Wrapping business processes around these LLMs is the same kind of hard organizational problem plaguing most internal IT projects. People are still the bottleneck.
You also run into the issue of accuracy compounding. Running multi step flows with AI compounds the success rate and dramatically increases the chances of a full-job failure. E.g. even at 99% success rate for any single step, a 30-step process is only likely to succeed 75% of the time without errors. If you go down to 95% success for each, you only have a 75% likelihood of flawless execution at about 6 steps.
So it’s also about getting those per step success rates way up.
lenzm · 4m ago
It has been years, when will it not be too early?
codyklimdev · 46m ago
I think a lot of the reasons for this is because AI helps provide a productivity boost to non-profitable sectors of most businesses, i.e. software development, finance, HR, etc. Since these departments do not directly drive profits, there's no visible bottom line to make meaningful observations on.
I do software for a retail company now and we've been having a similar debate: AI helps me and other departments do work more efficiently, but me getting a feature out the door faster is better for the business but doesn't get more products off the shelves. So, to the shareholders and the C-suite, is AI doing anything for the company?
comte7092 · 37m ago
> Since these departments do not directly drive profits, there's no visible bottom line to make meaningful observations on.
“Bottom line” is a reference to costs, it doesn’t matter whether a department is a profit center. If AI is making these departments more efficient, it should show up in the bottom line.
credit_guy · 32m ago
AI does show up in the bottom line, but it’s not attributable to AI. How can you tell if the last month’s 20 new features vs 10 new features the same period one year ago are due to AI or simply to your developers being smarter/working harder/returning to office, etc?
comte7092 · 17m ago
I would pose that question back to you, if it isn’t measurable, how are you certain that it is affecting the bottom line?
ericdotlee · 36m ago
My guess is they don't really know how to price it in yet - but also they seem to massively reduce headcount in areas where you can loftily make assumptions that "ai is boosting productivity"
Seems like hand waving and layoffs will have to stop before we get real data
Wrapping business processes around these LLMs is the same kind of hard organizational problem plaguing most internal IT projects. People are still the bottleneck.
You also run into the issue of accuracy compounding. Running multi step flows with AI compounds the success rate and dramatically increases the chances of a full-job failure. E.g. even at 99% success rate for any single step, a 30-step process is only likely to succeed 75% of the time without errors. If you go down to 95% success for each, you only have a 75% likelihood of flawless execution at about 6 steps.
So it’s also about getting those per step success rates way up.
I do software for a retail company now and we've been having a similar debate: AI helps me and other departments do work more efficiently, but me getting a feature out the door faster is better for the business but doesn't get more products off the shelves. So, to the shareholders and the C-suite, is AI doing anything for the company?
“Bottom line” is a reference to costs, it doesn’t matter whether a department is a profit center. If AI is making these departments more efficient, it should show up in the bottom line.
Seems like hand waving and layoffs will have to stop before we get real data