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Quick Start

Get started building your data product on Databricks. Choose your starting point:

Workshop participants: Complete the PRE-REQUISITES.md checklist before beginning.

Path A: Build and Deploy a Databricks App

Build a full-stack TypeScript app on Databricks AppKit, guided by 7 agent skills:

# 1. Clone template
git clone https://github.com/databricks-solutions/vibe-coding-workshop-template.git my-project && cd my-project

# 2. Authenticate
databricks auth login --host https://your-workspace.cloud.databricks.com

# 3. Open your AI coding assistant and prompt:
I want to build a Databricks App. Read @apps_lakebase/skills/01-appkit-scaffold/SKILL.md and scaffold a new AppKit project.

Follow the 5-phase workflow in apps_lakebase/Instructions.md:

Phase What Happens Skill Used
1 Scaffold + build UI from a PRD, test locally 01-appkit-scaffold, 02-appkit-build
2 Deploy to Databricks Apps (mock data) 03-appkit-deploy
3 Setup Lakebase project 00-appkit-navigator
4 Wire Lakebase backend (local) 04-appkit-plugin-add, 05-appkit-lakebase-wiring
4b Wire Serving / Agent endpoint (optional) 04-appkit-plugin-add, 06-appkit-serving-wiring
5 Deploy + E2E test with Lakebase 03-appkit-deploy

Path B: Build an End-to-End Data Pipeline

Take a raw schema CSV through the full medallion architecture -- Bronze, Silver, Gold, semantic layer, Genie Spaces, ML, and GenAI agents -- using one prompt per stage:

  1. Drop your schema CSV into data_product_accelerator/context/
  2. Open your AI coding assistant (Cursor, Claude Code, Windsurf, etc.)
  3. Prompt:
I have a customer schema at @data_product_accelerator/context/Wanderbricks_Schema.csv.
Please design the Gold layer using @data_product_accelerator/skills/gold/00-gold-layer-design/SKILL.md
  1. Follow the full 9-stage pipeline guide -- one prompt per stage, one new conversation per stage.

Repository Layout

Directory What It Does
apps_lakebase/ AppKit workshop -- 7 agent skills for building full-stack Databricks Apps
data_product_accelerator/ 55 agent skills for building end-to-end data products (9 stages)
agentic-framework/ Multi-agent build framework for Databricks Foundation Models

AppKit Commands (after scaffolding)

After scaffolding your app with the 01-appkit-scaffold skill, these commands run from your generated app directory:

Task Command
Install deps npm install
Dev server npm run dev
Build npm run build
Type generation npm run typegen
Validate databricks apps validate
Deploy databricks apps deploy --profile <PROFILE>
AppKit docs npx @databricks/appkit docs

Local URLs (after scaffolding)

Data Product Accelerator

Build a complete Databricks data product using one prompt per stage:

Schema CSV → Gold Design → Bronze → Silver → Gold → Semantic Layer → Observability → ML → GenAI Agents

Troubleshooting

# Check CLI version (must be >= 0.295.0)
databricks --version

# Reconfigure auth
databricks auth login --host https://your-workspace.cloud.databricks.com

# Verify connection
databricks current-user me

# Check deployed app
databricks apps get <APP_NAME> --profile <PROFILE>

# Kill stuck dev server
lsof -ti:8000 | xargs kill -9 2>/dev/null || true

Full docs: README.md | Prerequisites: PRE-REQUISITES.md | AppKit guide: apps_lakebase/Instructions.md | 9-stage guide: data_product_accelerator/QUICKSTART.md