Most outbound workflows hit a point where something has to read messy input, decide what it means, and write usable output. Claude handles that step for us. It is Anthropic's family of large language models, used across GTM teams for research, classification, and drafting. You reach it through a chat app, an API, or as an AI step inside tools like Clay and n8n. Give it a prompt plus context and it returns reasoning, a clean label, a summary, or a draft that routes onward into the rest of the workflow without rework. Nothing is set in stone, but we typically make Claude the intelligence layer between data and action. It scores fit, infers a persona, summarizes a company, or writes a first-touch line, turning raw enrichment into something a rep or a sequence can act on right away. At Nebor we run Claude as an AI step inside our Clay tables, often paired with Claygent. It reads enriched account data, classifies fit and segment, and drafts personalized angles so outbound reflects the actual account in front of us. We treat Claude and ChatGPT as interchangeable for this work and pick per build. With a tight prompt and clean inputs the output stays consistent enough to ship into a live campaign.