The approach had various problems at the time:
* what to do with a chain of reasoning if a previously asserted fact was retracted (i.e. when being questioned by the system, you realise that a previous answer was wrong)
* very brittle knowledge that doesn't transfer well outside a specific domain (the 'joke' example was a medical expert system that would diagnose rust-patches on a car as measles)
* The problem that as rule sets grew in size, domain knowledge needed to be supplemented by software engineering skills
We found it telling that none of the contributing companies continued to use the rule-based approach for very long when the EU funding dried up, and that none of them successfully commercialised it for a third party company. However, as an experienced programmer rather than an AI researcher, in at least one case, I found that the rule-based approach was a good way of getting domain experts to articulate the heuristics they used, and then embed these in a conventional application. The GUI we developed for the frame-based component was also repurposed for a very successful in-house modelling too, so the codebase wasn't a complete loss.