Fifteen terms that come up in every kickoff call. Plain-English definitions, no consultant-speak. Bookmark it, share it with your ops team, send it to the engineer who keeps asking what AEO actually means.
Answer Engine Optimization (AEO)
AEO
AEO is the practice of structuring your content, schema markup, and entity data so that large language models like ChatGPT, Claude, Perplexity, and Gemini quote your brand directly inside their answers, not just below them as a link. Where SEO chases the blue link, AEO chases the citation. The mechanics overlap with classic SEO — clean HTML, accurate facts, JSON-LD schema, internal linking — but AEO adds three things: extractable answer blocks (40-60 word definitions LLMs can lift verbatim), strong entity definitions in LLMO training corpora like Wikipedia and high-authority directories, and citation-friendly formatting (numbered lists, comparison tables, named experts). For most service businesses, AEO is the next 18 months of organic growth. See our full AEO guide.
Generative Engine Optimization (GEO)
GEO
GEO is the sister discipline to AEO, focused on generative search experiences like Google AI Overviews, Bing Copilot, and SearchGPT. These systems compose answers in real time from a synthesized set of sources, then footnote them. GEO emphasizes structured data (product schema, HowTo, FAQ), factual density (specific numbers, dates, named methods), and citation-worthy formatting. The practical playbook is similar to AEO but tuned for search-style intent (commercial and transactional queries) rather than chatbot conversation flow.
Large Language Model Optimization (LLMO)
LLMO
LLMO is the umbrella discipline covering both AEO and GEO. It is the active project of becoming the brand a language model names when a user asks a buying-intent question in your category. Three layers: training-corpus presence (your brand exists in the open web data the model was trained on), retrieval-corpus presence (your site is indexed by the live retrieval layer the model uses for current info), and prompt-time presence (your content is structured so it survives summarization without losing your name). Mid-market service businesses currently have a wide-open lane here.
n8n
n8n
n8n (pronounced "n-eight-n", short for nodemation) is an open-source workflow automation platform. It is fair-code licensed, self-hostable on a 5 USD VPS or available as managed cloud. Native catalog covers 400+ integrations including OpenAI, Anthropic, Google, Slack, Notion, HubSpot, Stripe, and full HTTP/webhook support. The killer feature is the Code node, which lets you drop into JavaScript or Python whenever a native node falls short — no escape hatch problem like Zapier. SkynetLabs uses n8n as the default automation runtime for client builds because it scales from 50 USD/mo retainers to enterprise without a license model change. See our n8n vs Zapier comparison.
GoHighLevel (GHL)
GHL
GoHighLevel is an all-in-one agency CRM that bundles funnels, email, SMS, calendar booking, social media posting, and pipeline management into a single tenant. Agencies pay one fee and spin up unlimited client sub-accounts. For a solo founder or small agency, GHL replaces ActiveCampaign + Calendly + ClickFunnels + Buffer at roughly the cost of one of those tools standalone. SkynetLabs uses GHL for client lead capture, drip nurture, and cross-platform social scheduling. It pairs natively with n8n through webhooks and a published API.
Workflow Automation
Automation
Workflow automation is the programmatic chaining of business steps so that a trigger in one system fires a reaction across many. Example: a new Stripe payment auto-creates a Notion record, sends a welcome email through GHL, posts a slack notification, and books a kickoff call in Calendly. The discipline replaces copy-paste, manual handoffs, and meeting-to-meeting context loss with deterministic pipelines that run 24/7. Common runtimes include n8n, Zapier, and Make.com.
AI Agent
Agent
An AI agent is a large language model wrapped in tool-calling, memory, and a goal loop so it can take multi-step actions on a user's behalf instead of just answering a single prompt. A normal chatbot says "here is how to book a table." An agent calls the OpenTable API, picks a slot, sends the confirmation, adds it to your calendar, and texts your guest. Agents come in two flavors: managed (built inside ChatGPT, Claude Projects, or a vendor platform) and bespoke (built in code or in n8n). SkynetLabs ships both depending on client risk tolerance.
Custom GPT
Custom GPT
A Custom GPT is a configured ChatGPT persona with system instructions, uploaded knowledge files, and optional API actions. They live inside ChatGPT, share by URL, and require no code to launch a v1. Useful for internal tools (HR policy bot, onboarding tutor), client-facing assistants (price quoter, FAQ handler), and lead magnets (a free GPT in exchange for a website link). Limits worth knowing: knowledge files cap, no native database connection without API actions, and your prompts are not fully private from the user. SkynetLabs ships custom GPTs as part of the lead-magnet stack.
WhatsApp Business API
WABA
The WhatsApp Business API is Meta's programmatic channel for sending and receiving WhatsApp messages at scale. Required for any automated bot serving more than a handful of conversations — the consumer app and even the basic Business app cap out fast. WABA enforces template approval (every outbound first-touch message must be pre-approved by Meta), 24-hour conversation windows (after a user replies, you have 24h of free-form responses), and per-message pricing by country. SkynetLabs builds WABA bots through Twilio, ManyChat, or direct Meta integration plus n8n.
Vibe Coding
Vibe Coding
Vibe coding is Andrej Karpathy's term for shipping software by describing what you want to a language model and accepting the diff without reading every line. The model writes, you steer. Fast for prototypes, dangerous in production unless paired with disciplined testing and code review. SkynetLabs ships vibe-coded MVPs in 5 to 7 days but always layers a QA pass and a human read-through before any client deployment. Done well, it collapses a two-week build into a Tuesday afternoon.
Make.com
Make
Make (formerly Integromat) is a visual workflow builder competing with Zapier and n8n. Strengths: visual scenario editor, branching logic better than Zapier, op-based pricing that beats Zapier on cost. Weaknesses: cloud-only (no self-host), weaker developer escape hatches, smaller integration catalog than Zapier. Best fit for marketers who outgrew Zapier but do not want a self-hosted server.
Zapier
Zapier
Zapier is the original no-code automation tool. It has the biggest integration catalog (7000+), the simplest UX in the category, and the highest per-task cost at scale. For under 100 USD/mo of automation work, Zapier is fine. Past that, the per-task billing dominates and the lack of a code escape hatch starts to bite. SkynetLabs typically migrates clients off Zapier and onto n8n when the monthly bill clears 200 USD or when a single workflow needs custom logic Zapier cannot express cleanly. Full breakdown in our n8n vs Zapier guide.
Webhook
Webhook
A webhook is an HTTP POST sent from one system to another the moment an event happens, like a payment, a form submission, or a calendar booking. It is the push-based glue under almost every real-time automation. Compared to polling (where you repeatedly ask "any updates?"), webhooks deliver the update the instant it occurs. Every modern automation runtime — n8n, Zapier, Make — treats webhooks as first-class triggers and outputs.
Embedding
Embedding
An embedding is a vector of floats representing the semantic meaning of a chunk of text, image, or audio. Models like OpenAI's text-embedding-3 or Voyage AI turn "What is AEO?" and "How do I get cited by ChatGPT?" into vectors that are numerically close because they mean similar things. Embeddings power semantic search, retrieval-augmented generation, deduplication, classification, and recommendation. Stored at scale in a vector database.
Vector Database
Vector DB
A vector database is a database optimized for similarity search across embeddings. Instead of "find rows where category = X", you ask "find the 5 chunks of text most semantically similar to this question." Powers retrieval-augmented generation (the RAG in most enterprise AI), semantic search, recommendation engines, and long-term agent memory. Common options: Pinecone, Weaviate, Qdrant, Supabase pgvector, and Chroma. Most SkynetLabs builds use Supabase pgvector to keep auth + storage + vectors in one tenant.
Need a system built around these terms?
SkynetLabs ships AI automation systems for founders who refuse to let manual work limit their growth. See case studies, the AEO guide, or book a call.