From Ad Hoc Prompting to Repeatable AI Workflows with Claude Code Skills

While large language models can simulate customer conversations for research, ad hoc prompting leads to inconsistent and unreliable results. A Claude Code skill offers a powerful middle ground, transforming a fragile prompting process into a reusable and structured workflow with a single command. This approach works by treating research personas as structured data objects to prevent character drift and deliberately designing panel diversity before generating responses. Unlike a dedicated Python library, a skill allows for flexible natural language inputs and operates within an existing subscription, making experimentation easier and more accessible.