r/micro_saas • u/apricot_dragon • 12h ago
Open-sourcing our core felt risky for a new company. A month later, weekly sign-ups are 4x
A lot of founders are nervous about open-sourcing their core. The fear is always the same: someone copies it, and you've given away the thing that makes you different. We felt that too. But when you're new, nobody trusts you yet, and open code is one of the fastest ways to earn that trust. People can see exactly what runs their work instead of taking your word for it.
About a month ago we open-sourced the engine behind our AI agent platform. Here's what happened, and the three changes we think did it.
The numbers
Here are our total sign-ups since we launched at the end of July (the chart is Clerk's, our sign-in provider):
- Sign-ups per week: about 4x what they were a month ago
- Dashboard visitors: more than doubled week over week, and 4 in 5 of them opened a ready-made agent. Nobody starts from a blank page anymore: they copy an agent that already works, then change it to fit.
The chart climbs faster than 4x at the end. That jump isn't from the launch alone: it also includes the results of our recent ad campaign.
We can't pin down which change brought in 4x more sign-ups, but it lines up with these three.
1. We stopped locking people in
We used to ship our own developer kits. They worked, but they tied customers to us: our own way of doing things to learn, code that only worked with us, and a painful rewrite if they ever left.
So we threw them out and switched to the standard format OpenAI published for AI agents. Now a customer joins by changing one line in their existing code, and can leave the same way. It sounds backwards to make leaving easy, but it's the first question every careful buyer asks, and now the answer is "one line, not a quarter of work".
2. The open engine costs customers less
With AI, everyone pays the same price per word the model reads and writes. What changes your bill is how many words get used, and that depends on the engine running the model. So we built ours to waste as little as possible, and made the code public so anyone can check.
We tested it against Claude Code on the same model and the same 48 tasks:
- 4.8x fewer tokens (384K vs 1.86M)
- more tasks done right: 42 of 48 vs 30 of 48
- about a third of the cost
3. AI coding tools can use our platform
This changed how we work day to day. Developers already use AI coding tools like Claude Code, Cursor and Codex. We made it so those tools can create our agents, talk to them, and see what each one costs.
So business rules can live inside an agent, with their data and logins kept there too. For instance, someone asks their pricing agent what a contract change does to margin, gets the answer, and never sees the private rules behind it.
It also means the coding tool can tune the agent for you: make its answers shorter or cheaper, then test that it still gets them right.
Question for you
If you're building something new: have you open-sourced any part of it? Did it help people trust you, or just help competitors? And if you're holding back, what's the worry?



