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Practical articles and engineering guides on Production AI: security, observability, evaluation, cost control, and deployment onto real infrastructure.
AI agent security for developers: why the prompt is never the security boundary, and how to handle prompt injection, tool permissions, unsafe model output, data leaks, authorization and runaway cost — with real failures and code from three .NET AI projects.
Read article →How to prevent SQL injection in AI-generated SQL: a least-privilege database user, a real T-SQL parser with an allow-list, cost limits, safe tool queries and a prompt that is never the security boundary. With code for ASP.NET Core and SQL Server.
Read article →OpenTelemetry traces and metrics across the whole pipeline, an audit log in a separate database, and a hardened container. Then a 132-question workload: the model is 96% of the time, and the first trace found a 2-second IPv6 localhost penalty on every new connection.
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