Debugging is more important than features
My blog returned 404 on every page at 2 AM. I had zero visibility into why. Here is the debugging infrastructure I wish I had set up from day one.
I ship the parts of your SaaS that are hard to get right.
Full-stack contractor. Payments and billing integrations, AI agents that survive production, and end-to-end product builds. Remote, UTC+1
// What I take on Three things, done properly
01
Payments & billing
Stripe and beyond: subscriptions, metered billing, webhooks that don't drop events, and migrations that don't double-charge anyone. The edge cases other people skip
02
AI agents in production
Not a demo. Agents with real context, guardrails, observability, and a token budget. Built to run reliably against your data
03
Full-stack SaaS
Owning a build end to end: architecture, infra, frontend, the lot. Pragmatic over perfect. I optimize for what you can maintain after I leave
// Featured writing From the blog
Architecture is more important than clean code
I spent 2 weeks making my serverless functions clean. The architecture was wrong. I rewrote everything as a single Express server and it was simpler.
// Archive All articles
Why the perfect code is less maintainable
I spent 3 hours reviewing a 200-line PR that handled every edge case. A 40-line version with a TODO would have been better. Here's why perfect code slows you down.
I was paying Stripe to process 3 payments a month. Then I checked the alternatives.
Stripe is the default answer for online payments. But if you only need one payment method, you're paying for features you'll never use. Here's what I found when I actually compared providers.
Social media link previews in React: server-side user-agent detection
How to handle Open Graph meta tags for LinkedIn, Google, and Discord previews in a React SPA using server-side user-agent detection with nginx or .htaccess.
AI-powered git branch diff summary: give your AI agent real context
How to generate a smart summary of branch diffs. Highlights deleted files and renames to give AI agents the context they need to review, refactor, or document code.
Testing Lambda and EventBridge locally without deploying
How to test AWS Lambda functions and EventBridge rules locally using SAM, LocalStack, and docker-compose. No cloud deployment needed.
AI-generated infrastructure is a maintenance nightmare
I asked AI to generate Terraform for a standard AWS setup. It produced 2,400 lines that worked perfectly. Here's why I'd never deploy it to production.
Checking your AI's context window: what fits and what doesn't
How to verify the actual context window of an LLM, understand external vs internal context, and avoid the silent truncation problem.
Token economy: how I stopped wasting context windows with LLM memory
How loom-memory turns a Git repository into a persistent knowledge base for AI agents. Reduce token spend by giving models durable context instead of cold reads.
Need a contractor for the hard parts of your SaaS?
Payments and billing, AI agents in production, or owning a full-stack build end to end. Remote, UTC+1. 20 minutes is enough to know if it's a fit
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