Story Theory Benchmark launched
34 tasks | 21 models | 5 narrative theories
Tests whether LLMs understand story structure — using frameworks screenwriters have used for decades.
Open source. Reproducible.
Full results below
https://t.co/N9I5TMMDAe
The conclusion:
The best AI writing tool doesn't write.
It remembers.
It remembers what the writer wants. What the character would say. How the world works.
It handles the predictable — so the writer handles the profound.
That's the next generation of agent-native writing.
But they're all solving the same problem:
Speed. How to make words come faster.
The question nobody's asking:
How do we help writers think less about mechanical parts — so they can think more about what matters?
🧵 What if enterprise AI's best-kept secrets could transform how we build story agents?
Two powerful concepts from enterprise AI might just be the breakthrough AI writing tools need.
7/ Three-Layer Story Agent Architecture
① Data Layer: Character profiles, world lore, plot history
② Orchestration Layer: Connect different writing agents, share narrative context
③ Action Layer: Character Engine — generate consistent actions/reactions based on settings
Built a Ralph Loop with open specifications!
1. You approve the open-end rubric first
2. All evaluator LLM models evaluate each iteration
3. When over a threshold, approve
Weekend experiment: https://t.co/aAvnG763gQ
Story Theory Benchmark is open source
→ Run it on your model
→ Add new tasks
→ Check the full leaderboard
If you're building AI writing tools, the methodology might be useful.
Follow for more on LLMs and creative writing!
#LLM#AIWriting#Benchmark
Story Theory Benchmark launched
34 tasks | 21 models | 5 narrative theories
Tests whether LLMs understand story structure — using frameworks screenwriters have used for decades.
Open source. Reproducible.
Full results below
https://t.co/N9I5TMMDAe