🦄 ai that works: decoding context engineering lessons from Manus
🦄 ai that works
A weekly conversation about how we can all get the most juice out of todays models with @hellovai & @dexhorthy
https://www.github.com/hellovai/ai-that-works
A few weeks ago, the Manus team published an excellent paper on context engineering. It covered KV Cache, Hot-swapping tools with custom samplers, and a ton of other cool techniques.
On this week's episode, we'll dive deep on the manus Article and put some of the advice into practice, exploring how a deep understanding of models and inference can help you to get the most out of today's LLMs.
Pre-reading
To prevent repeating the basics, we recommend you come in having already understanding some of the tooling we will be using:
Discord
Cursor (A vscode replacement)
Programming languages
Application Logic: Python or Typescript or Go
Prompting: BAML (recommend video)
Meet the Speaker 🧑💻
Meet Vaibhav Gupta, one of the creators of BAML and YC alum. He spent 10 years in AI performance optimization at places like Google, Microsoft, and D. E. Shaw. He loves diving deep and chatting about anything related to Gen AI and Computer Vision!
Meet Dex Horthy, founder at Human Layer - a YC company. He spent 10+ years building devops tools at Replicated, Sprout Social and JPL. DevOps junkie turned AI Engineer.