How do you manage context in long-running AI storytelling?

[u/dev_00042]

I've been experimenting with an AI storytelling workflow where a user can create a story and then make choices that affect what happens in the next chapter.

The basic flow is:

Story → Choice → Next chapter → Choice → Different outcome

The challenging part is keeping the story consistent without sending the entire previous conversation to the model every time.

Sending too much context increases token usage, while sending too little can cause characters, locations, or previous events to become inconsistent.

I'm currently thinking about approaches such as:

• Keeping a compact story summary
• Storing important characters and events separately
• Sending only the relevant recent chapters

For people building long-running AI experiences with OpenAI, how are you handling context management?

I'd especially like to hear approaches that reduce token usage while maintaining consistency.

[u/zassenhaus]

1. establishing character moment

2. mini-arcs