diff --git a/2025/Whodunit? Writing Murder Mysteries with LLMs/2025-whodunit-lightning.pdf b/2025/Whodunit? Writing Murder Mysteries with LLMs/2025-whodunit-lightning.pdf new file mode 100644 index 0000000..9465668 Binary files /dev/null and b/2025/Whodunit? Writing Murder Mysteries with LLMs/2025-whodunit-lightning.pdf differ diff --git a/2025/Whodunit? Writing Murder Mysteries with LLMs/README.md b/2025/Whodunit? Writing Murder Mysteries with LLMs/README.md new file mode 100644 index 0000000..8674d69 --- /dev/null +++ b/2025/Whodunit? Writing Murder Mysteries with LLMs/README.md @@ -0,0 +1,15 @@ +# Whodunit? Writing Murder Mysteries with LLMs - James Heller, Apartment 304 + +[Expanded Post](https://blog.apartment304.com/whodunit-llm-murder-mysteries) + +[Slides](2025-whodunit-lightning.pdf) + +[Play **Whodunit?**: Solve AI authored mysteries](https://whodunit.rip) + +Can a large language model craft a brand-new murder mystery on demand? Explore a mystery-writing AI and the tips and tricks that help it generate coherent, logic-driven mysteries for players to solve. The system writes backwards from the solution, breaks the story into structured steps, and uses Temporal to manage retries when APIs fail. The result is a low-tech game powered by cutting-edge tools. + +## Biography + +James is a software engineer at Apartment 304, which he co-founded in 2016. He works primarily on cloud architecture, application, and data engineering projects, and enjoys using Go whenever he can. He automates Halloween decorations and recently enlisted AI’s help in writing murder mysteries for game night. + +The End? diff --git a/README.md b/README.md index aa16c42..f712890 100644 --- a/README.md +++ b/README.md @@ -176,7 +176,7 @@ Panelists: David Soria Parra, Gari Singh, Ian Cottrell, Jaana Dogan ### Lightning Talks -#### Whodunit? Writing Murder Mysteries with LLMs - James Heller, Apartment 304 +#### [Whodunit? Writing Murder Mysteries with LLMs - James Heller, Apartment 304](2025%2FWhodunit%3F%20Writing%20Murder%20Mysteries%20with%20LLMs) Can a large language model craft a brand-new murder mystery on demand? Explore a mystery-writing AI and the tips and tricks that help it generate coherent, logic-driven mysteries for players to solve. The system writes backwards from the solution, breaks the story into structured steps, and uses Temporal to manage retries when APIs fail. The result is a low-tech game powered by cutting-edge tools.