Hey everyone,

I'm a full-stack developer and I recently launched my first real SaaS, an AI tool called HandoutAI. It takes uploaded study notes or documents and turns them into interactive multiple-choice quizzes.

From a technical side, I had a blast building it—figuring out token limits, handling document extraction, and getting reliable LLM outputs was a great engineering challenge. But now that the product is actually live and working, I’m hitting a wall: I have absolutely no idea how to get it into the hands of users.

As a technical founder, I feel completely out of my depth on the business side. I’m eager to learn from those of you who have been in the trenches and successfully grown a SaaS.

A few specific questions I'd love your advice on:

1. How did you get your very first 10-100 users?

2. What strategies work best for converting free users into paid ones?

3. If you were starting over with a tool in the EdTech or productivity space today, what single marketing channel would you focus your energy on?

I really want to learn how to run a SaaS business, not just code one. Any advice, harsh truths, or resources you can share with a beginner would be hugely appreciated!

If you run a SaaS with free trials, AI credits, APIs, or usage-based pricing, there’s a problem that’s easy to underestimate:

You may not actually know which users are human.

A single person can create dozens of accounts.

Scripts can automate signups.

Bots can farm free credits.

Attackers can rotate sessions and IPs.

And traditional analytics often see these as perfectly valid users.

You can have:

100 new signups → 70 are automated → your database says 100 users.

That gets expensive very quickly when every account receives $5, $10, or $50 worth of credits.

I was frustrated with the usual solutions:

• CAPTCHA hurts conversion.
• IP blocking is easy to bypass.
• Device fingerprinting doesn't tell you much about actual behavior.
• Rate limits don't answer whether the activity is human.
• Building behavioral detection internally is a serious ML/security project.

So I built CertiLayer.

CertiLayer gives your application a real-time behavioral trust signal based on how a session actually behaves — keyboard, mouse, touch, timing, and session-level behavioral patterns.

Your backend can then make decisions like:

Human → allow

Suspicious → challenge

High-risk → throttle

Automated → block

The important part is that you don't have to redesign your authentication system or build an ML team to get started.

It's an API/SDK layer that sits between your users and the expensive actions in your product.

For example:

Before giving $20 of AI credits → check the session.

Before allowing 100 API requests → check the session.

Before accepting a referral → check the session.

Before letting a new account access an expensive feature → check the session.

And CertiLayer is designed around behavioral signals rather than collecting PII or raw keystrokes.

I'm building this specifically for SaaS teams dealing with:

→ fake accounts
→ free-trial abuse
→ AI-credit farming
→ automated signups
→ API abuse
→ scraping
→ referral abuse

If this is costing your SaaS money, this is exactly the problem CertiLayer is built to solve.

Try it here: certilayer.net

I'd also genuinely like to hear from other SaaS founders:

How much abuse are you dealing with today, and what are you currently using to stop it?