Mercury LLM might work better getting input as an ASCII diagram, or generating an output as an ASCII diagram, not sure if both input and output work 2D.
Plumbing/electrical/electronic schematics are pretty important for AIs to understand and assist us, but for the moment the success rate is pretty low. 50% success rate for simple problems is very low, 80-90% success rate for medium difficulty problems is where they start being really useful.
I wouldn't trust it with 2d ascii art diagrams, there isn't enough focus on these in the training data is my guess - a typical jagged frontier experience.
See these two solutions GPT suggested: [1]
Is any of these any good?
[1] https://gist.github.com/pramatias/538f77137cb32fca5f626299a7...
Humans make errors all the time. That doesn't mean having colleagues is useless, does it?
An AI is a colleague that can code very very fast and has a very wide knowledge base and versatility. You may still know better than it in many cases and feel more experienced that in. Just like you might with your colleagues.
And it needs the same kind of support that humans need. Complex problem? Need to plan ahead first. Tricky logic? Need unit tests. Research grade problem? Need to discuss through the solution with someone else before jumping to code and get some feedback and iterate for 100 messages before we're ready to code. And so on.
