Articles
Practical notes on building and shipping SaaS products with AI coding agents. These are the workflows, deployment choices, launch checks, and architecture decisions behind Stacknaut.
I write about the parts that tend to break after the prototype works: auth, billing, infrastructure, prerendered SEO pages, agent setup, and how to keep a growing codebase understandable enough for both humans and coding agents.
Why I Use Stripe for SaaS Billing
Why Stripe works well for SaaS billing: hosted Checkout, subscription webhooks, billing portal, and how Stacknaut wires it into the app.
Why I Use Terraform for SaaS Infrastructure
Why Terraform is useful for small SaaS infrastructure, how Stacknaut uses it with Hetzner, and where Kamal takes over deployment.
Magic Link and Google Auth for a Small SaaS
Why magic link plus Google Sign-In is a practical auth setup for a small SaaS, and how Stacknaut wires both into one user model.
Skills vs MCPs vs Slash Commands vs CLIs
Skills vs MCPs vs slash commands vs CLIs — what each one does, how they differ, and when to use each one in Claude Code, Codex, and Droid.
Vue Pre-Rendering with Vite for SEO
Vue pre-rendering with Vite for static SEO meta tags: rendered routes, canonical URLs, Open Graph tags, Caddy rewrites, and hosted service tradeoffs.
Build a SaaS with AI Coding Agents
What actually works after shipping real production SaaS products with AI coding agents — the workflow, the stack, and the engineering practices that matter.
Turn an AI Prototype Into a Production SaaS
Move a Lovable, Bolt, Replit Agent, v0, or Cursor prototype toward production: repo ownership, backend, billing, deployment, logs, and launch checks.
SaaS Post-Launch Hardening Checklist
Security, data protection, resilience, performance, and operational maturity — the checklist for tightening up your SaaS in the weeks after launch.
The SaaS Launch Checklist I Wish I Had
A practical, technical checklist for launching a SaaS product — infrastructure, auth, billing, SEO, monitoring, and the smoke tests to run before launch.
How Do You Manage a Big Monolith with AI Coding Agents?
How to handle growing interdependencies in a large codebase when you're using AI agents to write the code — principles that work for managing a dev team.