How I Built an Enterprise POS System Alone with AI

I've been building software for 30 years. Fifteen of those years were spent in the POS industry — building, deploying, and maintaining point-of-sale systems for restaurants, retail stores, and quick-service chains. In August 2025, I started POSAIC: an enterprise-grade POS with 12 business domains, built entirely by one person with AI as my co-developer. This is the story of how and why.

Why Build Another POS?

After fifteen years in the industry, I watched POS evolve from on-premise software you bought once to cloud subscriptions that drain small businesses monthly. Square charges $60-165/month. Toast locks you into 2-year contracts with $799 hardware. Clover takes 3.5% + 10 cents per transaction.

The technology exists to build a full-featured POS that runs locally, costs nothing, and gives merchants complete ownership of their data. The only reason it hasn't been done is that it's not profitable in the traditional venture-backed model. But a solo developer with AI doesn't need venture funding.

The Architecture Decision

I chose a stack that would have been impossibly ambitious for a solo developer five years ago:

• Rust + Tauri v2 for the backend — type-safe, blazing fast, cross-platform desktop app with native performance.
• SQLite for local storage — battle-tested, zero-config, handles millions of transactions.
• Event Sourcing + CQRS for the data model — every state change is an immutable event, making sync and audit trivial.
• Hybrid Logical Clocks for distributed ordering — enables conflict-free P2P sync without a central server.
• Vue 3 + Pinia + UnoCSS for the frontend — reactive, fast, and maintainable UI.

This stack gives POSAIC the architectural foundation of systems that typically require 20-50 engineer teams. The event sourcing model alone would normally take a team months to implement correctly. With AI assistance, I had a working event store with Hybrid Logical Clock ordering in two weeks.

How AI Changed Everything

I use Claude (Anthropic) as my primary AI collaborator, running through Cursor IDE and Claude Code CLI. Here's what surprised me most about AI-assisted development:

• Domain modeling became conversational. I could describe a business domain — "order management with split payments, tips, refunds, and kitchen routing" — and iterate on the aggregate design in natural language before writing a line of code.
• Boilerplate vanished. CQRS requires a lot of repetitive code — command handlers, event handlers, query projections. AI generates these patterns consistently and correctly once it understands the project conventions.
• Testing became thorough. I'd describe edge cases in English and get comprehensive test suites. "What happens when a split payment is partially refunded after a shift close?" — AI would generate the test scenarios I might have missed.
• Cross-language fluency. Moving between Rust backend and Vue frontend in the same session, with AI understanding the IPC bridge between them, eliminated the context-switching tax that slows down full-stack development.

The 12 Domains

POSAIC has 12 bounded contexts, each with its own aggregate, commands, events, and queries:

Each domain follows the same pattern: commands validate business rules, emit events, and events are projected into read models. The saga domain handles cross-domain workflows like "when an order is paid, update inventory and record a ledger entry." This architectural consistency meant AI could generate new domains by referencing existing ones — the twelfth domain took a fraction of the time of the first.

What I Learned

• AI amplifies experience, it doesn't replace it. My 30 years of architecture decisions informed every prompt. AI wrote the code, but I made the design choices. A junior developer with the same AI tools would build a fundamentally different (and likely worse) system.
• Constraints matter more than features. I spent more time telling AI what NOT to do (no unwrap() in Rust, no f64 for money, no direct state mutations) than asking for features. The CLAUDE.md file in our repo is essentially an AI constitution for the project.
• Solo doesn't mean lonely. AI pair programming is genuinely collaborative. I often think through problems by explaining them to Claude, the way you would to a colleague. The rubber duck debugging effect is real, but the duck talks back with useful suggestions.
• The economics changed. A system that would have required $2-3M in developer salaries and 18 months with a traditional team was built for the cost of AI subscriptions and my time. This is why POSAIC can be free — the development cost structure is fundamentally different.

What's Next

POSAIC is launching in 2026 with the core POS application. Online ordering, self-service kiosk, and digital signage are on the roadmap. The same AI-assisted development process that built 12 domains in 8 months will continue to accelerate feature delivery. If you're a small business owner paying monthly POS fees, I built this for you. If you're a developer curious about AI-assisted architecture, I'd love to share what I've learned. And if you're a POS vendor charging $100/month for what should be free — we're coming for your market.