Claude Code и Codex для контента: как настроить систему, чтобы тексты «зашли»
A speaker explains how to train an AI content creation system by manually correcting initial posts and providing feedback to improve output quality. The process involves iterative refinement where the AI learns the user's brand voice and style preferences over time.
Summary
The speaker describes a systematic approach to training AI for content creation, emphasizing that initial posts generated by the system will require significant manual editing and refinement. They explain their personal process of correcting early AI-generated posts, providing specific feedback about language preferences (such as reducing English words and using more human language), and teaching the system to match their writing style. The speaker notes that after approximately 5-10 posts with corrections, the AI system (referred to as 'Code' or 'cloud cloud via telegram') begins to understand the user's preferences and can create content that closely matches their desired style and voice. They emphasize that this method can solve content creation problems permanently, but requires having a clearly defined brand voice first. For those without an established voice, they suggest analyzing content from preferred authors or telegram channels, though they caution this won't truly represent the user's authentic voice. The speaker concludes by promoting downloadable materials and encouraging engagement with their content.
Key Insights
- The speaker claims that initial AI-generated posts will require manual finishing and correction by the user to match their preferred style
- The author argues that after correcting 5-10 posts with specific feedback, AI systems learn to replicate the user's writing patterns and preferences
- The speaker asserts that this training method can solve content creation problems permanently once properly implemented
- The author emphasizes that having a clearly formulated brand voice is a prerequisite for successfully training AI content systems
- The speaker suggests that users can analyze other authors' content from telegram channels as an alternative approach, but warns this won't represent their authentic voice
Topics
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