GenAI Implementation Isnt Magic — It’s a Lifecycle

▤ Summary

This article explains the end-to-end lifecycle for building GenAI applications, from requirement gathering through monitoring and continuous improvement. It emphasizes that successful GenAI projects need structured planning around data strategy, model selection, prompt engineering, and architecture design. It also highlights the importance of integration, security guardrails, testing, deployment, and observability before a system goes into production. The core message is that GenAI implementation works as an ongoing lifecycle, not a one-time build. The article positions RAG, orchestration, and monitoring tools as key enablers of reliable enterprise GenAI systems.

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