u/Dismal_Ad_9032

I like local AI, but I think apps should be more honest about where local models are not the best choice.

Some tasks need the strongest reasoning model available. Some need current web info. Some need very large context. Some need high accuracy. Some are just faster and easier in cloud tools.

Local AI is great for privacy, offline access, drafts, notes, simple coding help, and working with sensitive files. But it is not always the best tool for every job.

I would trust local AI apps more if they were clear about their limits.

Should local AI apps actively guide users away from local models for certain tasks?

ok so most AI tools help you after something happens. summarise this, analyse that, write this report.

but what about before you make a call

like the actual moment where you decide something big and have no real way to know what it sets off. you just commit and find out later what broke

been looking at this concept of a decision simulation engine. you put in a decision, it models every stakeholder affected, competitors, regulators, customers, and maps out what each one does in response. then shows you the full chain of consequences before anything is real

found myndfield which is doing exactly this. not a prediction tool, more like infrastructure for the decision itself. shows you probability weighted outcomes, where you are most exposed and lets you run multiple versions of the same decision side by side feels like a genuinely different category than anything i have seen so far

anyone else looking at tools like this or think this is actually where enterprise AI is heading?