我如何利用 AI 在 150 次提交 (22 天) 內建構一個全端 SaaS 平台

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How I Built a Full-Stack SaaS Platform in 150 Commits (and 22 Days) with AI

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From zero to launch: Hand-rolled auth, AI chatbots, and shipping at ludicrous speed

It’s December 31st, 2025. I’m launching Synapse — a multi-tenant SaaS platform I built from scratch.

The first commit? December 9th.

22 days. 150 commits. One developer. Let’s talk about how that happened.

The Scope

I wanted to build a platform where teams connect their data warehouses (BigQuery, Snowflake, Redshift, ClickHouse, MotherDuck) and query them via an AI chatbot. “ChatGPT for your company’s data.”

That “simple” idea actually required:

In the “before times,” this is a 6-month project with a team. With AI? 22 days solo.

What We Hand-Rolled

🔐 Native JWT Authentication

No Supabase. No Auth0. Just bcrypt password hashing and JWT tokens with:

When I needed secure token logic for invites, I didn’t have to fight some third-party’s opinions.

💬 Real-Time AI Chatbot

The crown jewel. A WebSocket-based chat where users:

The schema service introspects 5 different warehouse APIs and converts them to LLM context. Building this alone could’ve taken weeks — AI assistance made it days.

🔌 SQL API for Programmatic Access

Beyond the chatbot, users needed programmatic access. So we built a full SQL API system:

It’s like building a mini-Retool: define your query, get a REST endpoint, share the API key. Users can integrate Synapse data into dashboards, scripts, or other applications.

💳 Stripe + Frontend Guardrails

Full Stripe integration with checkout, customer portal, and webhooks. The clever bit: frontend-only subscription guardrails. Instead of complex backend usage tracking, we just count the data already rendered:

Simple, effective, no new infrastructure.

📧 Password Reset & Org Invites

Two deceptively complex flows built with the same secure pattern:

Both features? About 2 days total.

The AI Factor

I paired with AI for virtually every feature — not just boilerplate, but architecture decisions, implementation patterns, debugging, and documentation.

The AI didn’t make decisions for me. It helped me explore options faster, implement patterns consistently, and maintain coherence across 50+ backend files and 40+ frontend files. When you’re moving at 7 commits/PRs per day, that consistency matters.

The Timeline

Some days were 15+ commits of pure shipping. Others were 3 commits of “why is CORS still broken.”

Lessons Learned

What’s Next

After launch: data visualization, more LLM providers, team collaboration features, and whatever users tell me they need.

22 days ago, Synapse didn’t exist. Today it’s a real product with authentication, multi-tenancy, AI chat, billing, and a programmatic API.

The future isn’t AI replacing developers. It’s developers with AI shipping what used to require teams.

Just like Synapse, AI also wrote this article. 😉

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Written by Sam McCaffrey

Life Through Data

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