The Generation Function
Generator agents create things that did not exist. Given a description, they produce outputs matching specifications. The input is intent, the output is artifact.
This differs from retrieval, which finds existing items, and analysis, which evaluates what exists. Generation synthesizes something new. The agent interprets requirements and materializes results.
Generator Agent Output Types
Text artifacts: Documents, reports, emails, scripts, and other written deliverables. From outlines to finished drafts.
Visual outputs: Images, diagrams, charts, presentations. Visual communication created from descriptions.
Code generation: Functions, modules, configurations, and complete applications. Software created from requirements rather than written line by line.
Data structures: Schemas, templates, forms, and organized information frameworks. The scaffolding for capturing data.
How Generator Agents Work
Interpretation: The agent parses your request, identifying what you want and how it should appear. Clarity in specification produces better results.
Planning: For complex outputs, the agent determines structure before creating content. Section order, component relationships, and overall organization get decided.
Production: The agent creates the artifact, following its plan and your specifications. This phase often involves multiple internal iterations.
Evaluating Generator Agents
Assess output quality on representative tasks. Provide actual specifications from recent projects and compare generated results to what you ultimately needed.
Check iteration efficiency. How many rounds of feedback does reaching acceptable quality require? Fewer is better.