Prompt engineering dominates now, but knowledge graphs will become essential at scale.
I am not seeing significant use of knowledge graphs at startups yet. There is heavy reliance on out of the box language models and significant investment in prompt engineering, both at startups and larger companies. The zeitgeist is to mine these wonderful resources rather than going upstream to drive the language models themselves. Knowledge graphs are not simple and are difficult to build, while prompt engineering and rule-based approaches are easier. Results from research literature take time to get absorbed by practitioners. Once startups scale or work on applications where accuracy is crucial, they will have to adopt knowledge graphs.
— The synergy between LLMs and knowledge graphs · The Edge