#LLM

LLMs, SLMs, VLMs, MoEs: Modern AI Alphabet Soup Decoded in 10 Minutes (2026)

What Is an AI Agent? Explained With a Complete Restaurant Analogy and System Architecture (2026)

FastAPI Rate Limiting and Cost Controls for LLM-Backed Endpoints

Traffic-shaped rate limiting isn't enough when every request has a dollar cost attached. A layered approach: request limits, token-aware budgets, and hard circuit breakers.

FastAPI Streaming Responses for LLM Token-by-Token Output

A step-by-step build of a real token-streaming endpoint in FastAPI: StreamingResponse, server-sent events, backpressure, client disconnects, and the gotchas that don't show up in a demo.

FastAPI + Pydantic v2: Building Type-Safe LLM API Endpoints

A hands-on walkthrough of the Pydantic v2 patterns that actually hold up when your endpoint's request or response body is generated, in part, by a language model.

Why FastAPI Became the Default Backend for AI Products in 2026

Node.js won the last decade of API backends. For AI products, the calculus flipped. Here's the actual reasoning — not hype — behind why most AI teams reach for FastAPI first.

streamUI: Dynamic React Components via Vercel AI SDK 3.x

Text generation is only the first step. Learn how to stream interactive, fully styled React components directly from LLM completions using Vercel AI SDK streamUI.

Structured Output & Agentic Routing with Vercel AI SDK 3.x

LLM responses are unpredictable. Discover how to use Vercel AI SDK Core APIs to guarantee structured JSON schema outputs and build dynamic agent routing loops.

Accelerating LLMs in the Browser: WebGPU vs WebNN — A 2026 Deep Dive

WebGPU and WebNN have fundamentally changed what's possible for LLM inference directly in the browser. This deep dive benchmarks both APIs, dissects WGSL shader code for matrix multiplication, and shows you exactly when to pick each technology.

Browser-Native AI Models with WebGPU: Running LLMs Locally Without a Server

Stop paying for inference APIs. This deep dive covers the full stack of running quantized LLMs directly in the browser using WebGPU compute pipelines, Transformers.js v3, and ONNX Runtime Web — with real benchmark numbers and production architecture patterns.

Human-Agent Collaboration Patterns That Actually Work in 2026

Beyond the hype: battle-tested patterns for building systems where humans and AI agents genuinely collaborate — with real approval workflows, trust calibration UX, and LangGraph checkpointing code.

Compiling LLM Tokenizers to WebAssembly: Speeding up Browser-Native AI Pre-processing by 10x

Learn how to optimize browser-native LLM execution. Compile heavy HuggingFace tokenizers from Rust to WebAssembly to eliminate pre-processing bottlenecks in WebGPU pipelines.