#LLM — Sejan

The Paradigm Shift to Test-Time Compute and Agentic Reasoning: The State of AI in Late 2026

#LLM

Oct 11, 2026

The Paradigm Shift to Test-Time Compute and Agentic Reasoning: The State of AI in Late 2026

A comprehensive analysis of the latest breakthroughs in artificial intelligence: how the industry transitioned from pre-training parameter scaling to test-time compute scaling (System 2 deliberation), reinforcement learning for verifiable reasoning (DeepSeek-R1, OpenAI o3), and production-grade agentic orchestration architectures.

PagedAttention and KV Cache Management: The Architecture Behind High-Throughput LLM Serving

#LLM

Sep 23, 2026

PagedAttention and KV Cache Management: The Architecture Behind High-Throughput LLM Serving

A deep technical dive into LLM inference memory architectures: how PagedAttention eliminates the 60-80% GPU memory fragmentation bottleneck using OS virtual memory principles, copy-on-write prefix caching, continuous batching (Orca/vLLM), and radix block management internals.

GPU Memory Architecture & FlashAttention-3: Solving the Memory Bandwidth Bottleneck in LLM Inference

#LLM

Sep 21, 2026

GPU Memory Architecture & FlashAttention-3: Solving the Memory Bandwidth Bottleneck in LLM Inference

A comprehensive hardware and algorithmic deep dive into GPU memory systems and LLM acceleration: how FlashAttention-3 eliminates the HBM memory bandwidth wall through SRAM tiling, online softmax normalization, warp specialization on Hopper/Blackwell, and PagedAttention KV-cache management.

The Model Context Protocol (MCP) Architecture Guide: Building Production-Grade Tool Servers and Enterprise AI Gateways

#LLM

Sep 15, 2026

The Model Context Protocol (MCP) Architecture Guide: Building Production-Grade Tool Servers and Enterprise AI Gateways

A comprehensive architectural deep dive into the Model Context Protocol (MCP): the JSON-RPC standard connecting LLMs to external systems, building custom TypeScript MCP servers, handling stateful transport (stdio vs. SSE), and architecting secure enterprise MCP gateways.

Speculative Decoding in Production: Accelerating LLM Inference 3x with Medusa Heads, Draft Models, and Verification Kernels

#LLM

Sep 13, 2026

Speculative Decoding in Production: Accelerating LLM Inference 3x with Medusa Heads, Draft Models, and Verification Kernels

A deep architectural guide to Speculative Decoding in LLM inference: why memory bandwidth creates an autoregressive bottleneck, draft-and-verify execution pipelines, multi-head Medusa architectures, tree-based attention verification, and deploying in vLLM.

Architecting GraphRAG: Combining Knowledge Graphs with Vector Embeddings for Multi-Hop AI Retrieval

#LLM

Sep 12, 2026

Architecting GraphRAG: Combining Knowledge Graphs with Vector Embeddings for Multi-Hop AI Retrieval

A deep architectural guide to GraphRAG: why flat vector cosine similarity fails at multi-hop reasoning, extracting entity-relationship knowledge graphs, hierarchical Leiden community detection, and building a hybrid graph-vector retrieval pipeline.

Demystifying AI Agent Harnesses: Architecture, Tool Execution, Context Compaction, and Building Your Own in Node.js

#LLM

Sep 10, 2026

Demystifying AI Agent Harnesses: Architecture, Tool Execution, Context Compaction, and Building Your Own in Node.js

A comprehensive deep dive into AI Agent Harnesses: why raw LLMs fail without runtime scaffolding, how the ReAct step machine operates, context budget management, and how to build a production-grade agent harness from scratch in Node.js and TypeScript.

Inside the Muse AI Ecosystem: Architecture, Open-Weights Glimmer 30B, and Agentic Reasoning

#LLM

Sep 05, 2026

Inside the Muse AI Ecosystem: Architecture, Open-Weights Glimmer 30B, and Agentic Reasoning

A technical breakdown of the Muse AI family: Muse Spark's 1M-token multimodal reasoning, the open-weights Muse Glimmer 30B running locally, and agentic image synthesis.