The problem is not that LLM or, say, generative AI tools such as Midjourney, "have no imagination" and collapse upon the same solution. Anyone who has spent any serious time exploring what was originally called the "latent space" Midjourney provided a view into, is aware that the combinatorics around what these systems have ingested is inconceivably large and full of wonders and surprises... what we might well describe as unexpected, novel, dare I say creative, imagery [etc.]
The problem AFAICT is asking for examples of something without providing any process or instruction.
Vibe-coded single-shot prompts are inevitably (unless this is patched) going to converge on statistically-likely or contextually hinted examplars.
And this is true all the way down. It's true of secondary and tertiary features (what camera angle do we have on the pelican? Is it a juvenile or injured? Is it riding to the left or right? etc.)
The fact that humans are a heterogeneous pool with different experiences and capabilities, means if you sample humans, you get high variability. If you ask contemporary LLM, they are converging, indeed, but not in the way implied; they are converging because the corpus they are trained on is comprehensive and coextensive.
What you get is the centroids in the space.
Until you simply ask for something else.
If you want more "creative" examples, of pelicans or anything else, it's more or less trivial to get them. And if you detect durable secondary or tertiary qualities you want to see varied, you ask.
More seriously,
if what you want is to interact with large capable models/systems which by default exhibit variability , you do the (minimal) work to make that happen.
Midjourney has from very early on exposed explicit dials to turn in exactly this way.
I am surprised the author does not know this.