In this article, I catalogue several LLM and user failure modes I have encountered over the years across tasks such as vibe coding, building websites, automating workflows, developing RAG systems, and creating AI agents.
My aim is to keep these limitations in view, recognise recurring failure patterns and reduce the chances of being caught off guard by an LLM’s output.
The end goal is to produce reliable automation workflows and other AI-generated outputs.
The knowledge of various failure modes can help you understand why agents behave the way they behave, why they sometimes seem to lie, ignore instructions or take actions they are not authorised to take and what you can do about it.
In my opinion, this is one of the best pieces of knowledge I have ever acquired in the field of AI automation.
If you can stomach the article, technical detail and dry subject matter long enough to read it from start to finish, you will be better equipped to use LLMs for automation work than 99% of AI users and developers.