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In most production incidents involving “missing messages,” the queue is blamed early. SQS is down.The message was dropped.AWS lost it. True message loss inside managed queue infrastructure is extremel
Modern backend services rarely perform isolated work. A single request often fans out into multiple network calls, database queries and asynchronous operations. The service is effectively coordinating
Large language model APIs feel deceptively simple from an engineering perspective.You send a prompt, you receive text. Compared to provisioning databases, tuning JVM memory or debugging distributed locks, the integration looks almost trivial. A singl...
Over the last year, many products added AI features. Chat assistants, automatic summaries, classification, recommendations, drafting emails, generating documentation, suggesting actions. In many cases
Modern backend engineering increasingly revolves around distributed systems.As a consequence, many technical interviews — even for senior and leadership roles — are designed around deceptively simple
Over the last year, most conversations about AI in software engineering have revolved around speed. People ask whether engineers are now two, five, or ten times faster. The assumption behind that ques
Many teams say they “have observability”. Usually that means: CPU graphs memory usage request count maybe error rate Those are useful, but they are not observability. They are infrastructure vis
Over the last months I started using an AI coding assistant powered by large language models (Codex-style systems). I did not approach it as a novelty or productivity experiment. I approached it the s
Most backend systems don’t fail because of a bad initial design. Many systems start simple, clean and understandable. Early teams usually know every component, every database table and most side effec