Shared knowledge from NEXT4I and the web community.
What Is a Token in LLMs? A Developer's Guide to Cost Optimization and Architecture. Understanding how LLM tokens work is the difference between an AI feature that costs $50/month and one that runs up a $5,000 AWS/OpenAI bill.
Why treating an LLM as a probability engine, not a brain, changes how you architect around it. The reasoning behind NEXT4I's AI layer.
I was building a RAG (Retrieval-Augmented Generation) pipeline for NEXT4I the kind of system that reads your documents first, then answers questions from them. Standard stuff: document ingestion → chunking → embedding → vector search → LLM answer generation.
Connecting Obsidian, Git, and AI Agents with nothing but plain Markdown. The Seamless Integration by Design philosophy from NEXT4I.
ลงชื่อเพื่อรับแจ้งเตือน และร่วมเป็นผู้ใช้งานกลุ่มแรกพร้อมรับสิทธิพิเศษ
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