Natural Language vs Deterministic Interfaces for LLMsKey PointsNatural language interfaces for LLMs are powerful but can be problematic for software engineering and automationBenefits of natural language:Flexible input handlingAccessible to non-technical usersWorks well for casual text manipulation tasksChallenges with natural language:Lacks deterministic behavior needed for automationDifficult to express complex logicResults can vary with slight prompt changesNot ideal for command-line tools or batch processingProposed Solution: YAML-Based InterfaceYAML offers advantages as an LLM interface:Structured key-value formatHuman-readable like Python dictionariesCan be linted and validatedEnables unit testing and fuzz testingUsed widely in build systems (e.g., Amazon CodeBuild)Implementation SuggestionsCreate directories of YAML-formatted promptsBuild prompt templates with defined sectionsRun validation and tests for deterministic behaviorConsider using with local LLMs (Ollama, Rust Candle, etc.)Apply software engineering best practicesConclusionMoving from natural language to YAML-structured prompts could improve determinism and reliability when using LLMs for automation and software engineering tasks.
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