Our Experience at the Hacktober Fest

说明与用途

在一次黑客松中，团队开发了一个工具，生成并测试多种假设来解释销售下降，而不是依赖单一的 AI 解释。

问题

AI tools often give a single confident answer that may be incorrect, making it hard for analysts to trust the explanation for business metric changes.

结果

In a demo, the obvious reason (a big customer stopping orders) explained only 8% of the sales drop, revealing a more complex underlying cause.

工作流

• Identify a business metric drop (e.g., sales).
• Generate multiple possible explanations using an AI model.
• Retrieve actual sales data for each hypothesis.
• Test each hypothesis against the data to calculate its explanatory power.
• Report the percentage of the drop explained by each hypothesis and highlight the most supported ones.

证据

Our team, Training with Vibes, built something called Argue With My Data. The idea came from a simple frustration: you ask an AI tool why your sales dropped, and it gives you one confident answer that sounds right but might be completely off.

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It comes up with several possible explanations, tests each one against the actual numbers, and tells you which ones hold up and which don't.

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In our demo, the "obvious" reason, a big customer who stopped ordering, turned out to explain only 8% of the drop.

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One version of our code passed every test on one laptop and crashed on another.

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An AI call froze in the middle of testing and we had to figure out why.

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