Librarian Hotline: Think With AI by Setting Up Custom Instructions

There’s a difference between using AI and thinking with AI. Using AI is transactional: we ask a question and accept the answer that comes back. Thinking with AI is closer to a working session, where the conversation becomes a way to pressure-test our reasoning and surface what we haven’t yet considered. That working-session version of AI is where the technology becomes useful for sharpening our thinking rather than replacing the work of thinking altogether.

Getting there isn’t simply a matter of asking better questions. It takes a tool that’s willing to engage with our thinking, and by default, ChatGPT and Claude aren’t built for that kind of engagement. Both are designed to be agreeable. They affirm shaky reasoning and generate polished answers to half-formed questions, rarely pushing back even when pushing back is what would actually help us. That agreeableness is a structural obstacle to using AI as a thinking partner, and it shows up in every conversation we have until we tell the AI to behave differently.

That’s where custom instructions come in. They’re the first place we tell the AI what kind of working relationship we want, and the most direct way to shift the dynamic from agreeable assistant to actual collaborator.

“I use ChatGPT a lot for work, and lately I’ve started to wonder if it’s making me worse at my own job. I’m not working through problems the way I used to, and I’m taking everything it tells me at face value. Is there a way to set it up so I’m still involved in the work instead of just outsourcing it?”

— J.R.

A note before we begin: Thank you for being here, whether you’re a free or paid subscriber. This post covers what custom instructions are, where to find them, and the principles that determine whether the AI keeps us mentally engaged or lets us coast (available to everyone). The step-by-step setup in both Claude and ChatGPT, a complete starter set of instructions to paste into either platform, and how to extend the same thinking-partner setup into Projects for ongoing work are available for paid subscribers.

The concern in this question is one of the defining themes of our current moment. AI tools are powerful enough to handle the analytical work we used to do ourselves, and using them constantly without the right guardrails can leave our own reasoning a little weaker each time we open a chat. The reflex to just accept what comes back can be hard to resist, but the cost of that reflex compounds. Once we stop asking our own questions, the AI becomes the only voice in the conversation.

The way out is to change how the AI shows up in the conversation in the first place, and the lever for that is a feature called custom instructions. Both ChatGPT and Claude have a text field in their settings where we can write a short note the AI reads before every conversation begins. What goes in that field shapes the entire dynamic that follows. Used well, it can be the difference between an AI that hands us a finished answer every time and one that asks what we’ve already considered before responding, then pushes back when our reasoning has a gap.

The most common approach to filling this space is with practical details like a job title or a formatting preference. But the same space can go further, changing how the AI responds when we bring it a half-formed idea or a question we haven’t fully worked through yet.

Whatever we paste into the custom instructions field becomes a standing directive for the AI, applied to every new conversation. The wording we choose shapes the starting point of those conversations, and what that starting point looks like is up to us. Asking the AI for shorter, faster answers will tend to produce shorter, faster answers. Asking it to slow down and surface gaps in our reasoning will steer the conversations in that direction instead.

Here’s the kind of note someone might write if they want quick, usable output:

“I’m a marketing manager. Give me concise answers.”

And here’s an alternative someone might write if they want the AI to slow them down and engage with their reasoning:

“Before giving me a solution, ask me what I’ve already considered. If my thinking has a gap, point it out before moving forward.”

Both are useful, but they create very different experiences. A direct prompt for concise answers gets us to a finished result faster, which makes sense when we know exactly what we need. A prompt asking the AI to question our reasoning and point out gaps before answering creates a back-and-forth where it slows down and pushes back when something looks off. That kind of back-and-forth is what keeps us mentally engaged in the work instead of waiting on the AI to finish it for us, and it starts with writing instructions that build friction into the process on purpose.

The most useful kind of friction is making the AI ask us something before it gives us an answer. AI can produce a polished response before we’ve had a chance to work through the question ourselves. A polished answer is easy to accept at face value, especially when it’s well-written and addresses what we asked. An instruction like "when I bring you a problem, ask me what I've already tried or considered before jumping to a solution" changes the order of the conversation. Instead of the AI going straight to an answer, it has to check in with us first. That moment, where the question turns back to us, gives our own thought process and judgment a chance to surface before the AI fills the space.

That principle extends naturally to the assumptions embedded in our questions. Without explicit permission to push back, AI will build on whatever premise we hand it, even a shaky one. If we walk in with a flawed assumption baked into our question, the AI will treat it as settled and build from there. An instruction like “if my question contains an assumption that might be wrong, flag it” gives the AI a role beyond answering: checking whether the question itself holds up. It’s a challenge to give ourselves that kind of scrutiny unprompted, which is exactly why it helps to build it into the tool.

Both of these ideas can live side by side in a single short paragraph in the custom instructions field. The result is an AI that stops producing answers on autopilot and starts drawing us into the process, where our own thinking has a chance to shape where the conversation goes.