Gooey.AI

Gooey.AI is an online workspace that lets me stitch together large-language-model prompts, data sources, and simple widgets into mini-apps I can share in a browser.

How to use Gooey.AI

1. Create an account at gooey.ai and pick a starter template or begin with a blank canvas.
2. Drag a model block onto the canvas, type your prompt, and set any variables you want end-users to adjust.
3. Add data connectors or extra logic blocks if the project needs spreadsheets, web scraping, or conditional flows.
4. Switch to the preview tab to test the interface exactly as visitors will see it.
5. Click “Publish”, copy the generated link, and send it to clients, team-mates, or embed it in a site.

A closer look at Gooey.AI

Advantages

• Straightforward builder: The canvas feels like Figma for prompts; I could position blocks freely and wire them up without reading docs.
• Helpful templates: Ready-made projects for blog outlines, YouTube chaptering, and CSV cleaning cut my setup time to minutes.
• Live collaboration: Colleagues joined my workspace and tweaked prompts while I watched, which turned feedback cycles into real-time chat.
• Transparent pricing: A free tier covers light use, and the pay-as-you-go model shows token spend per run so surprises disappear.
• One-click share links: Non-technical reviewers opened my demo on mobile and ran it instantly, no install needed.

Drawbacks

• Limited styling options: I could adjust colours and fonts only through custom CSS, so layouts stayed fairly plain out of the box.
• Version control friction: Saving checkpoints works, yet rolling back to an earlier state required manual cloning rather than a timeline slider.
• Model range gaps: GPT-4 and Claude are present, though open-source choices such as Mistral aren’t available yet.
• API throttling: During peak hours my runs queued for a short while; fine for demos, less ideal for production dashboards.

I left the test week impressed by how quickly concepts turned into clickable prototypes, even if deeper styling and wider model support would make the service more versatile.