Kudos on building something cool to solve a pain point, but unsure about the efficacy of this implementation.
Kudos on building something cool to solve a pain point, but unsure about the efficacy of this implementation. A list of negative-sentiment tweets about competitor products is certainly a good place to start, but is by no means a list of actionable leads. Still requires quite a bit of human interaction to figure out which tweets are actually solid leads, and is only truly useful if your competitors have only one product. You also miss out on users asking for suggestions who aren't currently using a competitor product (which IMO is a more valuable segment). A more interesting implementation is one that takes context into account, but that would require some homemade ML work and likely outside of the scope of quick & hacky solutions.
Posted by shayanjm on Feb 18, 2015, 5:14 PM
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- I think this release is really going to give them a hard time selling Fable: > On our benchmarks, Claude Opus 5.5 leads in agentic codin...
- My biggest problem with this is that this regulation is only aimed at AI.
- Because it works too reliably.
- OCaml's type system is quite janky and simplistic compared to Haskell's.
- This is a very annoying problem, it's infuriating, you pay 10 USD<->20 USD/mo, and the ads are not even removed.
- These are markets that are being developed actively by car companies.
Raise real-world problems, find people facing the same issue, and discuss solutions.8,000 issues0 comments
hackernews (Marketing)
I think this release is really going to give them a hard time selling Fable: > On our benchmarks, Claude Opus 5.5 leads in agentic codin...
My biggest problem with this is that this regulation is only aimed at AI.
Because it works too reliably.
OCaml's type system is quite janky and simplistic compared to Haskell's.
This is a very annoying problem, it's infuriating, you pay 10 USD<->20 USD/mo, and the ads are not even removed.
These are markets that are being developed actively by car companies.
> We can see that because people who put their money where their mouths are, like venture capitalists, encourage those behaviors.
So what is the unmet need behind an obsession with sexless/child-like figures?
Kudos on building something cool to solve a pain point, but unsure about the efficacy of this implementation.
Kudos on building something cool to solve a pain point, but unsure about the efficacy of this implementation. A list of negative-sentiment tweets about competitor products is certainly a good place to start, but is by no means a list of actionable leads. Still requires quite a bit of human interaction to figure out which tweets are actually solid leads, and is only truly useful if your competitors have only one product. You also miss out on users asking for suggestions who aren't currently using a competitor product (which IMO is a more valuable segment). A more interesting implementation is one that takes context into account, but that would require some homemade ML work and likely outside of the scope of quick & hacky solutions.
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