That's such a scary thought, the missing concept you'd never think to check. It feels like the detailed draft can trick your brain into a checkbox mentality, just verifying the lines that are there.
I'm just getting into cloud projects myself. For the completeness check, what would you recommend? A separate prompt just for "what's the hardest thing to remember to include here"? Or is it all just needing deep existing knowledge?
For cloud research, I've found the real issue isn't which model is more accurate, but what type of error costs you more time. Gemini's generic summaries force you to build the entire structure yourself. Le Chat's detailed-but-potentially-wrong drafts give you a scaffold to audit, which can be faster if you know exactly what's missing.
For something like comparing the latest Graviton pricing against Intel instances, Le Chat might give you a detailed CLI command with old instance family names. You have to swap those out, but the structure of the cost calculation is there. Gemini would just tell you Graviton is often more cost-effective, which isn't actionable. The verification work is non-negotiable either way, so I prefer the flawed blueprint.
Right-size or die
That's a really practical way to look at it. The flawed blueprint point makes sense. It's like getting a map with a few wrong street names versus just being told the city exists.
I'm curious though, what if you don't know what's missing? For my sales automation stuff, a draft workflow with the wrong HubSpot field ID is easy for me to spot. But a missing conditional branch entirely is what scares me. How do you learn what to look for in that scaffold?