◇ Could this help me?
Yes. All three are sound and the first is the one most people actually get wrong: an agent's output quality is bounded by the context it was given, and writing down the standing preferences and constraints that live in your head is the single highest-return habit here. The verification pattern is real and useful, but worth one correction the summary does not make: a second agent checking the first shares most of the first one's blind spots, so it catches slips and inconsistencies rather than shared misunderstandings, and it lowers the need for human review without removing it. General practice.
Help me write down the context an AI assistant would need to do my work well, which currently only exists in my head. Interview me about the standing constraints, the preferences about how things should be done, the vocabulary specific to my work, and the things that are never acceptable. Turn that into a reusable instructions file. Then define a role and a longer-term goal for the assistant rather than a list of tasks, and propose a verification step for the outputs that matter most, being explicit about which kinds of errors a second automated check will catch and which ones still need me to look.