AI Engineering roadmap maps LLM fundamentals to agents, evals, and safety
debashis_dutta · x · 2026-09-11
systemdesignone shared an AI Engineering roadmap as a tree-style index covering seven areas: LLM fundamentals (transformers & attention, inference & decoding, tokenization, context windows), prompting & context (context engineering, structured outputs, constrained decoding), representations (embeddings, vector databases, hybrid retrieval), RAG (chunking, reranking, GraphRAG), tools & agents (function calling, agentic workflows, memory & state, MCP, A2A, human-in-the-loop), evaluation (evals, datasets, online metrics, tracing), and safety (guardrails, AI security, prompt-injection defense). Useful as a self-study framework for AI engineers.
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