AI Agent Engineer Roadmap

26 weeks / 9 phases / 62 modules / free + Telugu resources

The Agent Engineer roadmap, rebuilt with learning links.

Same practical path: Python, LLM APIs, RAG, agents, memory, guardrails, and cloud deployment. The upgrade: every module now has a free primary resource plus a Telugu YouTube companion wherever possible.

Tracker

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0/62 modules completed

Month

Daily list

Today

2-3 hour study plan

The day plan appears below: watch the assigned part, then practice that same topic.

    No tasks yet. Add suggested tasks or create your own.

    Roadmap

    Pick a phase, search a topic, open the resource.

    Portfolio

    Build these after the relevant phases.

    01

    Distributed Document Ingestion + RAG Pipeline

    PDF ingestion, semantic chunking, PII redaction, embeddings, hybrid search, graph RAG, evaluation, and citation-backed answers.

    Docling / Pinecone or Qdrant / Neo4j / FastAPI / LangSmith

    02

    Multi-Agent Natural Language to SQL

    Planner, SQL writer, validator, executor, and explainer agents with read-only database enforcement and benchmarked accuracy.

    LangGraph / PostgreSQL / FastAPI / Streamlit / LangSmith

    03

    Regulated-Domain Knowledge Base

    A clinical, legal, or finance knowledge base with evidence-backed answers, guardrails, monitoring, caching, and deployment.

    RAG / Graph DB / Guardrails / AWS / MLflow / Cost dashboards

    How to use

    Do not binge the links. Build your way through them.

    1. Learn the module

    Use the primary free resource for depth. Use the Telugu option when you want the concept explained in Telugu first.

    2. Practice the topic

    After watching the assigned part, spend focused time repeating and modifying the same examples.

    3. Fold it into a capstone

    At the end of a phase, combine your practice work into one portfolio-grade system with README, screenshots, traces, and eval numbers.