#AI Architecture

Mixture-of-Agents (MoA): Layered Multi-LLM Collaboration Architecture for Frontier Tasks

An advanced AI architecture guide to Mixture-of-Agents (MoA). We analyze multi-layer iterative synthesis, proposer-aggregator hierarchies, heterogeneous model ensembles, and outperforming GPT-5 on reasoning benchmarks.

Graph RAG with Neo4j: Entity Resolution & Knowledge Graph Embeddings for LLMs

An advanced AI architecture guide to Graph RAG. We analyze property graph data modeling in Neo4j, LLM entity extraction pipelines, Cypher query generation, and resolving multi-hop relational context that vector search misses.

AI Context Windows Explained: Working Memory, Attention Limits, and "Lost in the Middle" (2026)

Fine-Tuning vs Prompting vs RAG: Teaching vs Asking Explained Simply (2026)

Neural Networks Explained: Layers of Voting Neurons and Activation Functions (2026)

RAG Explained: Giving AI an Open-Book Exam (System Architecture & Pipeline) (2026)

System Design Interview Prep 2026: The New AI-Era Architectural Patterns & Questions

What 'Superhuman Coder by 2027' Would Actually Require, Technically

Technical roadmap for 2027 AI coding. What 10M token working memory, zero-shot AST refactoring, dynamic physical execution sandboxes, and verification loops require.

Building a Model Router: Picking the Cheapest Model That Still Works

A step-by-step walkthrough of building a request router that sends each query to the cheapest model likely to answer it correctly, with fallback and confidence scoring baked in.

When to Use a Reasoning Model vs a Fine-Tuned Small Model

Two completely different ways to get a hard task right: make the model think harder at inference time, or make a smaller model already know the answer shape. Neither is universally correct.

Reasoning Models vs Fast Models: Choosing the Right Latency/Accuracy Tradeoff

Reasoning models think longer and get more right. Fast models answer instantly and get most things right, most of the time. Here's how I decide which one belongs in a given code path.

Vector-First Stacks: Re-Architecting for the AI Era in 2026

Traditional relational databases are no longer the center of the universe. Explore the rise of Vector-First Stacks and why your next app will be built around embeddings in 2026.