In this workshop, we'll explore the four fundamentals of flow engineering: managing state, curating context, improving conditional edges, and best architectural practices. Through these fundamentals, you'll learn to transform complex LLM interactions into well-structured, maintainable systems that deliver reliable results."
If you've built a advanced LLM app, you know how finicky it is to break down complex goals into sub-tasks and organize them into a workflow. For instance, what are the best practices when decomposing tasks? How to manage the state within a workflow? Are generic flows better than complicated ones?
Flow engineering is an emerging skill among AI engineers that covers these questions.
In this workshop, we'll explore the four fundamentals of flow engineering: managing state, curating context, improving conditional edges, and best architectural practices. Through these fundamentals, you'll learn to transform complex LLM interactions into well-structured, maintainable systems that deliver reliable results.
Minki Jung is an AI Engineer at the Government of Canada, where he builds AI applications for citizens. With a bachelor's degree in physics and philosophy, he transitioned to the tech space as a full-stack engineer in 2022 and now specializes in AI engineering. Based in Montreal, he organizes the local AI Tinkerer community.
Minki Jung is an AI Engineer at the Government of Canada, where he builds AI applications for citizens. With a bachelor's degree in physics and philosophy, he transitioned to the tech space as a full-stack engineer in 2022 and now specializes in AI engineering. Based in Montreal, he organizes the local AI Tinkerer community.
