alt Hacker NewsI think you are broadly correct, but just to pushback on a few points: (1) Ability to solve hard problems in days vs weeks as immense value (2) Back-end improvements (if done right), should improve platform speed, stability, scalability etc. which should have revenue implication (3) Ability to on-board a SWE equivalent entity in minutes, have them work on a specific hard problem and then off-board them in minutes can have value
All of the above, of course, depends upon Fable consistently being a 2x-3x SWE at minimum.
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> Back-end improvements (if done right), should improve platform speed, stability, scalability etc. which should have revenue implication
Depends entirely on the domain. If you're selling entreprise software, this kind of stuff barely matters for sales.
It can reduce operational costs which is good but there's a limit to how much that's worth.
In my experience, the challenge in software development is not to solve a problem, but to define the outcome, the scope, the acceptance criteria etc.
20x the cost means you need to have fable to be 20x better than the alternative, which is a tall order. And there's more options out there too, perhaps the 4x cost is enough.
This means if the deepseek / under 1k alternative is at least x1.2 improvement, fable needs to be x24, which I think is very2 unreasonable. It is possible for it to worth if it can x2 a $20k SWE, though I doubt it can do that.
The thing about AI-generated “solutions” is that they often go down bad rabbit holes and need to be re-run, or since they are so “cheap” to create they are often just thrown away and rebuilt when requirements evolve. Plus, just more stuff is created and needs to be maintained. So in the end, your efficiency gains go out the window.
“Ability to solve hard problems in days vs weeks as immense value”. Citation needed.
LlMs are incredible don’t get me wrong, but they are good on tiny contexts (writing a script). Not on software engineering (adding features to Chrome).
>pushback on a few points
Claude keeps telling me this when I argue with it. LMAO.
You're not really solving problems, you're retrieving the best match of solved problems from compressed corpus. And that corpus is available to many companies, meaning "hard" problems stop having "hard problem" value the moment they enter the weights of any model via the internet ... or distill from one model to another. Anthropics business model is commoditising knowledge, but as we see with the Fable model card, they only want it done to the knowledge of other businesses, in their own field, they totally hate it.