AI TOOLS FOR ONLINE BUSINESS BUILDERS | PART 1 #1
I’ve been building out a series on AI tools that might actually be useful for people building online income systems. Not hype. Not press releases. Real experiments, real results, honest verdicts.
Google Opal was the first one on my list. It’s a no-code app builder from Google Labs that lets you chain together AI models — Gemini, Imagen, and others — into shareable mini-apps, using plain English. No code required.
I went in with a specific goal: follow a step-by-step build guide, create a working app, and report back on what it was actually like. Here’s the honest version.
| 📋 The UD Portability Rule Before you build anything on a free platform, ask: “If this disappeared tomorrow, what would I lose?” Output you own (images, text, audio saved to your drive) = Safe to use Workflow that lives in their account (like an Opal app) = Useful, but not business-critical Audience or list built on their platform = Always migrate to owned assets |
First: The Sign-In and Access Screen
Opal’s sign-in screen — straightforward Google OAuth, but read before you click Continue.
Before you build anything, Opal asks for permission to access your Google account. Specifically, it wants access to your Google Drive — both broad read access and the ability to see, edit, create, and delete specific files.
The “Additional access required” screen. You’ll need to select all permissions to proceed.
| 💡 Pro Tip I used a separate, empty-drive Gmail account for this experiment. That way, I could grant Opal the access it needs without giving it a window into anything real. If you’re privacy-conscious or just cautious, I’d recommend the same approach. Set up a clean Google account for testing new tools, and only bring in files you specifically want the tool to use. |
One thing worth noting: the permission screen says “Select all” but frames it as a choice. In practice, it’s all-or-nothing — you can’t proceed with partial permissions. That’s a real friction point for less tech-comfortable users, and worth flagging for your audience.
Inside Opal: The Landing Page and Builder
The Opal landing page — a gallery of sample apps built by the Opal team gives you an immediate sense of what’s possible.
Once you’re in, the landing page shows a gallery of sample apps — book recommenders, business profilers, playlist builders. It’s a good orientation to what Opal can actually do before you start building.
The blank builder canvas. Two prompts: add a step manually, or just describe what you want to build.
Creating a new app drops you into a clean canvas with a simple prompt: describe what you want to build. That’s it. No templates to configure, no settings to fumble through first.
The Build: “Is Google Opal Right For You?”
The app I set out to build was a three-question quiz. Users answer:
- Do they have coding skills?
- What do they want to build? (content workflow, lead magnet, research tool, or something to share)
- How comfortable are they with AI tools? (beginner, intermediate, or advanced)
Then Gemini analyzes their answers and delivers a plain-English verdict on whether Opal fits their situation, what they could realistically build, and one honest limitation to know about.
I pasted my full build description into the prompt box. Here’s what Opal generated:
The workflow Opal generated from my plain-English description. Three input steps feeding into an analysis node and an HTML output node — exactly the structure I described.
Fast, logical, and it matched my intent. The three input steps (Coding Skills, Project Goal, AI Proficiency) fed into an “Analyze Opal Suitability” node, which then passed to a “Generate Result Webpage” output. Clean.
What Didn’t Work: The Editing Attempt
I tried to manually edit the Gemini analysis step to use a custom prompt tuned to a plainspoken, no-hype tone. That didn’t take.
The editing interface accepted my input — then told me it couldn’t find the step to modify. A clear beta limitation.
The error message said it was “unable to find step ‘Analyze Opal Suitability’ to modify.” The editing interface looked functional but the modification didn’t stick. Worth knowing if you’re planning to tune outputs carefully.
Adding the Footer Step
Next I asked Opal to add one more step: a text output block that always displays the UnretiredDoug.com link. That worked cleanly.
The updated workflow after adding the footer step. The “Generate Review Message” node was added in about a minute.
The new node appeared in the workflow within about a minute. Adding steps conversationally is where Opal feels most natural.
Publishing and the Remix Warning
| ⚠️ Watch Out When you go to Share your app, “Allow access to editor view and remix” is toggled ON by default. That means anyone with your link could potentially copy your workflow. Turn it off before you share publicly if you want to keep your build to yourself. |
Once I turned that off, sharing was simple. Sharing the app automatically handled the publish step — no separate publish button required.
The published OpalFit app running live at opal.google/app/1nQ5xrxflUF2yt72XZvRTTVHLNtRuUvdc
The link opened cleanly in a new window and the app ran properly. The visual design Opal generated — the illustrated Google Opal decision diagram — was a genuinely nice touch I didn’t ask for.
The Honest Verdict
Google Opal is a legitimate experiment worth your time if you’re curious about no-code AI tools. It’s not fully baked — it’s clearly still in beta — but the core loop works: describe what you want, get a functional workflow, share a link.
For UD-style builders — people who want to create useful, shareable tools without writing code — it has real potential. A personalized recommender, a research workflow, a lead magnet mini-app: all realistic starting points.
The limitations are real too. Custom prompt editing is clunky. No persistent storage. The Console doesn’t give you much visibility. These are the kinds of things you’d only know from actually building something, which is exactly why I did.
Quick Reference: Google Opal at a Glance
Next in the Series
I have a list of Google tools to work through, and Opal was first. Next time, something a little more ambitious.
If you want to follow along as I build and test each one, you know where to find me.UnretiredDoug.c