Skip to main content

​
Design Considerations and Limitations

While the API is minimal—centered on Agent, Task, and Tool—there are important tradeoffs and design constraints to be aware of.

​
Prompt Chaining

This workflow breaks a task into smaller steps, where the output of one agent becomes the input to another. It’s useful when a single prompt can’t reliably handle the full complexity or when you want clarity in intermediate reasoning. Notebook: Prompt Chaining with Keyword Extraction + Summarization The agent first extracts keywords from a resume, then summarizes what those keywords suggest. How to evaluate: Check whether each step performs its function correctly and whether the final result meaningfully depends on the intermediate output (e.g., do summaries reflect the extracted keywords?)
  • Check if the intermediate step (e.g. keyword extraction) is meaningful and accurate
  • Ensure the final output reflects or builds on the intermediate output
  • Compare chained vs. single-step prompting to see if chaining improves quality or structure

​
Orchestrator + Worker Pattern

In this approach, a central agent coordinates multiple agents, each with a specialized role. It’s helpful when tasks can be broken down and assigned to domain-specific workers. Notebook: Recruiting Evaluator Orchestrator The orchestrator delegates resume review, culture fit assessment, and decision-making to different agents, then composes a final recommendation. How to evaluate: Assess consistency between subtasks and whether the final output reflects the combined evaluations (e.g., does the final recommendation align with the inputs from each worker agent?)
  • Ensure each worker agent completes its role accurately and in isolation
  • Check if the orchestrator integrates worker outputs into a consistent final result
  • Look for agreement or contradictions between components (e.g., technical fit vs. recommendation)