Furthermore, due to autoregressive nature of GPT models, the more auto-gpt generates (the more it works, the more tasks it performs..) the chance of things going off the right path grow exponentially, and then it is 'doomed' to the end [1].
Thus, chance of this being actually useful for anything longer than what a simple prompt can already do with a tool like ChatGPT is very low.
The end result is an impressive concept but a practically unusable tool. And the problem, in general, is that as the auto-gpt improves (which it will at impressive pace), so will our ambition in using it, which will lead to constant disappointment and what we have today will be generally how we feel about it in the future. Always needing "just a bit more", but never really there.
We already have a "baby AGI" that has been deployed in production environment for a few years - it is called Tesla self driving. It was supposed to get us from point a to point b completely autonomously. And for 6 years now it has been almost "almost there", but never really there (and arguably never will be).
What this does though, is create and inflate a giant FOMO, and the best way of dealing with FOMOs (long term) is to stay on the firm ground, observe, wait for clarity and the right action.
[1] Watch in particular Yann LeCun's presentation at https://www.youtube.com/watch?v=x10964w00zk