AI Knowledge Hub

Decision-grade AI terms. Zero fluff.

This is not a blog. It’s a governed reference library: plain-English first, technical second, and practical “use/ignore/risk” so you can move fast without guessing.

Start with RAG (Beginner) → Learn Agents → Why we don’t guess →
Format: use / ignore / risk Order: simple → technical → tools Goal: fewer wrong turns

How to use this hub

Step 1

Start with the Decision Box

Use it to decide if the term matters for your current build. If it’s “ignore,” move on.

Step 2

Read Simple → Technical

Get the concept in plain English first, then learn the implementation details only if needed.

Step 3

Follow the Term Flow

Prereqs → next concepts → common confusions. This prevents “learning drift.”

Fast move: Pick a cluster below, read 3 terms, then build something small. Knowledge that never ships is just mental furniture.

Quick router

If you’re not sure what you need, start with the problem you’re solving.

Find what you need (fast)

Search tip

Use your browser search on this page

CtrlF Type a term like “RAG”, “embeddings”, or “agent” to jump to the right section.

When you build a lot, you don’t browse — you target.

Anchor docs

Governance before “helpful”

If an AI always answers, it’s not smart — it’s confident. These rules force the system to pause or refuse when evidence is missing.

AI Bill of Rights AI Constitution Start: Personal Blueprint

Learning Center (execution guides)

Term pages explain what something is. Learning Center guides show how to implement it without stepping on rakes.

Guide

Build a basic RAG pipeline

A start-to-finish walkthrough: chunk → embed → store → retrieve → answer.

Open guide →
Guide

Choose a vector database

Decision criteria: scale, cost, latency, filters, hybrid search, ops.

Open guide →
Guide

Agent safety checklist

How to keep tool-using agents from becoming expensive chaos.

Open guide →
Note: The “/learn/…” links above are placeholders. Swap them to your real Learning Center URLs (or delete this section until those posts exist).

Recommended build order (don’t drift)

RAG stack
  • Embeddings
  • Chunking
  • Vector Databases
  • Semantic Search
  • Top-K Retrieval
  • Re-ranking
Agents stack
  • AI Agent
  • Agentic Workflow
  • Tools / Functions
  • Memory (what it is / risks)
  • Evaluation
  • Guardrails

AKH is “copy-first” by design: simple explanation → technical breakdown → top players → next concepts.

Start now

Pick one cluster, read 3 terms, build a small prototype. That’s how knowledge turns into leverage.

Start with RAG → Learn Agents → Guardrails →

Page job: route to the right term fast. Everything else stays out of the way.

Independent System Reviews: Independently evaluated by multiple AI systems → Open the index • Unedited archive
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