Builder Lab
Your Hands-On AI Builder Journey
“Start fast. Make it work.”
Build a production‑ready AI chatbot, then level up to the Engineer Lab for deeper engineering practice.
Learning Path – Step‑by‑Step
1. Kick-off & Mindset
Resource | Description | Action |
|---|---|---|
▶️ Kick-off Video | Introduces the Builder mindset, goal‑setting and how to think like an AI product owner. | |
📄 Mindset Canvas PDF | A one‑page worksheet to capture your problem statement, target user and success metrics. | |
✅ Quick-Start Checklist | 7‑point checklist to ensure you have the right environment (Node 18+, Firebase CLI, Git). |
2. Tool Foundations
Resource | Description | Action |
|---|---|---|
▶️ Tooling Overview Video | Walk‑through of Flowise, n8n, Firebase Functions and the no‑code UI. | |
📂 Starter Repo | Boilerplate repo with Firebase setup, Flowise config and n8n starter workflow. | |
📄 Environment Setup Guide | Step‑by‑step instructions to install Node, Firebase and the required npm packages. |
3. Project 1: RAG Chatbot
Resource | Description | Action |
|---|---|---|
▶️ RAG Chatbot Walkthrough | Build a Retrieval‑Augmented Generation chatbot that pulls from a custom knowledge base. | |
📂 RAG Flowise Flow | Ready‑to‑import Flowise flow that wires LLM, vector store and prompt templates. | |
📂 Chatbot Repo | Full source code (Node .js + Firebase Functions) for the chatbot backend. | |
✅ Testing Checklist | Verify vector store indexing, LLM response latency and UI responsiveness. |
4. Project 2: Automation Workflow
Resource | Description | Action |
|---|---|---|
▶️ Automation Walkthrough | Build a lead‑capture pipeline: Tally form → n8n webhook → Firestore → email sales team (optional Firebase Cloud Function for custom email - developers only) | |
📂 n8n Workflow Template | Drag‑and‑drop workflow that receives the Tally webhook, writes the payload to Firestore and triggers an email node (or a Cloud Function) | |
📂 Webhook & Email Repo | Code for the n8n webhook endpoint, environment variables and an optional Firebase Cloud Function that formats and sends the sales‑team email | |
📄 Run Book | Operational guide covering webhook validation, error handling, dead‑letter logging and manual retry procedures |
5. Polish and Deploy
Resource | Description | Action |
|---|---|---|
▶️ Polish & Deploy Video | UI polish & one‑click Firebase deploy | |
🌐 Live Demo Link | A publicly accessible demo of the finished chatbot and Automation Workflow. |
6. Next Level Preview
Resource | Description | Action |
|---|---|---|
▶️ Teaser Video | Quick teaser of how the same chatbot will gain observability, versioning and self‑hosting in the Engineer level; how the workflow will migrate to a custom FastAPI service with retries and a production database. |
Who Is This For?
No-Code Builders
Drag‑and‑drop today, learn the engineering fundamentals you need to scale tomorrow.
Code-first Devs
Feel the speed of drag‑and‑drop, then spot coding opportunities to add flexibility.
Full-stack & Ops
Own the whole AI stack from SaaS UI to serverless backend, perfect stepping‑stone to Engineer & Architect levels.
Product Leaders & Founders
Ship a lead‑gen chatbot or an automated sales pipeline now to validate ideas and start generating revenue.
What You'll Achieve
- A production‑ready RAG chatbot that captures leads and stores them in Firestore.
- An end‑to‑end automation workflow that receives a Tally form submission, saves the lead in Firestore and emails the sales team (with an optional Cloud Function for custom formatting).
- A secure, one‑click deployment on Firebase with best‑practice hardening baked in.
Next Steps
Level Up - Ready for deeper engineering practice? Jump to the Engineer Lab for optimization, observability & scaling.