it’s only as good as it’s training data and how it interprets it. thus you can never have an LLM in any kind of leadership or major decision making role simple because of GIGO - Garbage In, Garbage Out.
they’re painfully easy to manipulate or simply by feeding it bad data. In this case it fucked up it’s time keeping thing which shouldn’t surprise anyone who has done any sort of coding with an LLM and then an idiot human being prompted it to make a decision based on garbage data. It’s like asking a hammer why it failed to manage the construction crew building a house. doesn’t work like that and should never work like that.
In this case it fucked up it’s time keeping thing which shouldn’t surprise anyone who has done any sort of coding with an LLM
This time and earlier last year, yeah. Try again with the newer Anthropic tools and you’ll find them to be rather thorough and correct with their calendar and clock math, handling of edge cases like DST shifts, leap years, etc.
Yeah, I “vibe coded” a timesheet app in about $15 of Claude subscription credits. Actually did it twice: $10 for the Python version, then migrated that to Go for $5 - it does run a lot faster in Go while simultaneously consuming less power / resources. It makes a couple of nicely formatted timesheets, serves multiple clients with multiple service providers, tracks everybodys’ shifts, providers can log in from their phone and accept/drop shifts, schedulers can create new open shifts for providers to consider, etc. etc. - been using it for about a month now, so far the math is flawless - as compared to the human+calculator math that was being used before which seemed to have at least 1 error per 10 shifts computed.
Its almost like we were told very early on, that a machine cannot be held accountable and therefore a machine cannot be in management
it’s only as good as it’s training data and how it interprets it. thus you can never have an LLM in any kind of leadership or major decision making role simple because of GIGO - Garbage In, Garbage Out.
they’re painfully easy to manipulate or simply by feeding it bad data. In this case it fucked up it’s time keeping thing which shouldn’t surprise anyone who has done any sort of coding with an LLM and then an idiot human being prompted it to make a decision based on garbage data. It’s like asking a hammer why it failed to manage the construction crew building a house. doesn’t work like that and should never work like that.
This time and earlier last year, yeah. Try again with the newer Anthropic tools and you’ll find them to be rather thorough and correct with their calendar and clock math, handling of edge cases like DST shifts, leap years, etc.
Which is pretty impressive for a text generator, but if I need accuracy I’m still going to use a mathematical calculator.
Yeah, I “vibe coded” a timesheet app in about $15 of Claude subscription credits. Actually did it twice: $10 for the Python version, then migrated that to Go for $5 - it does run a lot faster in Go while simultaneously consuming less power / resources. It makes a couple of nicely formatted timesheets, serves multiple clients with multiple service providers, tracks everybodys’ shifts, providers can log in from their phone and accept/drop shifts, schedulers can create new open shifts for providers to consider, etc. etc. - been using it for about a month now, so far the math is flawless - as compared to the human+calculator math that was being used before which seemed to have at least 1 error per 10 shifts computed.