ProdAIStack
Independent field notes for production AI

Engineer AI
that holds up
in production.

Understand the architecture. Follow a deliberate curriculum. Build and verify the real system.

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PRODAI / SYSTEM MAPLIVE REFERENCE
REFERENCE FLOW VERIFIED
Production AI request architectureA request moves from client through application, gateway, model, validation and response, with fallback, observability and evaluation branches.Client01Application02Gateway03Primary model04Validation05Response06FallbackObservabilityEvaluation
2 Guides1 Paths2 Builds
01 / Understand02 / Practice03 / Verify
01
Knowledge

Articles

Deep explanations of architecture, reliability, retrieval, and evaluation.

02
Curriculum

Learning Paths

Ordered journeys that connect concepts to practical implementation.

03
Practice

Projects

Hands-on systems with source code, experiments, and verification evidence.

Latest field notes

Read what matters
after the prototype.

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Featured curriculum / 01

Production AI Foundations

Learn the architecture and hands-on engineering practices required to move from a model call to a reliable production AI system, then extend that foundation into production RAG with versioned ingestion, hybrid retrieval, authorization, citations, observability, and evaluation.

4
Steps
3h
Duration
advanced
Level
Enter learning path
  1. 01
    LearnProduction AI System Design: From Model Call to Reliable Product
  2. 02
    BuildProduction AI System Design Lab
  3. 03
    LearnProduction RAG Architecture: Ingestion, Retrieval, Citations, and Evaluation
  4. 04
    BuildProduction RAG Architecture Lab
Hands-on project library

Learn by shipping
the whole system.

Each project turns a production AI concept into an implementation you can inspect, run, and extend.

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01Real architecture02Runnable source03Verification evidence
01 / ProjectVerified
Production AI architecture showing an application service, model gateway, LLM provider, reliability controls, observability and evaluation
advanced / 1 technologies

Production AI System Design Lab

Build and test the reliability layer around a production LLM application, including contracts, validation, retries, idempotency, fallback routing, observability, and release gates.

TypeScript
  • Typed AI Application Contract
  • Minimal Model Gateway
  • Provider Adapter
02 / ProjectVerified
Production AI architecture showing an application service, model gateway, LLM provider, reliability controls, observability and evaluation
advanced / 2 technologies

Production RAG Architecture Lab

Build and test a production RAG architecture with versioned ingestion, hybrid keyword and vector retrieval, RRF fusion, authorization filtering, reranking, context assembly, citation validation, evaluation metrics, and release gates.

TypeScriptNode.js
  • RAG Application Contracts
  • Idempotent Ingestion and Versioning
  • Versioned Chunker