Notes on SaaS architecture, AI integration, and compliance-ready engineering.
For regulated or sensitive workloads, where an AI feature is deployed matters as much as how it’s built. Here’s what changes inside your own security boundary.
Read moreLaunching an AI feature is the easy milestone. Keeping it accurate months later, after the data has shifted and the prompt has changed, is the real work.
Read moreThere is no single best AI model — only the one that fits a given use case on accuracy, cost, latency, and data-handling requirements for your product.
Read moreAn agent that can take action is powerful and dangerous in equal measure. The design question isn’t whether to add human review, but exactly where to put it.
Read moreA retrieval-augmented generation demo is easy. A version your security team signs off on and users can actually rely on is a different piece of engineering.
Read moreMost SaaS products don’t need active-active multi-region from day one. Here’s how to figure out exactly what your platform needs, and when it needs it.
Read moreA short list of architecture questions regulated SaaS founders should ask their engineering team before the platform is ever audited for the first time.
Read moreHow to integrate retrieval-augmented generation into an existing SaaS product without turning your next security and compliance review into a nightmare.
Read moreThe architecture decisions that separate a SaaS platform that grows gracefully from one that needs a costly rewrite the moment real customers show up.
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