The autonomous marketing glossary

- AI agent: A piece of software that uses a language model to take a series of actions toward a defined goal, often calling tools or other agents along the way. Why it matters: agents are the building block of an autonomous workflow. Multiple agents chained together is what turns one-task AI into a system that runs without you.

- A marketing approach in which AI agents work together to plan, execute, and measure campaigns rather than being used as one-off helpers for individual tasks. Why it matters: this is the framing that separates a 13-hours-saved week from a marginal-improvement week. The goal is a system, not a tool.

- A version of ChatGPT that you train with your own files, instructions, and writing samples so its outputs match your voice and use case. Why it matters: a CustomGPT trained on your winning emails or your brand voice is what makes AI-drafted output sound like you. Without it, you're spending more time editing than writing.

- The framework that names three capabilities every autonomous marketer needs: Imagine (generation and research), Activate (shipping campaigns), and Validate (measuring outcomes). Why it matters: in the AI Lab study of 1,000 marketers, 63% only use AI in Imagine; the 23% who use it effectively span all three pillars, which is where the real time and cost savings show up.

- A workflow design pattern where AI handles the first draft or the heavy lifting and a human reviews, edits, and approves before anything ships. Why it matters: every workflow shown in the webinar (Amanda's outbound, Maddy's social posts, Jazz's pitches) keeps the human at the approval step, which is what protects voice and accuracy.

- A tool that runs scripts ("phantoms") to extract data from web sources like LinkedIn Sales Navigator without copy-pasting. Why it matters: it's the data extraction step in Amanda's prospecting workflow. Without it, the CustomGPT has nothing to draft against.

- Feeding a CustomGPT examples of your real work (past emails, brand guidelines, writing samples) so its outputs reflect your style rather than the model's defaults. Why it matters: Amanda specifically trained hers on 15 emails that had earned real responses, not generic templates. The proof in her output came from the proof in her training data.

- An automation platform that connects tools and triggers actions between them, including a newer agent layer that lets a Zap reason over input before deciding what to do next. Why it matters: Maddy Osman's news-scanning workflow uses a Zapier AI agent to decide if an article is relevant before drafting the social post, which is the difference between a dumb filter and an autonomous one.

- Multi-step workflows in ActiveCampaign that fire based on a contact's behavior or attributes, including sends, tags, score updates, and conditional branches all in one builder. Where it lives: under Automations in the main navigation.

- Broadcast emails sent to a list or segment at a specific time, separate from automations, which run continuously based on triggers. Where it lives: under Campaigns in the main navigation.

- A points system that rates contacts based on the actions they take (opens, clicks, page visits, form submissions) so you can prioritize who's most engaged. Where it lives: under Contacts → Scoring.

- Saved filters that group contacts by shared attributes or behaviors so you can target them in campaigns and automations. Where it lives: under Contacts → Segments.