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How a GitHub lawyer uses Copilot CLI to verify AI outputs

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YouTube
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1:38
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Englisch (Vereinigte Staaten)
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2322
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2.75s
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Transkript von How a GitHub lawyer uses Copilot CLI to verify AI outputs

Von einem Sprachmodell aus dem Ton des Films transkribiert, nicht von der Marke geschrieben. Klicke auf eine Zeile, um an diese Stelle zu springen.

  1. 0:00We work in a very hallucination-sensitive context.
  2. 0:03In areas like legal, cost of error can be very high.
  3. 0:07And GitHub Copilot CLI was the first time
  4. 0:10I saw something that felt like a tipping point.
  5. 0:13The more I used it, the more I started pushing it.
  6. 0:16I would throw increasingly complex things at it
  7. 0:20or things that I thought, no way could a tool do this,
  8. 0:23and it did them.
  9. 0:24One day, I was reviewing analysis that CLI generated,
  10. 0:28and it kept referring to source docs.
  11. 0:31The time it took to be jumping between docs to verify it,
  12. 0:35it was a lot.
  13. 0:36I told it, let's build a skill that embeds inline screenshots
  14. 0:40of the relevant portions of the documents.
  15. 0:43And that led to Eyeball.
  16. 0:44It helped me verify the AI outputs with my eyeball.
  17. 0:49When it tells me, for example, here,
  18. 0:52there's something about the indemnity clause
  19. 0:53I should pay attention to and why,
  20. 0:55I don't need to believe it.
  21. 0:57I can see it. It puts the relevant screenshot there and highlights for me the text that is driving its conclusions.
  22. 1:03Trust is important because we act on what we're getting out of these tools.
  23. 1:07We need to know that what we act on has a solid basis and truth.
  24. 1:12Copilot CLI bred like wildfire over a month or two,
  25. 1:15and now we have every lawyer in GitHub working in the terminal, which was not on my bingo card.
  26. 1:21Don't hold back on what you ask the tool to do because you'll probably be surprised.
  27. 1:27I'm Dan, a lawyer at GitHub and now an open source developer.
27 Zeilen · 268 Wörter

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