Tag

#llm-engineering

Posts tagged with llm-engineering

4 posts

Overview of AI agent orchestration with a thin router dispatching work to specialized agents rather than running every decision through one central loop.

Engineering • Oct 19, 2026 •13 min read

AI Agent Orchestration, Thin Router or Fat God Agent

AI agent orchestration is a knowledge-placement decision. This teardown of Meta's minimal router shows what a fat loop costs and when to stay thick.

#ai-agents #orchestration +4

A RAG chunking strategy decides how source documents are split into the chunks that feed embedding and vector retrieval.

Guides • Oct 17, 2026 •11 min read

RAG Chunking Strategy, Decided by a 50-Pair Eval

Stop copying 512-token defaults. Build a small retrieval eval on your own corpus and let decision gates and cost math pick your RAG chunking strategy.

#rag #chunking +3

Data center servers running large language model workloads, where LLM prompt caching cuts the cost of repeated input tokens.

Guides • Sep 16, 2026 •10 min read

LLM Prompt Caching Can Cut Input Costs Up to 90%

LLM prompt caching can cut agent loop input costs up to 90%. Compare OpenAI, Anthropic, Gemini, and Bedrock on TTLs, breakpoints, and real savings math.

#prompt-caching #llm-costs +3

Controlling reasoning effort in LLM APIs means setting explicit parameters that cap how many tokens a model spends on internal chain-of-thought before producing visible output.

Guides • Jul 28, 2026 •13 min read

Control Reasoning Effort LLM APIs in Production

Control reasoning effort LLM APIs across OpenAI, DeepSeek, and Anthropic. Practical routing rules to cut cost and latency without losing accuracy.

#llm-engineering #api-optimization +3