[mlcruz]

> we have a means of giving them full business/human levels of context

Trust me, this is a work in progress. Right now most corporations do not have their data organized and structured well enough for this to be possible, but there is a lot of heat and money in this space.

Imo, What most of the people that are not directly working in this space get wrong is assuming swes are going to be hit the hardest: There are some efficiency gains to be won here, but a full replace is not viable outside of AGI scenarios. I would actually bet on a demand increase (even if the job might change fundamentally). Custom domain made software is cheaper as it has ever been and there is a gigantic untapped market here.

Low complexity to medium complexity white colar jobs are done for in the next decade through. This is what is happening right now in finance: if models stopped improving now, the technology at this point is already good enough to lower operational costs to the point where some part of the workforce is redundant.

[packetlost]

> Right now most corporations do not have their data organized and structured well enough for this to be possible, but there is a lot of heat and money in this space.

I think you misunderstand what I'm saying. I'm not really referring to data systems at all, I'm referring to context on what problems are actually being solved by a business. LLMs very clearly do not model outcomes that don't have well-defined textual representations.

I'm not sure that I agree with white collar jobs being done for, not every process has as little consequence to getting it wrong as (most) software does.

[mlcruz]

> I think you misunderstand what I'm saying. I'm not really referring to data systems at all, I'm referring to context on what problems are actually being solved by a business. LLMs very clearly do not model outcomes that don't have well-defined textual representations.

Yeah i misunderstood your point, i completely agree with what you are saying.

I honestly do not believe that strategy, decision making and other real life context dependent are going to be replaceable soon (and if it does, its something other than llms).

> I'm not sure that I agree with white collar jobs being done for, not every process has as little consequence to getting it wrong as (most) software does.

Maybe im too biased due to working in a particularly inefficient domain, but you would be surprised how much work can be automated in your average back office.

Much of the operational work is following set process and anything out of that is going to up the governance chain for approval from some decision maker.

LLM based solutions actually makes less errors than humans and adhere to the process better in many scenarios, requiring just an ok/deny from some human supervisor.

By delegating just the decision process to the operator, you need way less actual humans doing the job. Since operations workload is usually a function of other areas, efficiency gains result in layoffs.

[packetlost]

> Maybe im too biased due to working in a particularly inefficient domain, but you would be surprised how much work can be automated in your average back office.

> Much of the operational work is following set process and anything out of that is going to up the governance chain for approval from some decision maker.

Oh that's very interesting! Thank you for the insights!

[Planktonne]

> Trust me, this is a work in progress. Right now most corporations do not have their data organized and structured well enough for this to be possible, but there is a lot of heat and money in this space.

This is exactly what people were saying a decade ago when everyone wanted data scientists, and I bet it's been said many times before in many different contexts.

Most corporations still haven't organised and structured their data well enough, despite oceans of money being poured into it.