Data Architecture

Part 2: Hierarchical Memory — Episodic, Semantic & Temporal Graphs

← Previous Chapter: Part 1: Swarm Topologies | Series Hub | Next Chapter: Part 3: Resilient Tool Calling → Answer-first: Efficient agent memory requires a 3-tier hierarchy: (1) Working Memory (short-term buffer in Redis), (2) Episodic Memory (summarized past trajectories in PostgreSQL), and (3) Semantic Memory (entity relationships in a Temporal Knowledge Graph).

Part 3A: Enterprise RAG Architecture & Codebase Vector Indexing

← Previous Chapter: Part 3A: Cursor Rules | Series Hub | Next Chapter: Part 3B: AI Automation for Internal Ops → Answer-first: Codebase RAG requires Abstract Syntax Tree (AST) chunking to preserve function and class boundaries, combined with Hybrid Search (BM25 for exact symbols + dense embeddings for semantic search) and cross-encoder reranking.

Part 7: Phase 2 — Dual-Write: CDC & Kafka Synchronization

← Previous Chapter: Part 6: Phase 1 — Strangler Fig | Series Hub | Next Chapter: Part 8: Phase 3 — Full Cutover → Answer-first: Dual-writing at the application layer creates race conditions and split-brain states. Instead, Phase 2 implements Change Data Capture (CDC) via Debezium reading the MySQL binlog directly, streaming event deltas through Apache Kafka to populate PostgreSQL microservice databases asynchronously. flowchart LR MagentoAdmin["Magento Admin Update"] --> MySQL["Magento MySQL"] MySQL -->|"Binlog Stream"| Debezium["Debezium CDC Connector"] Debezium -->|"JSON Event Deltas"| Kafka["Kafka Topic: magento.catalog.products"] Kafka -->|"Consumer Group"| GoSync["Go Catalog Sync Worker"] GoSync -->|"Upsert JSONB"| Postgres["Target PostgreSQL"]