The $0 to $10K MRR Playbook for AI SaaS
I took an AI product from zero to $10K MRR. Here's every step, every mistake, and the exact playbook I'd follow if I started over today.
Building an AI SaaS is different from building a traditional SaaS. The margins are thinner, the competition is brutal, and your users have already tried ChatGPT. Here's what actually works.
Step 1: Find the workflow, not the feature
Nobody pays for 'AI-powered X.' They pay for saving 4 hours a week on a task they hate. Find that task. Build for it. Ignore everything else until you have 10 paying customers who would be genuinely upset if your product disappeared.
Step 2: Ship ugly, ship fast
Your first version should embarrass you. Mine did. The UI was a single text input and a results panel. No onboarding, no settings, no dark mode. But it solved the problem in 30 seconds instead of 2 hours. That's all that mattered.
Step 3: Pricing from day one
Free tiers kill AI startups. Your API costs are real and they scale linearly with usage. Charge from day one.even $9/month.because users who pay $0 don't give useful feedback. They just complain about rate limits.
The best market research is a credit card form.
Step 4: Build distribution before features
I spent 60% of my time on distribution and 40% on product. Twitter threads, blog posts, community engagement, cold DMs to potential users. The product doesn't matter if nobody knows it exists. By the time I had a polished V2, I already had an audience waiting for it.
The timeline
Month 1: MVP + 10 beta users. Month 2: $500 MRR from direct outreach. Month 3: $2K MRR from organic + referrals. Month 5: $10K MRR with a product that actually worked well. The secret isn't a hack.it's doing the boring stuff consistently while everyone else is tweaking their landing page.
Written by
Dayssam Bakaar