alt Hacker NewsCounterpoint, why do current state of the art generative AI companies, with the ability to use models that the public can't even access, and the ability to burn tokens at cost, still pay for very expensive Saas software?
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Addendum to counterpoint: why haven't those SotA gen-AI companies become the most productive software companies on earth, and release better and cheaper competitors to all currently popular software?
People always gripe about the poor quality of software staples like Microsoft Office or GitHub or Slack. Why hasn't OpenAI or Anthropic released a superior office suite or code hosting platform or enterprise chat? It would be both a huge cash cow and the best possible advertising that AI-facilitated software development is truly the real deal 10x force multiplier they claim.
If someone invents a special shovel that can magically identify ore deposits 100% of the time, they aren't going to sell it with the rest of the shovelmongers. They're going to keep it to themselves and actually mine gold.
Because SaaS at the corporate level is about liability transfer first and any value or functionality is a distant second.
their costs are bound to compute anyway, they don't mind huge compensations also - it's not much of a cost saving to re-build, even cheaply, inhouse Slack or whatever?
How is that a counterpoint? Do these companies currently use as many SaaS as other companies? More importantly, will they do so in the future?
Bingo!
... and why are they still loosing billions of $? Surely their AI can help them (say) generate good biz models? :-)
Opportunity cost.
Cloning Slack and wasting ultra-expensive engineers on that might be more expensive, and it's not your core mission.
That's really simple - actually writing the software has never really been the hard part in most SaaS apps. So long as you're moderately disciplined and organised it's easy to build what most SaaS apps are e.g. a CRUD-app-with-a-clever-bit. The clever bit is the initial challenge that sets it apart from the rest, but encoding that in software has never really been that difficult.
Having the ideas necessary to know what to write is where practically all the value lies (caveat: there is value in doing the same as someone else but better, or cheaper.) AI can help with that, but only in so much as telling you the basics or filling in the blanks if you're really stuck. It can't tell you the 'clever bit' because that is by definition new and interesting and doesn't appear in the training data.
What this means is that at some point Anthropic will be able to prompt Opus to clone Jira and never pay an Atlassian bill again. Opus just needs to figure out what Jira is first. It's not there yet.