers can execute quickly. EngineerIt acts as the bridge between product thinking and engineering delivery.

Instead of forcing users to write requirements documents manually, it guides them through a lightweight workflow:

1. Enter the product idea in natural language.
2. Review AI-generated interpretations of that idea.
3. Answer discovery questions about users, features, and constraints.
4. Generate a synthesis of MVP scope, risks, and architecture lanes.
5. Compile a detailed engineering specification.
6. Export prompt packs and planning files that can be used by developers or AI coding assistants.

What The App Produces

• Project interpretations so the team can align on the right direction early.
• Guided interview questions to extract missing requirements.
• Feature prioritization for MVP, enhancements, and strategic additions.
• Architecture lane recommendations with tradeoffs.
• A structured engineering spec with pages, flows, entities, integrations, deployment notes, and acceptance criteria.
• Prompt packs for tools like ChatGPT, Cursor, or Copilot.
• A downloadable ZIP containing README, tasks, spec JSON, env template, validation output, and deployment notes.

Why It Matters

EngineerIt is meant to reduce the gap between "I have an idea" and "a developer can start building this today." For a hackathon setting, that makes it useful both as a planning product and as a demonstration of multi-step AI workflow design: interpretation, questioning, synthesis, validation, and export all happen in one flow.

Product Flow

• Landing page for idea intake.
• Project workspace with a multi-step wizard.
• API routes for project creation, interpretation, interview generation, synthesis, spec compilation, prompt generation, preview generation, and export.
• Local persistence for projects and generated artifacts.
• Validation and linting rules to catch weak specs and prompt issues before export.

Stack

• Next.js App Router
• React + TypeScript
• Tailwind CSS
• SQLite for local project persistence
• OpenAI and MiniMax model routing
• Playwright and Vitest for testing

Running Locally

1. Install dependencies with npm install.
2. Copy values from .env.example into a local .env.
3. Start the app with npm run dev.
4. Open http://localhost:3000.

Environment Notes

The app expects API credentials for at least one text model provider. Preview generation and some export flows also use environment configuration defined in .env.example.

Repository Notes

• The latest remote implementation is now merged into main.
• The previous local rewrite state was preserved in commit ba19eff before the merge.