Building a Modern AI-Ready Backend: Web MVC, JNI, WebFlux, and Python RPC I designed and implemented a modular backend architecture that supports traditional Spring MVC services, native AI acceleration through JNI, reactive APIs using WebFlux, and remote Python-based inference. Through this project, I explored multiple approaches to bridging classical Java...

Agent S: A Local AI Automation Assistant As AI agents evolve, developers increasingly need tools that combine natural language intelligence with real executable automation. Agent S is an open-source, local-first AI automation assistant. It serves as an intelligent orchestration layer that connects multimodal AI capabilities with real executable tools, enabling...

Observability and Billing: Building Unified Dashboards for Operations and Finance In modern AI and data systems, observability and financial transparency must go hand in hand. Every request should not only deliver results but also record its full lifecycle, including latency, reliability, quality, and cost. By treating each request as a...

Human-in-the-Loop Review and Idempotent Write-Back: From /review to Auditable System Updates In any AI-driven workflow, some decisions are too important to leave entirely to machines. Before an automated result is allowed to change real business data, it should be reviewed by a person, especially when the decision carries risk or...

Evaluation and Redlines: Offline Baseline + Production Replay + Automatic Rollback Goal: A new model version should go live only when data proves it’s better, otherwise, it automatically rolls back.