Genai

Diagnose AI agents that repeatedly call tools, revisit the same state, or fail to converge on a result.

Scenario-based AI engineering interview preparation covering RAG, evaluation, reliability, and production trade-offs.

A practical, connected roadmap from Python and ML foundations to LLMs, RAG, agents, evaluation, production AI, and cloud architecture.

Production GenAI architecture interview scenarios covering RAG, agents, security, cost, evaluation, and reliability.

A design case for tool-using AI agents with bounded execution, authorization, observability, and safe failure handling.

A requirements-first architecture pattern for designing a production retrieval-augmented generation platform.

Diagnose unsupported RAG answers by separating retrieval, context construction, model behavior, and evaluation failures.