Stop writing prompts to classify text: make evaluation declarative
📰 Dev.to AI
Learn to make text evaluation declarative instead of writing prompts to classify text, improving testability and maintainability
Action Steps
- Identify text classification tasks in your workflow
- Replace prompt-based classification with declarative evaluation
- Define clear rules and conditions for text classification
- Implement a testing framework to validate declarative evaluation
- Refactor existing prompt-based code to use declarative evaluation
Who Needs to Know This
Developers and data scientists working with LLMs can benefit from this approach to improve the reliability of their text classification systems
Key Insight
💡 Declarative evaluation improves testability and maintainability of text classification systems
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🚫 Stop writing prompts to classify text! Make evaluation declarative for better testability and maintainability 💡
Key Takeaways
Learn to make text evaluation declarative instead of writing prompts to classify text, improving testability and maintainability
Full Article
I've built the same thing more than once: a step that reads an inbound message — a lead form, a support ticket, a DM — and decides what to do with it. Qualify it, escalate it, route it, drop it. Every time, the implementation had the same shape: hand-write a prompt that asks an LLM to return JSON, parse the JSON, branch on it. And every time it rotted the same way: The prompt was untestable. "Looks right" was the only QA. It drifted. A model upgrad
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