It sounds like you're making the argument that deploying k8s for a startup is an extreme case of premature optimization.
You can get tons of credits for your startup, typically hundreds of thousands from Microsoft, Amazon, etc. -- Eventually you run out of credits, so you switch providers. I did this 3 times at a startup and got three years of free infrastructure.
If you are selling enterprise software, then you use k8s so you can deploy at enterprise without having to integrate with all the wacky requirements.
You can build a saas that offers isolated service nodes on k8s infra pretty easy if you just give everyone a small vm with a k8s cluster on it.
If you use a scale to zero model, your infra costs are a lot cheaper. Simiarly the auto-scaling k8s capabilities are really nice and it's awesome to be able to easily build systems that can scale up massively. You never know when you r startup will get popular.
If you mean assembling your own k8s infrastructure by spinning up machines, then you're right.
If you mean deploying your software on managed k8s infrastructure, then this an outstanding use of your startup's time. You will be able to find plenty of developers already familiar with the workflow, and you'll have a straightforward time growing and deploying your app on different providers. It cleanly side-steps many production pitfalls that burned our time 10 years ago.
Many types of startups will benefit from K8s right from day one.
Because all that above? It comes with a system that will actively help you binpack your workloads as much as possible into the compute you give it.
Your usual "throw separate instances"? Can get expensive quick, especially if you're not aggressively modifying instance sizes. As for "lol just use Heroku"... I call that kind of company "bankrupt", but that's probably because the difference between cost of infrastructure and cost of engineer time is wildly different in my area to SV.
All startups are not the same though. If the startup has obtained any kind of reasonable Series A, it totally makes sense to invest in kubernetes, and allow your engineering team to essentially pull in literally any kind of dependency, test it quickly, and find out if it works or not. It acts as a catalyst that would let you churn out new products really quickly, and as such its an invaluable tool to allow your startup to move quickly.
If you work in enterprise environments and are able to use kubernetes, you are set to really shock your organization with how quickly you can move. I've seen this same situation play out in a few orgs and its really amusing how stupidly productive it allows engineers who learn it to be, and how quickly they get things done and get more responsibilities, promotions etc.