@suraj_sharma14: If I had 6 months to become a GenAI Engineer. I'd do this. Stage 1: Python + Async Architecture FastAPI, asyncio, typin…

If I had 6 months to become a GenAI Engineer. I'd do this. Stage 1: Python + Async Architecture FastAPI, asyncio, typing, Pydantic v2, event-driven design, API integration patterns. Stage 2: Multimodal LLM Fundamentals Transformer architecture, SLMs vs LLMs, context window management, vision/audio inputs, token economics. Stage 3: Structured Outputs + Prompt Ops JSON schema enforcement, function calling, prompt versioning, template management, few-shot optimization. Stage 4: Advanced RAG + Knowledge Graphs Hybrid search, graph RAG, semantic reranking, metadata filtering, citation grounding, incremental indexing. Stage 5: Agentic Workflows + Orchestration LangGraph/LlamaIndex, tool use, planning loops, multi-agent collaboration, human-in-the-loop handoffs. Stage 6: Production GenAI Applications Streaming responses, optimistic UI, fallback models, rate limiting, cost-aware routing, session management. Stage 7: Evaluation + Quality Assurance LLM-as-a-judge, automated eval harnesses, regression testing, hallucination metrics, RAGAS/DeepEval. Stage 8: Inference + Infrastructure Optimization vLLM/SGLang, quantization (FP8/INT4), KV caching, speculative decoding, edge deployment, model distillation. Stage 9: MLOps + Observability Distributed tracing, latency monitoring, cost dashboards, drift detection, CI/CD for prompts and models. Stage 10: AI Safety + Compliance Guardrails, prompt injection defense, PII redaction, copyright checks, EU AI Act compliance, content filtering. Stage 11: Open Source + Portfolio Ship multimodal agents publicly, write technical deep dives, record demo videos, contribute to orchestration libs. Stage 12: Apply GenAI Engineer, AI Application Developer, LLM Infrastructure Engineer, Autonomous Systems Engineer roles. Most people stay stuck watching tutorials. Builders get hired. (Bookmark it)