What problem does it solve?
Prompt engineering is about designing and refining prompts to achieve reliable, high-quality outputs from large language models. It emphasizes a test-driven, measurement-based approach to avoid relying on unverified techniques and to enable iterative improvements grounded in evidence.
Core Features & Use Cases
- TDD-driven prompt design: Establish baselines, define success criteria, run structured tests, and iterate with minimal changes.
- Explicit instructions and formats: Create prompts that clearly define task, audience, constraints, and output structure.
- Examples and formatting guidance: Use few-shot examples and consistent formatting to improve determinism.
- Three practical use cases:
- Claude configurations (skills/agents)
- Ad-hoc prompting in chat interfaces
- Application development with LLM APIs
- Rigorous testing and evaluation: Emphasize repeatable tests, multiple runs for reliability, and guardrails.
Quick Start
Write a baseline prompt, define 5–10 test cases, and iterate one change at a time to measure impact.
