I use models from Opus through Haiku and down into Qwen locally hosted models.
I don't know how anyone could believe that Haiku is useful for most engineering tasks. I often try to have it take on small tasks in the codebase with well defined boundaries to try to conserve my plan limits, but half the time I end up disappointed and feeling like I wasted more time than I should have.
The differences between the models is vast. I'm not even sure how you could conclude that Haiku is usable for most work, unless you have a very different type of workload than what I work on.
More information required. What are you working on? What languages? How do you define “small tasks”? What are “well-defined boundaries”? What is your workflow?
Most importantly, define your acceptance criteria. What do you mean by “disappointed” - this word is doing most of the heavy lifting in your anecdote. (i.e. I know plenty of coders who are “disappointed” by any code that they didn’t personally write, and become reflexively snobby about LLM code quality. Not saying that’s you, but I can’t rule it out, either.)
The models are not the same, but Haiku is definitely not useless, and without a lot more detail, I just ignore anecdotal statements with this sort of hyperbole. Just to illustrate the larger point, I find something wrong with nearly everything Haiku writes, but then again, I don’t expect perfection. I’d probably get a “better” end result for most individual runs with the more expensive models, but at vastly higher cost that doesn’t justify the difference.
I use Haiku frequently, and for my codebase it is working fine.
But I'm not vibecoding, I don't let models do large work or refactorings, this is just for some small boring tasks I don't want to do.