- Plateforme
- YouTube
- Durée
- 1:38
- Langue parlée
- anglais américain
- Vues
- 2,3 k
- Coupe médiane
- 2.75s
- Visage à l'écran
- 44%
- Images sombres
- 58%
Transcription de How a GitHub lawyer uses Copilot CLI to verify AI outputs
Transcrit par un modèle vocal à partir du son du film, et non rédigé par la marque. Cliquez sur une ligne pour y amener la lecture.
- 0:00We work in a very hallucination-sensitive context.
- 0:03In areas like legal, cost of error can be very high.
- 0:07And GitHub Copilot CLI was the first time
- 0:10I saw something that felt like a tipping point.
- 0:13The more I used it, the more I started pushing it.
- 0:16I would throw increasingly complex things at it
- 0:20or things that I thought, no way could a tool do this,
- 0:23and it did them.
- 0:24One day, I was reviewing analysis that CLI generated,
- 0:28and it kept referring to source docs.
- 0:31The time it took to be jumping between docs to verify it,
- 0:35it was a lot.
- 0:36I told it, let's build a skill that embeds inline screenshots
- 0:40of the relevant portions of the documents.
- 0:43And that led to Eyeball.
- 0:44It helped me verify the AI outputs with my eyeball.
- 0:49When it tells me, for example, here,
- 0:52there's something about the indemnity clause
- 0:53I should pay attention to and why,
- 0:55I don't need to believe it.
- 0:57I can see it. It puts the relevant screenshot there and highlights for me the text that is driving its conclusions.
- 1:03Trust is important because we act on what we're getting out of these tools.
- 1:07We need to know that what we act on has a solid basis and truth.
- 1:12Copilot CLI bred like wildfire over a month or two,
- 1:15and now we have every lawyer in GitHub working in the terminal, which was not on my bingo card.
- 1:21Don't hold back on what you ask the tool to do because you'll probably be surprised.
- 1:27I'm Dan, a lawyer at GitHub and now an open source developer.
27 lignes · 268 mots
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