2026 Modern AI Search & RAG Roadmap - Learning Roadmap | Nemorize

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Learning Topics

This roadmap covers the following topics:

✅ Foundations of Modern AI Search

✅ Semantic Search Principles
- ✅ Vector Embeddings
- ✅ Cosine Similarity & Distance Metrics
✅ Vector Database Architecture
- ✅ ANN Algorithms
- ✅ Vector DB Selection
✅ Hybrid Retrieval Systems
- ✅ Sparse vs Dense Retrieval
- ⚪ Metadata & Filtering
- ✅ Reranking Models
✅ Query Understanding & Intent

✅ RAG Architecture & Implementation

✅ Classic RAG Pipeline
- ⚪ Query Processing
- ⚪ Context Augmentation
- ⚪ Response Generation
✅ Agentic RAG Systems
- ⚪ Query Decomposition
- ⚪ Multi-Hop Reasoning

✅ Data Pipeline & Indexing

✅ Document Processing
- ⚪ Smart Chunking
- ⚪ Multimodal Processing
✅ Embedding Pipeline
- ⚪ Batch Processing
- ⚪ Incremental Indexing
✅ Data Freshness & Lifecycle

✅ Evaluation & Quality Metrics

⚪ Retrieval Metrics
- ⚪ Precision & Recall
- ✅ Ranking Quality
⚪ Generation Quality
- ⚪ Faithfulness Testing
- ⚪ Citation Coverage
✅ Grounding & Hallucination Control

✅ Production Deployment & Optimization

⚪ Performance Optimization
- ⚪ Caching Strategies
- ⚪ Latency Optimization
⚪ Infrastructure & Security
- ⚪ Access Control
- ⚪ Observability
- ⚪ Cost Management

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