In this channel's material, custom instructions appears in two different modes. In the product sense, it is a settings layer in ChatGPT: a persistent block of context about the user — tendencies, goals, working style — that the model applies across conversations without being re-prompted. The interviewer's practice is the channel's flagship example: he stores his tendency to be “too opportunistic” plus his quarterly goals there, so the model nudges him back on track whenever a shiny idea appears — “a screen-time reminder” for strategy. Sahil Lavingia extends the same logic to the team level, pairing goal-holding in the product with a standing rule that employees spend five hours evaluating ideas with the model rather than deferring them to next quarter — clearing half-examined ideas out of everyone's head and removing excuses across the company. In the setup-design sense — most explicit in the Writing Camp Q&A — custom instructions is one slot in a layered AI writing stack, distinct from style guides and from skills; each slot carries a different kind of standing context, and knowing which layer a given preference belongs in is part of designing the setup.