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DSPy framework enhances Datasette Agent's SQL prompt generation

Simon Willison explored using the DSPy framework to enhance the system prompts for Datasette Agent, a tool that generates SQL queries to answer data-related questions. He tasked Claude Code with evaluating and improving these prompts, specifically focusing on how the agent lists table schemas and provides advice on using `describe_table`. The testing, conducted with GPT-4.1 mini and nano, revealed that including column names in the schema listing or adjusting the advice on `describe_table` could prevent errors and improve query generation. AI

IMPACT DSPy's application to Datasette Agent suggests a path for improving prompt engineering in specialized AI agents, potentially leading to more reliable data analysis tools.

RANK_REASON The item describes the use of a framework (DSPy) to improve a specific AI-powered tool (Datasette Agent) by refining its prompts, which falls under tooling.

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

DSPy framework enhances Datasette Agent's SQL prompt generation

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The item describes the use of a framework (DSPy) to improve a specific AI-powered tool (Datasette Agent) by refining its prompts, which falls under tooling.
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COVERAGE [1]

  1. Simon Willison TIER_1 English(EN) ·

    Using DSPy to evaluate and improve Datasette Agent's SQL system prompts

    <p><strong>Research:</strong> <a href="https://github.com/simonw/research/tree/main/dspy-datasette-agent-prompts#readme">Using DSPy to evaluate and improve Datasette Agent&#x27;s SQL system prompts</a></p> <p>One of this morning's AIE keynotes covered <a href="https://github.com/…