Ship AI Fast: the AI SaaS boilerplate I’m building so makers stop reinventing auth + LLM glue
There’s a pattern I couldn’t unsee.
Day one: someone spins up a chat UI. Tokens stream. Friends get a Loom. “Shipping this weekend.”
Week one: cookies won’t stick. Password reset is weird. “Almost done with auth.”
Week two: Stripe Checkout works in test mode. Webhooks don’t. The user is “paid” in the UI and free in the database.
Week three: they try to bolt on RAG from a tutorial. Then agents. Then “why is the OpenAI bill $180 for eleven users.” Launch slips. Energy dies. The idea was never the problem.
I lived pieces of that myself. I’d open the editor meaning to build the product — the thing users would actually pay for — and spend the day on glue. Webhooks. Entitlements. Routing. Another half-working memory layer. By Friday I’d shipping infrastructure again, not software anyone cared about.
Generic SaaS kits helped with the web side and left the AI side at zero. App builders got me a pretty demo I didn’t really own. Generating everything from an empty repo felt fast until every feature invented a new shape of chaos.
So I started building Ship AI Fast — not another landing page, an answer to that week-three death spiral.
One ownable codebase: auth, Stripe, entitlements, an AI gateway, RAG, agents, observability, local LLMs that aren’t an afterthought. The boring platform in one place, so the interesting product can finally get the calendar.
I’m still deep in building it. Waitlist’s open for makers who want the zip when it’s ready — pay once, own the code.
If you’re in week two right now, staring at a webhook log: you’re not alone. What’s eating your time — billing, RAG, or agents? I’m prioritizing whatever hurts most.
The week-three death spiral is a real pattern. I'd keep validating whether founders are buying an AI boilerplate or confidence that they can spend their next month learning from users instead of debugging infrastructure. That's the outcome they'll actually pay to accelerate.
I totally agree
One thing I'd be curious to learn is what founders expect to be doing with the time they save.
If the answer is talking to users, you've removed a bottleneck. If it's building more features, you've mostly shifted where the bottleneck lives.
I had used my time talking to possible customers
That's probably the highest-leverage use of that recovered time.
I'd keep watching whether the founders using it actually spend more time talking to users, or whether the saved time gets absorbed by building faster. The first creates learning velocity; the second can just accelerate the same cycle.