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Architecting Intelligence Labs

Deep dives, architecture blueprints, and hands-on systems for building real-world AI.

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Featured Deep Dives

Comprehensive technical articles on AI systems, architecture, and production ML.

LLM Systems
Architecting LLM Inference
KV cache, continuous batching, vLLM internals, speculative decoding, quantization, and serving architecture.
25 min readRead more
ML Infrastructure
Architecting Reinforcement Learning for LLMs
RLHF, PPO, DPO, reward modeling, and alignment workflows.
20 min readRead more
System Design
ML System Design for Principal Engineers
Search, recommendations, forecasting, fraud systems, ML platforms, and production tradeoffs.
30 min readRead more
AI Compute
Demystifying AI Compute
GPUs, TPUs, accelerators, memory, networking, and the real economics of AI infrastructure.
22 min readRead more
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Architecture Blueprints

Visual reference architectures for building real-world AI systems.

View BlueprintLLM Systems
LLM Inference Blueprint
End-to-end architecture for high-throughput LLM serving with batching and caching.
View BlueprintAgentic AI
Agentic AI Stack Blueprint
Multi-agent orchestration, tool calling, and state management architecture.
View BlueprintLLM Systems
RAG Production Architecture
Retrieval-augmented generation with vector stores, chunking, and hybrid search.
View BlueprintML Infrastructure
ML Platform Blueprint
Feature stores, training pipelines, model registry, and inference infrastructure.
View BlueprintML Infrastructure
Distributed Training Blueprint
Data parallelism, model parallelism, and gradient synchronization at scale.
View BlueprintProduction ML
AI Evaluation Pipeline
Automated evaluation, regression testing, and quality gates for ML systems.

Watch the Visual Deep Dives

Whiteboard-style explanations and architecture walkthroughs for complex AI systems.

18:24
LLM Systems
How LLM Inference Actually Works
Deep dive into the mechanics of token generation, attention, and serving.
12:45
LLM Systems
KV Cache Explained Visually
Visual walkthrough of attention caching and memory optimization.
22:10
Agentic AI
Agentic AI Stack: What Breaks and Where
Failure modes and reliability patterns for multi-agent systems.
15:30
Labs
OptiFlow Architecture Walkthrough
Technical deep dive into the OptiFlow optimization system.

Labs in Progress

Experimental tools, demos, and practical systems from Architecting Intelligence Labs.

FeaturedActive
OptiFlow AI
Generative AI-powered distributed and parallel job optimizer for cloud, Spark, Ray, Kubernetes, ML training, and LLM inference workloads.
Explore OptiFlow AI
Coming Soon
LaunchGate AI
Model evaluation and release-readiness agent for ML and LLM systems.
Coming Soon
Coming Soon
RAG Evaluation Toolkit
Evaluation framework for retrieval quality, answer faithfulness, groundedness, and hallucination detection.
Coming Soon
Coming Soon
LLM Inference Playground
Interactive learning environment for prefill, decode, KV cache, batching, GPU memory, and inference optimization.
Coming Soon
Explore All Labs

Work With Me

Advisory, architecture reviews, workshops, and consulting for teams building production AI.

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LLM Infrastructure Advisory
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ML Platform Design
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Built by an AI systems practitioner

PJ

Architecting Intelligence Labs is created by Pawan K Jha, an ML and AI systems leader with experience building large-scale ML platforms, forecasting systems, search and ranking platforms, GenAI systems, and AI architecture across enterprise environments. The mission is to make complex AI systems understandable, practical, and production-ready.

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