The coin example you refer to is one of the classic arguments for probabilistic reasoning.

Say someone tosses a coin. Before the toss, I estimate the probability to be 0.5. Coin lands, I don't know the result. My frequentist soul tells me that it is either heads or tails, but not a random variable with associated probability

Your correct in that the coin is either heads or tails. The probability that you assign it is a statement about your state of knowledge of the system, which contains uncertainty. This is particular to you: it is your reasoning that indicates to you, given the facts that you have in your possession (this is typically the $I$ in $p(\rm{heads} | I)$.

This is a fundamental point of difference, in probabilistic reasoning (or Bayesian reasoning), we try to recognize that the probability we discuss are not inherent features of the system under study (in this case a coin), but they are quantifiers of our (or someone robot's) state of knowledge about the system.

So the classic argument goes that someone else then 'takes a peek' at the coin. For them, the probability has collapsed to the coin being either heads or tails. Their state of knowledge now has no uncertainty. But for you, your state of knowledge remains unaffected by the fact that they looked. Now of course if they try to make a bet with you it may change your state of knowledge, but I'll leave my explanation at that.

The coin example you refer to is one of the classic arguments for probabilistic reasoning.

Say someone tosses a coin. Before the toss, I estimate the probability to be 0.5. Coin lands, I don't know the result. My frequentist soul tells me that it is either heads or tails, but not a random variable with associated probability

You're correct in that the coin is either heads or tails. The probability that you assign it is a statement about your state of knowledge of the system, which contains uncertainty. This is particular to you: it is your reasoning that indicates to you, given the facts that you have in your possession (this is typically the $I$ in $p(\rm{heads} | I)$.

This is a fundamental point of difference, in probabilistic reasoning (or Bayesian reasoning), we try to recognize that the probability we discuss are not inherent features of the system under study (in this case a coin), but they are quantifiers of our (or someone robot's) state of knowledge about the system.

So the classic argument goes that someone else then 'takes a peek' at the coin. For them, the probability has collapsed to the coin being either heads or tails. Their state of knowledge now has no uncertainty. But for you, your state of knowledge remains unaffected by the fact that they looked. Now of course if they try to make a bet with you it may change your state of knowledge, but I'll leave my explanation at that.