Engineering Implementations

Deep technical implementations of AI systems, research papers, model architectures, inference engines, and production AI infrastructure.

39+ Implementations 9 Engineering Domains Research → Code → Systems

Engineering Across Systems

This is where research becomes engineering. I work through papers in depth — not summaries, but the architecture decisions, the data flow, the trade-offs, and the reasons a system is built the way it is. Each entry pairs the original idea with my understanding of it: what actually matters, what is often missed, and how it holds up when you have to build it.

The goal is not coverage but depth — reconstructing each system from first principles across the full stack, from attention mechanics and model architectures to inference engines, agents, and production reliability.

Explore Engineering Domains

Nine domains spanning the full stack — from attention mechanics and model architectures to inference systems, agents, and production reliability.

Transformers & Attention

Self-attention mechanisms, KV caching, context handling, and the transformer optimizations that power every modern LLM.

Attention · KV Cache · Context · Architectures

1 Implementation

AI Agents

Agent fundamentals, multi-agent systems, agent memory, harnesses, and the MCP tooling layer behind autonomous LLM agents.

Agents · Multi-Agent · MCP · Harness

5 Implementations

LLM Inference & Serving

High-performance LLM serving, scheduling, KV cache management, quantization, attention backends, and GPU optimization.

KV Cache · Scheduling · Quantization · CUDA

8 Implementations

LLM Training & Alignment

Pretraining, fine-tuning, reinforcement learning for LLMs, preference optimization, and reasoning-focused training.

Pretraining · Fine-Tuning · RLHF · DPO

8 Implementations

Reasoning & Prompting

Chain-of-thought, prompting techniques, reasoning architectures, and test-time compute for stronger LLM reasoning.

Chain-of-Thought · Prompting · Test-Time Compute

2 Implementations

Memory & Context Systems

Agent memory, context compression, long-context architectures, and memory-efficient inference.

Agent Memory · Context Compression · Long Context

1 Implementation

RAG & Knowledge Systems

Retrieval, indexing, knowledge management, and retrieval optimization for grounded, up-to-date LLM systems.

Retrieval · Indexing · Knowledge

1 Implementation

Guardrails, Security & Observability

Guardrails, AI/LLM security, evaluation, monitoring, and observability for safe, reliable production AI.

Guardrails · Security · Evaluation · Monitoring

2 Implementations

Models & Architectures

LLM architectures, mixture-of-experts, small language models, and emerging alternatives to the standard transformer.

LLM Architectures · MoE · SLMs

11 Implementations