Some of this rings true - yes, there are SaaS companies leaping onto to the A.I. hype train with little regard (or care) whether AI can add any real value to their product.
But Zitron conflates this with a lack of potential or capability of A.I. itself. This is absolutely not true. Any developer who has spent any length of time pair programming with A.I. or using it to analyse/debug code will understand immediately what I’m talking about. 5,000 LOC files debugged, discussed or refactored in seconds. Bugs tracked down in an instant instead of an hour. When AI fits a task well, it adds immense, jaw dropping value and it’s clear to me that, with LLMs harnessing transformers we have discovered something new and revolutionary.
I havent coded in years, so I'll take your word for the potential of AI in SWE. But, software development has guardrailed against bad code with unit testing, CI/CD, etc. Also, productivity / output can be measured more-or-less well. Partly for that reason, it's also used to efficiency shifts (say from C++ to Java; or Perl to anything...) and those are not usually massive, all-or-nothing changes.
Where's the equivalent in customer support? or document creation? or any of these other mythical AI use cases? genuinely asking.
The article makes a good case that the SaaS bubble is deflating and needs a new hype cycle to keep investment up. AI makes sense for that, so at least that's one good use case :-)
Comments
Some of this rings true - yes, there are SaaS companies leaping onto to the A.I. hype train with little regard (or care) whether AI can add any real value to their product.
But Zitron conflates this with a lack of potential or capability of A.I. itself. This is absolutely not true. Any developer who has spent any length of time pair programming with A.I. or using it to analyse/debug code will understand immediately what I’m talking about. 5,000 LOC files debugged, discussed or refactored in seconds. Bugs tracked down in an instant instead of an hour. When AI fits a task well, it adds immense, jaw dropping value and it’s clear to me that, with LLMs harnessing transformers we have discovered something new and revolutionary.
I havent coded in years, so I'll take your word for the potential of AI in SWE. But, software development has guardrailed against bad code with unit testing, CI/CD, etc. Also, productivity / output can be measured more-or-less well. Partly for that reason, it's also used to efficiency shifts (say from C++ to Java; or Perl to anything...) and those are not usually massive, all-or-nothing changes.
Where's the equivalent in customer support? or document creation? or any of these other mythical AI use cases? genuinely asking.
The article makes a good case that the SaaS bubble is deflating and needs a new hype cycle to keep investment up. AI makes sense for that, so at least that's one good use case :-)