Super Awesome AI Source
  • Home
  • About
Sign in Subscribe

vector search

A collection of 2 posts
How to Build a Tenant-Scoped AI Agent Output Caching Layer Using Semantic Similarity Deduplication to Cut Multi-Tenant LLM Inference Costs in 2026
AI

How to Build a Tenant-Scoped AI Agent Output Caching Layer Using Semantic Similarity Deduplication to Cut Multi-Tenant LLM Inference Costs in 2026

LLM inference bills have a way of arriving like a cold shower. You architect a beautiful multi-tenant AI product, onboard a few hundred customers, and suddenly your monthly token spend looks like a phone number. The culprit, more often than not, is not complex reasoning chains or massive context windows.
Mar 16, 2026 10 min read
vector search

Memory-Optimized Vector Search vs. Full Graph Retrieval: Which Architecture Should Backend Engineers Standardize for Multi-Hop Reasoning in Production AI Apps in 2026?

There is a quiet but fierce architectural debate happening in backend engineering teams right now. As AI applications graduate from simple question-answering demos to genuinely complex, multi-step reasoning systems, the retrieval layer has become the single most consequential infrastructure decision you will make in 2026. Two camps have formed: engineers
Mar 4, 2026 8 min read
Page 1 of 1
Super Awesome AI Source © 2026
  • Sign up
Powered by Ghost