Topic
Practical engineering: technical debt, security, APIs, choosing technology and working with AI in the build.
15 articles
"How much does an app cost?" has no honest answer without knowing the scope, platform and complexity. Here is what actually builds the price, and how to get an estimate you can rely on.
Read articleLanguage models don't know what they haven't seen. RAG means finding the most relevant parts of your documents before answering and handing them to the model. Here is the idea, the benefit and the limits.
Read articleArguing over the "best framework" is usually wasted time. The criteria that matter more are the team, the product's lifespan, the cost of change and replaceability. Here is a decision framework.
Read articleMany modern sites are well designed and yet invisible to search engines. Here is the technical checklist: server rendering, metadata, sitemap, canonicals, speed and structured data.
Read articleText is written for people, and a search engine has to guess its meaning. Structured data tells a machine outright what a page is about, who wrote it and which questions it answers.
Read articleWeb push lets a site or PWA send a message even when the user hasn't opened it. Used badly it is annoying, and in some conditions it isn't dependable. Here are the facts.
Read articleYou don't have to choose between building fast and building right. Draw the system's boundaries correctly from the start, put the simplest implementation behind each one, and grow later without a rewrite.
Read articlePayment providers, SMS, databases and AI models all change eventually. The ports-and-adapters pattern turns that change into replacing one file instead of rewriting the product. A plain explanation with real examples.
Read articleTechnical debt isn't always bad. Like a loan, taken deliberately and with a repayment plan it can help a product move faster. How to tell good debt from bad, and how to pay it down without stopping delivery.
Read articleWhen the API contract is written before the implementation, front-end and back-end teams work in parallel, disagreements surface early and integration at the end is no surprise. The approach and the design rules.
Read articleIn an AI product every answer costs money, and user growth can turn into growing losses. A multi-model gateway, the right model for each task, caching and usage caps make the cost predictable.
Read articleA good Persian or Arabic product isn't a mirrored English one. Direction, typography, digits, mixed-language text and icons each have their own rules. A practical guide to designing and building right-to-left interfaces.
Read articleDesign systems aren't only for large companies. With a few tokens, ten base components and a handful of clear rules, a small team can ship a consistent product and build faster. Where to start, and what you can skip.
Read articleAI tools have made writing code fast, but not deciding what to write. A team benefits from them when it already has a precise definition, a clear architecture and automated tests. The human role has changed; it hasn't gone.
Read articleSecurity isn't a feature you add later. A few simple decisions at the start — validating input, handling passwords and keys properly, least privilege and security headers — prevent most common incidents.
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