Dictionary
Definition layer. The vocabulary of the system.
AI Agent
An autonomous AI system that plans and executes multi-step tasks.
RAG (Retrieval-Augmented Generation)
Inject external knowledge into an LLM at query time.
Prompt Chaining
Pipelining LLM calls where each step's output feeds the next.
LLM Orchestration
Coordinating multiple model calls, tools, and data sources into one reliable system.
Vector Database
A database optimized for similarity search over embeddings.
AI Content Pipeline
An end-to-end system that takes a topic and outputs publish-ready content.
No-Code Automation
Building business workflows visually without writing code.
AI SDR (Sales Development Rep)
An autonomous system that researches, qualifies, and contacts leads.
Workflow Trigger
The event that starts an automated workflow.
Tool Calling
The model-to-system interface that lets an LLM trigger external actions.
Structured Output
Forcing AI responses into predictable schemas that software can use.
Human-in-the-Loop
A control pattern where humans review high-risk AI decisions before execution.
Agent Memory
Persistent context that lets agents retain preferences, decisions, and prior work.
Automation Observability
Monitoring inputs, model calls, outputs, cost, latency, and failures across AI workflows.
Semantic Search
Finding information by meaning rather than exact keyword match.
Vibe Coding
Building software by describing intent in natural language and letting AI generate the code.
Affiliate Marketing
Earning commissions by recommending other companies' products through trackable links.
Programmatic SEO
Generating hundreds or thousands of targeted pages from a structured dataset.
MCP (Model Context Protocol)
Open protocol that lets LLMs connect to tools, data sources and apps through a standard interface.
Agentic RAG
RAG where an agent decides what to retrieve, when, and from which source — instead of a single static query.
Embedding
A numerical vector representation of text, image or audio that captures meaning for similarity search.
Fine-Tuning
Continuing to train a base model on your own examples to specialize its behavior.
AEO (Answer Engine Optimization)
Optimizing content to be cited by AI answer engines like ChatGPT, Perplexity and Google AI Overviews.
Edge Computing
Running code and AI inference close to the user instead of in a central data center.
Guardrails
Runtime checks that constrain LLM inputs and outputs to keep behavior safe and on-spec.
AI Evals
Reproducible test suites that measure LLM output quality across model, prompt and code changes.
Context Window
The maximum amount of text (in tokens) an LLM can consider in a single call.
Multimodal AI
Models that natively process more than one input type — text, images, audio, or video.
AI Orchestration
Coordinating multiple AI models, tools and steps into a single reliable workflow.
Knowledge Graph
A network of entities and the relationships between them, queryable like a map.