Blog — page 11

Tutorial: Build a Production RAG App in 2 Hours

A practical 2026 RAG tutorial — chunking, hybrid retrieval, reranking, citations, and eval. Production-grade Python code for OpenAI, Qdrant, Cohere.

Tutorial: Fine-Tune Llama 4 Scout for Your Domain

A 2026 hands-on tutorial for fine-tuning Llama 4 Scout — LoRA setup, dataset prep, training, eval, deployment. Concrete Python code with Unsloth.

16 min read

Frontier Agents, Trainium3, and Amazon Nova: AWS re:Invent 2025 Key…

What if the software developers, database administrators, and security analysts of tomorrow aren’t humans, but autonomous AI systems capable of executing...

Tutorial: Stream LLM Responses from a FastAPI Backend

A 2026 production-grade FastAPI streaming tutorial — SSE, async, post-stream usage tracking, client-disconnect handling, and observability.

Vector Databases in 2026: Pinecone, Qdrant, Weaviate, pgvector

A 2026 guide to picking a vector database — Pinecone, Qdrant, Weaviate, or pgvector. Pricing, performance, hybrid search, and which workload fits which engine.

The GPU Scarcity Story: H100, H200, and B200

The 2026 GPU supply picture — H100 softening, H200 plentiful, B200 ramping — and a practical decision matrix for what to rent or buy for AI workloads.

4 min read

Pin Your Models: A Survival Guide for Unstable AI Defaults in Production

Why "default" model aliases are dangerous in production, how to pin AI model versions safely, and what to do when a vendor deprecates yours.

Self-Hosting LLMs in 2026: When It Pays Off

The honest 2026 math on self-hosting LLMs — break-even volumes, hidden engineering costs, model picks, and when regulatory drivers override the cost question.

On-Device AI in 2026: Apple Intelligence, Phi, and the Local LLM…

Local LLMs got useful in 2026. What runs on a MacBook, what runs on a phone, when to use cloud frontier models instead — a 2026 field guide.

Prompt Caching Explained: Anthropic, OpenAI, and the Math

How prompt caching works at Anthropic and OpenAI in 2026 — cache breakpoints, write and read pricing, TTL, breakeven math, and how to design cache-friendly prompts.

Rate Limiting AI APIs: Strategies That Actually Work

A 2026 guide to AI API rate limiting — token bucket, sliding window, per-tenant fairness, 429 handling, and Redis-backed scale patterns.

Voice Agent Architecture in 2026: LiveKit, Pipecat, and the End of the…

How LiveKit Agents, Pipecat, and Vapi differ architecturally in 2026 — and why the "STT → LLM → TTS" pipeline mental model is breaking down.

Embedding Models in 2026: OpenAI vs Cohere vs Open Source

A 2026 embedding model comparison — text-embedding-3, voyage-3, Cohere embed-v3, BGE-M3, Google — with quality, dimensions, context, and cost tradeoffs.

LoRA and Distillation: A Practical Guide for 2026

A 2026 practical guide to LoRA, QLoRA, and distillation — when to use each, default hyperparameters, dataset quality, the toolchain, and shipping to production.

vLLM vs TGI vs SGLang: Inference Engines Compared

A 2026 comparison of vLLM, TGI, and SGLang inference engines — PagedAttention, RadixAttention, throughput, and which engine fits which production workload.

The Agentic AI Stack: From Tool Use to Autonomous Workflows

How the AI agent stack is layered in 2026 — model, framework, tools, memory, observability, evaluation — and the design decisions that matter at each layer.

Why Model Context Protocol (MCP) Won the Agent Integration Wars

How Model Context Protocol went from Anthropic standard to industry default in 16 months — and what it means for AI agent builders.

Fine-Tuning vs RAG: The 2026 Decision Framework

A 2026 framework for choosing between fine-tuning and RAG — what each does, when each wins, and the hybrid pattern that most production systems actually use.

Load Balancing AI Workloads: Routing Across Providers

A 2026 guide to load balancing AI workloads — gateway patterns, multi-provider failover, latency-aware routing, caching, cost guardrails, and observability.

19 min read