A weekly system to learn more than most startups do in a month

For solo builders, speed is everything — especially when it comes to product experiments.

Here’s a system for using AI to run five micro-experiments a week.

What qualifies as a micro-experiment?

A micro-experiment is small by design — built to get signal fast.

Examples:

• A new headline on your landing page

• Two subject line variants for a welcome email

• A button redesign with different copy

• A tweak to onboarding — like asking one more question (or one less)

• A social post with a new hook or CTA

If it helps you answer a question faster, it counts.

If it takes more than 1–2 hours to build and launch, it’s probably not “micro.”

1. Start with 5 questions, not 5 features

Before building anything, write down five things you're unsure about. Not features — questions. For example:

• Are users confused by my landing page?

• Does my headline make them want to read more?

• Would a different CTA convert better?

• Is onboarding too long?

• Do people get what this product even does?

Write 5 questions like that. That’s your backlog for the week. If you’re drawing a blank, prompt AI:

"I'm building a [product] for [audience]. Suggest 10 small experiments I can run this week to test clarity, conversion, or engagement."

2. Use AI to spin up the test fast

Each experiment should take under 2 hours to build and launch. AI makes that possible.

Want to test copy?

"Write 5 headline variations -- one clear, one emotional, one benefit-led, one bold, one urgency-driven."

Swap it into your site. Launch.

Want to test pricing layout?

"Create a pricing mockup for freelancers. Show monthly vs annual. Highlight one plan as 'best value.'"

Use Figma, Framer, or V0.dev to mock it up fast.

Want to test onboarding?

"Write a 3-step onboarding flow that helps [user type] reach [outcome] quickly. Keep it friendly and clear."

Use Cursor, Framer, or V0.dev. Keep it light.

Reminder: Don't overbuild. You want something testable, not polished.

3. Get the test in front of real people

You don’t need thousands of users. You need signal.

Start with people already in your orbit:

• Previous users

• People who’ve shown interest

• Friends, clients, or peers in your space

• Other founders

Ask:

"Trying out a quick experiment -- mind taking a look and telling me what's confusing or missing?"

Then widen the circle:

• Niche subreddits

• Slack groups

• Small newsletters

• Founder communities

Use something like Jotform’s AI agent or another site chatbot. Set it up with focused prompts like:

• “What’s confusing?”

• “Would you try this?”

• “What’s missing?”

Even 5–10 responses is enough to learn from.

4. Use AI to summarize feedback and find the signal

Once feedback comes in, don’t disappear into spreadsheets.

Feed the raw data back into AI:

• “Summarize this feedback. What’s confusing? What’s landing? What should I fix?”

• “Compare version A and B. What worked better, and why?”

• “Suggest 3 follow-up experiments based on these results.”

You’re not looking for statistical proof. You’re looking for insight that moves you forward.

If you’re clearer than you were on Monday — that’s a win.

5. Log what you learned and queue up what’s next

The value compounds only if you keep track of it.

At the end of each week, open a doc or Notion page. For each experiment, fill in:

• Hypothesis

• What you changed

• What you observed

• Next move (double down / pivot / discard)

If writing it feels like friction, don’t.

Just tell ChatGPT or Gemini:

"Write a short weekly summary of these 5 experiments. Include what I tested, what I learned, and what I'm doing next."

Over time, it adds up to deep understanding — of your users, your product, and what actually moves the needle.

Tools that fit this process:

These tools won’t get in your way:

• AI Assistants: ChatGPT (GPT-4o), Claude, Gemin

• Execution: Cursor (code), Framer / Webflow (frontend), Jotform (feedback)

• Tracking & Analysis: Notion / Sheets / Airtable, Hotjar / Clarity, Vercel Analytics / Simple Analytics

• Automation (optional): Zapier, Make

Use what works. Ignore what doesn’t. The system is what matters — not the stack.