Alignment is mostly about making cognition aimable at all

If I understand you right, you're thinking of scenarios like "the AI initially tries to create lots of watery looking stuff, but then it later realizes that watery looking stuff can be made of different substances (e.g., oxygen paired with protium vs. deuterium)". We can imagine different outcomes here, like:

1. Some part of the AI feels like protium is important for "real water", while another part feels that deuterium is important for "real water". So the AI spends a lot of its resources going back and forth between the two goals, undoing its own work regularly.
2. The AI thinks about its values, and realizes that (for some complicated reason related to how it does reflection and how its goals work) it's really deuterium-containing water that it likes, not protium-containing water. So it switches to making heavy water exclusively. 
3. The AI thinks about its values, and realizes that (for some complicated reason related to how it does reflection and how its goals work) it wants to put 90% of its resources into producing heavy water, and 10% into producing light water.

Whether 1 counts as "one agent that's internally conflicted" versus "multiple agents in a tug-of-war for control" might turn out to be a matter of semantics, depending on whether there turns out to be a crisp and natural interpretation of the word "agent".

Whether 2 counts as "the agent self-modifying to change its goals" versus "the agent keeping the same goals but changing its probability distribution about which physical things those goals are pointing at", may also turn out to be an unimportant or arbitrary distinction. It at least doesn't seem very important from a human perspective: the first kind of agent may have a different internal design than the second kind of agent, but the behaviors are likely to look the same from the outside, since sufficiently coherent agents optimize expected utility (probability times utility) in practice, and it may be hard to say from the outside which parts of the expected utility are probability vs. utility, especially if the agent's doing a bunch of complicated reflection and self-modification.

Similarly, whether 3 counts as "normative uncertainty about what's best" versus "complete certainty in a meta-level goal that assigns some utility to heavy water and some utility to light water" may turn out to be a somewhat arbitrary distinction.

I understood Nate's post to be saying that sufficiently capable agents tend to stop looking like 1, not that they necessarily tend to stop looking like 2 or like 3.

In principle it's possible for an agent to stably consist of some sub-agent that optimizes heavy water on Mondays and Tuesdays and light water on the other days of the week. But because the first sub-agent will tend to want to disempower the second sub-agent (so it can produce more heavy water on other days of the week), and the second sub-agent will tend to want to disempower the first sub-agent, there are many scenarios where one sub-agent or the other ends up "winning".

(Or, failing that, the two sub-agents will tend to eventually agree to effectively merge into a new agent that values a compromise between the goals of the original two sub-agents, since both agents can get more of what they want if they spend fewer resources on undoing the other agent's hard work.)