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sources/platform/actors/development/ai_assistant_coding/index.md

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import { RULES_AND_INSTRUCTIONS_PROMPT } from "@site/src/utils/ai-prompts";
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import PromptButton from "@site/src/components/PromptButton";
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The following documents describe how you can leverage llms.txt and llms-full.txt in AI IDEs, create rules and instructions files, and follow best practices for AI assistant coding.
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The following documents describe:
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- [How you can leverage llms.txt and llms-full.txt in AI IDEs](#use-llmstxt-and-llms-fulltxt)
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- [Create rules and instructions files](#add-rules)
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- [Best practices for AI assistant coding](#best-practices)
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### Documentation for LLMs: llms.txt and llms-full.txt
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Search engines weren't built for Large Language Modals (LLMs), but AI needs context. That's why we created `llms.txt` and `llms-full.txt` for our documentation. These files follow the [growing standard](https://llmstxt.org/) for LLMs consumption.
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Search engines weren't built for Large Language Modals (LLMs), but LLMs needs context. That's why we created `llms.txt` and `llms-full.txt` for our documentation. These files follow the [growing standard](https://llmstxt.org/) for LLMs consumption.
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Find them here:
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### Best practices
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- **Small tasks**: Don't ask AI for many tasks at once. Break complex problems into smaller pieces. Solve them step by step.
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- **Small tasks**: Don't ask LLMs for many tasks at once. Break complex problems into smaller pieces. Solve them step by step.
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- **Iterative approach**: Work iteratively with clear steps. Start with a basic implementation. Improve it based on feedback and testing.
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- **Iterative approach**: Work iteratively with clear steps. Start with a basic implementation and gradually add complexity.
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- **Versioning**: Version your changes often using git. This lets you track changes, roll back if needed, and maintain a clear history.
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- **Security**: Don't expose API keys, secrets, or sensitive information in your code or conversations with AI assistants.
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- **Security**: Don't expose API keys, secrets, or sensitive information in your code or conversations with LLM assistants.

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