AI Native System Design
A 12-week program focused on designing systems where AI is a first-class citizen — not bolted on. You'll build RAG pipelines, vector-native architectures, and AI-first data platforms that scale.
12
WEEKS
48+
HOURS
12
PROJECTS
$899
PER YEAR
RESPONSE
What You'll Learn
12 weeks of deep, practical content. Each week builds on the last.
AI-First Architecture Principles
- Why AI-native is different from AI-bolted-on.
- Data flow patterns for AI systems vs traditional CRUD.
- Designing for probabilistic outputs and graceful degradation.
- Cost modeling for AI workloads — tokens, embeddings, inference.
Embedding Pipelines at Scale
- Chunking strategies that preserve semantic meaning.
- Embedding model selection — OpenAI, Cohere, open-source trade-offs.
- Batch vs streaming embedding pipelines.
- Versioning embeddings and handling model upgrades.
Vector Database Deep Dive
- Pgvector, Pinecone, Qdrant, Weaviate — when to use which.
- Index types: HNSW, IVF, PQ — performance trade-offs.
- Metadata filtering, hybrid search, and multi-tenancy.
- Scaling vector stores to billions of embeddings.
Production RAG Architecture
- End-to-end RAG pipeline design for enterprise use cases.
- Hybrid retrieval: semantic + keyword + metadata filtering.
- Re-ranking pipelines and citation verification.
- Handling contradictory data and hallucination reduction.
Document Ingestion & ETL for AI
- LlamaIndex for multi-format document processing.
- Parsing PDFs, slides, spreadsheets with Unstructured.io.
- Incremental ingestion and knowledge base freshness.
- Data quality scoring and automated cleanup pipelines.
Conversational Memory Systems
- Short-term vs long-term memory architectures.
- Sliding window, summarization, and compression strategies.
- User-scoped memory with privacy controls.
- Memory-augmented retrieval for personalized responses.
Live Class Schedule
Every Tuesday
Design Reviews
8:30 PM IST | 8 AM PST
11 AM EST | 5 PM CET
Every Thursday
AMA Sessions
8:30 PM IST | 8 AM PST
11 AM EST | 5 PM CET
Every Saturday
Live Classes
8:30 PM IST | 8 AM PST
11 AM EST | 5 PM CET
Not for Beginners. Not Sorry.
This track assumes you can code, you've shipped to production, and you're ready to level up.
Backend Engineers Adding AI
You know how to build traditional systems. Now you need to integrate AI as a first-class component, not an afterthought.
Data Engineers Moving to AI
You build data pipelines. This track teaches you to build AI-native data platforms — embeddings, vector stores, and retrieval systems.
AI Product Engineers
You're building AI-powered products and need to design architectures that scale, not just prototypes that demo well.
ENROLL NOW
$899/year
Annual payment. Lifetime access to content and updates. No subscriptions ever.
Enroll Now →Or view all pricing plans including all-tracks access
Common Questions
Do I need ML experience?
No. This is about system design for AI products, not training models. You should be comfortable with APIs, databases, and distributed systems.
Is this about using LangChain?
Frameworks are tools, not architecture. We teach you to design the system, then pick the right tools. You'll use LangChain, LlamaIndex, and raw APIs where each makes sense.
How is this different from the AI Engineering track?
AI Engineering teaches you to build with AI tools and ship AI products. AI Native System Design teaches you to architect the underlying systems. Think of it as the difference between building a feature and designing the platform.
Ready to level up?
12 weeks. Real projects. Senior engineers only. The next cohort starts soon.
Enroll Now — $899/yr →