To me the biggest gain I see is that you take the programmers out of the loop. Instead of formulating your ideas to start a project and then acquiring the resources to do a single iteration on it which may take months if not years, now many specialists "just do it" and do several such iterations in a single day. Afterwards they may still go the ordinary route via programmers but on a completely different level and a lot of fruitless work is frontloaded and 100x cheaper. This doesn't show up in any such statistic.
So, the question is not "Does it make our programmers more productive?" but "Does it make our organization faster?".
I have great hope that the CAD & FEM field will benefit greatly from LLM use. To my understanding we currently don't have a free CAD kernel and broadly applicable FEM solver because these are just too hard to make because geometry and physics are hard unforgiving problems. But all pieces of information are available and many implementations covering some details exist. So, the task is a lot of literature research and putting everything together and that's where LLM based agents should shine.
Of course we won't 1-shot a new CAD kernel but the human work will likely shift more towards identifying failure modes, specifying test cases and sometimes solving really hard details. Sometimes even working out details that have no precedent in literature or free code.
My feeling is that GPT-5.5 doesn't lack the raw intelligence so much as it lacks "methodology". I don't know how exactly to put it... how to approach a problem, how to take care of the details and side effects, how to handle unexpected difficulties and bugs, how to not spin out of control, how to write solid code, how to clean up afterwards, how to document, how to give useful feedback... the things that you learn on the job.
So, if they improved a lot in those areas, then GPT-5.6 could become a lot more useful compared to GPT-5.5 even though it might score lower in many benchmarks. It's possible but unlikely since their approach was mostly brute force in the past.
On what setting in which environment do you run it? I use the VSCode extension on Extra High and feel like it does exactly what needs to be done and stops when the thing I asked for is done. Extra comments come only when they fall into the area of code that was changed.
In a past life i tried to implement Delaunay triangulation in floating point for data that can come in a rotated square grid. Normal precision doesn't work in that case. I learned a lot about arbitrary precision numbers doing that. The question about floats here gave me flashbacks.