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Jev isn't a smaller LLM — it's a decision model with the generation loop removed. It returns typed values with probabilities instead of text, and its speed comes from architecture, not parameter count
Over the past two years RAG evolved from a 'linear pipeline' to 'loop-based reasoning'. It maps cleanly to five stages: Naive, Advanced, Modular, Graph, Agentic. The real inflection point is control moving from pipeline to agent — a System 1 → System 2 shift. Looking back at engineer-news's own RAG stack, it's stuck at the Naive edge — so this post also lays out what to fix next.
The previous post zoomed out for a five-stage panorama of RAG. This one zooms in on the five infra lessons any real RAG has to face: document ingestion, contextualized chunking, three-lane hybrid search, tensor reranker, and GraphRAG's semantic gap. Each lesson is checked against engineer-news's current stack, ending with a priority list for a personal site.
PageIndex swaps the vector DB for a hierarchical tree index plus an LLM Agent that reasons over it, and it shines on long structured documents (98.7% on FinanceBench). This site's Hybrid RAG instead runs vector search with a keyword fallback on the Cloudflare edge — a completely different set of tradeoffs.
A pnpm monorepo integrating four tool SPAs: a to-do list, a habit tracker, an ebook reader, and a resignation stamp collector. apps/root is the sole build entry point; the four modules are library-only workspace packages bundled together by root's Vite, sharing @a920604a/auth and @a920604a/ui, deployed across Firebase + Cloudflare dual cloud.
A pure-TypeScript tag scoring engine computes real-time risk across 140 foods for four conditions — gout, high cholesterol, diabetes, and hypertension. The entire backend runs on Cloudflare's free tier, for a monthly cost of $0.
Astro handles static rendering and content management, Cloudflare Pages/Workers handle deployment and dynamic APIs, D1 provides lightweight data storage, Vectorize + Workers AI power RAG semantic search, and R2 stores OG images and TTS audio. The entire pipeline — from YouTube crawl to user search — runs inside the Cloudflare ecosystem.