gave the first chance to GPT 5.6 Pro today (sorry for being late to the party) and it was very good in a specific way
I was frustrated that Fable was being too risk averse and unwilling to challenge me. I gave it a design for a system, and I included some bad parts in it. I was expecting it to notice and change the bad parts, which would, in turn, increase my confidence it was also finding bad stuff I did *not* notice (which was what I was using it for!). but that didn't happen, because that's Fable. it won't defy the status quo, and that's one of its worst flaws
so, I just dumped the whole chat into ChatGPT Pro, and asked: "this other model is not being helpful, can you handle this?"
and it proceed to identify all the bad parts I knew were bad, and it identified a bunch of additional bad stuff that I missed. exactly what I wanted Fable to do, but it didn't. so, for this use case, it did save the day
now I'm wondering whether this was just a N=1 luck sorta thing, or if there's some deeper lesson here? perhaps the very thing that makes Fable so good for long term work (the code doesn't degenerate into chaos) is what is now frustrating me (it won't defy the status quo). and GPT is inherently the opposite, it will be too aggressive with changes, but will work best when what you need is precisely a bit of critical thinking rather than just flawless execution?