[alexhans]

I'm a broken record but with:

- evals

- limiting AIs to tool calling, bounded planning, interpreting/producing natural language.

- bounding non determinism

- investing in small tools/security (If something shouldn't happen, then it shouldn't not be possible, RBAC style).

They can be good enough for a massive amount of contexts.

[samrus]

This thing will be far more specific to whatever usecase your thinking of. It wont generalize as much and as easily as LLMs do. Youre heading back towards IBM's watson

[pixl97]

This is simply a different kind of AI than LLMs will ever be. There may be some kind of architecture that does this in the future, but it's not, and can never be a neural network that is attempting to be AGI.

[b3nji]

Can you expand on this for someone that is a dummy and new to using LLM's properly?

[alexhans]

I could but I'd probably miss the angle that is helpful to you. Do you want to instead share what your pain points are, what are you trying to delegate to AI and what you aren't? Based on that I can expand my answer better with a thing or two you can try.

[cadamsdotcom]

Have a look at any mass manufacturing process.

Raw materials in, lots of process steps in the middle with tolerances etc; some % yield of goods out.

When you work with LLMs, the "raw materials" is its first attempt to answer your prompt.

Mass manufacturing mirrors what we do with LLMs to knock their output into shape: grounding, automated quality checking tooling (eg. linters for code, grammar checkers for prose), and ultimately, as many turns as needdd to manually bang the output or work product into shape...

You should never ship your AI's first draft - that'd be slop. But you also shouldn't have to repeat yourself to get its output into a form you can use. If you know you're always going to have to tell it to change one specific thing, see if you can automate a process that tells it to change that thing for you, so you don't have to. Do this enough times and you've created a deterministic outcome at least at some level. And you're out of that loop of getting it to that level.

Tooling for this is limited today. You can provide instructions; but you're always at the mercy of labs to make models that follow instructions and at their mercy that they didn't put conflicting instructions in the system prompt.

Better to put in things like linters and grammar checkers - even going as far as putting in a fact checking process or for legal stuff, a citator.

Without these extras, AI output is no more real than some dream you had.

[AmericanOP]

Or more simply, accept revealed costs.