You shipped an AI-built career website on Google Cloud. In about three hours you went from a blank project to a public URL — using the same toolchain professional teams ship with.

What you built

• A visual design generated and refined in Stitch.
• A working career site coded agentically in Antigravity, against the Stitch reference.
• Your content as structured data — collected by a Gemini Gem interview and stored in persona.json.
• A live deployment on Cloud Run, sitting behind a public HTTPS URL.
• A real, professional development workflow: Superpowers, MCP servers, small commits, iterative prompts.

Next steps

• Customize further on your own time. Edit persona.json, push a follow-up Antigravity prompt, redeploy. The pipeline you set up today is reusable.
• Try the bonus tracks. The MCP server turns your persona.json into tools any AI client can call. The chatbot wires Vertex AI (or your MCP server) to a chat widget on the deployed site.
• Add the URL to LinkedIn, GitHub, and your CV. A live site that you can iterate on beats a static PDF every time. Put it where recruiters will see it.
• Explore the resources page. Curated links to Google products, frameworks, and further reading — bookmark it and come back as questions come up.

Keep going with codelabs

Right now is the highest-leverage moment to learn more — your Google Cloud project is configured, credits are live, and you have momentum. Google publishes free, hands-on tutorials called codelabs that fit cleanly into a focused hour. Three to consider next:

• Getting Started with Google Antigravity — deepen your fluency with the IDE you used today.
• Getting Started with Google MCP Servers — if the bonus track caught your attention.
• Building AI Agents with ADK: The Foundation — the natural next step from a chatbot to a real agent.

The full curated list with commentary lives on the resources page.

Resources