Just add a couple of feedback loops, if they're strange enough it might work.
Edit: Fun fact, the Winograd Schema Challenge (https://en.wikipedia.org/wiki/Winograd_schema_challenge) is named after Terry Winograd, the author of SHRDLDU.
I always thought the effort must have been related to code like this. This simple language interpreter can do lots of things, but only in its small world of boxes and pyramids. It follows that if you teach it a bunch of things and how they relate to each other, you'd create an intelligent computer.
Instead that whole field was dropped, presumably because it didn't work, and eventually neural networks started to be thought of as the next generation of soon-to-be-AI systems. But it's pretty apparent by now that things like GPT-3 are hollow shells, good at emulating some very specific things humans can do, but there's nothing remotely like intelligence behind it.
I wonder if in 20 years we'll look back at this as another dead end on the road to AI.
Doug Lenat left Stanford and moved to Texas to focus on Cyc... and I always wonder when he'll return triumphantly to Silicon Valley with a "100% complete" knowledge base in hand :)
But I suspect the next time somebody tackles a project like this it'll use natural language parsing to derive its dataset from all the world's written text, automatically. Wikipedia will tell you a pea is green, if you can read it.