Leash, Not Autopilot: Building Predictable AI Behavior with Copilot Instructions
The article discusses the importance of providing clear instructions to AI systems like GitHub Copilot to ensure predictable and reliable behavior, as AI is not a magical solution that works out-of-the-box.
Why it matters
This article highlights the need for developers to take an active role in managing AI assistants like Copilot, rather than treating them as magical solutions that work out-of-the-box.
Key Points
- 1AI systems like Copilot are not designed to work perfectly without supervision
- 2Copilot is a large language model (LLM) that requires an AI system on top to manage context and history
- 3Providing clear, customized instructions is crucial for Copilot to behave as desired in production codebases
Details
The article explains that AI systems like Copilot are not magical solutions that work perfectly without any setup or supervision. Copilot is a large language model (LLM) that generates responses based on the input it receives, but it does not have any inherent understanding of context or history. The AI system sitting on top of the LLM is responsible for managing this, and if it fails to do so, the LLM will not be able to provide useful responses. The author emphasizes the importance of providing clear, customized instructions to Copilot to ensure it behaves predictably, as there are millions of different user workflows and definitions of what a 'good' response looks like. The article also includes a sample set of instructions that can be used to orient the Copilot model towards the desired behavior.
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