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Developer proposes 3-question framework for AI vs. deterministic software

A developer outlines a three-question framework for determining whether to use a deterministic software approach or a large language model (LLM) for a given component. The questions focus on whether the answer is a fact or judgment, the cost of a wrong answer, and if the correct answer can be tested. This approach aims to maintain deterministic boundaries for AI features, particularly in customer support scenarios, by assigning AI to interpret intent and software to enforce policy. The framework suggests that while LLMs can be used for tasks like similarity search in knowledge bases, the decision-making process itself should remain deterministic to prevent prompt injection vulnerabilities. AI

IMPACT Provides a structured approach for developers to decide when to integrate LLMs versus deterministic software, potentially improving AI system reliability.

RANK_REASON The item is an opinion piece by a developer discussing a framework for AI implementation.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Developer proposes 3-question framework for AI vs. deterministic software

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10 / 100
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Commentary
The item is an opinion piece by a developer discussing a framework for AI implementation.
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product, other
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Antonio Lopes Correia ·

    Drawing the Line: What Deserves an LLM and What Doesn't

    <p><em>The three questions I use to decide what stays deterministic</em></p> <blockquote> <p>Part 2 of an ongoing experiment: building an LLM-powered support agent with deterministic boundaries. The <a href="https://github.com/antoniolopescorreia/reliable-ai-support" rel="noopene…