21–24 of 24 posts
In my opinion, the way this will play out is with a significant amount of validation and human oversight to fully utilize these LLMs. As you mentioned, I recommend giving the AI room for error and improving the experience of manually checking everything. Maybe create a tool to facilitate manually checking the output? This is a valuable read: https://www.ufried.com/blog/ironies_of_ai_1/
I have been building Research automation with LangGraph for the past 2 months. We always put a human in the loop checkpoint after each critical step, might be annoying now but I think it will save us long-term.
I have been building Research automation with LangGraph for the past 2 months. We always put a human in the loop checkpoint after each critical step, might be annoying now but I think it will save us long-term.
I have been building Research automation with LangGraph for the past 2 months. We always put a human in the loop checkpoint after each critical step, might be annoying now but I think it will save us long-term.
how have you implemented that?
the implementation we are building is open source: https://github.com/giatenica/gia-agentic-short-v2