Insights
Engineering notes on custom software, web, mobile & AI
Practical, technically specific notes on the decisions behind custom software, web and mobile development, and applied AI.
Custom Software vs SaaS: When Should a Business Build Its Own System?
Custom software earns its cost once a workflow can't be represented cleanly by an existing product — when integrations, permissions, automation, or data ownership become more expensive to work around than to build.
Read noteCloud AI vs Local AI Deployment: Privacy, Latency, Cost and Control
Cloud APIs, privately hosted cloud models, and local GPU deployment each shift privacy, latency, cost, and maintenance responsibility to a different place. Here is how to choose.
Read noteHow AI Models Are Integrated Into Production Web Applications
A trained model is not a product. Here is the architecture — inference API, versioning, failure handling, and frontend UX — that turns a model into a reliable feature.
Read noteHow Computer Vision Can Be Integrated Into a Web Application
From camera permissions to real-time pose analysis: the practical architecture behind computer vision features in a browser or mobile app.
Read noteLaravel vs Next.js for Different Types of Business Applications
Both are strong choices. The right one depends on what the application actually needs to do, not which is more popular.
Read noteWhat Goes Into Building an AI-Powered Web Application?
AI features live or die on the plumbing around the model. Here is what actually needs to be built to get AI output in front of real users.
Read noteWhen Should You Train Your Own AI Model Instead of Using an API?
Third-party AI APIs cover most use cases. Here is a practical framework for the specific situations where training a custom model is the better call.
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