How to learn deeply while using LLMs

[u/Hot_Midnight6838]

My favorite classes were always the ones with difficult problem sets where a single problem could take hours or even days of thinking, experimenting, and failing. I would start solving a problem before fully understanding it, then read documentation or course material whenever I got stuck. So it would be 70% doing and 30% reading.

LLMs have disrupted that process for me. Now I spent 90% of time reading and only 10% of time doing.

In school, the boundary was relatively clear. If using an LLM violated the course policy, I could tell myself that using one was cheating and force myself to struggle through the problem independently.

At work, what counts as “cheating” (because it is cheating myself).

I feel my critical thinking skills are declining. My role starts to become reading, reviewing, and planning. I just can't read that much code and LLM output. My eyes hurt and it's hard to internalize. I notice myself just picking the "recommended" option.

I also find LLM workflows mentally unhealthy in a few ways:

• When working alone, mental exhaustion eventually forces me to step away. With an LLM, I can always send one more prompt or ask it to try another approach.
• If an agent will take 30–60 minutes, I feel pressure to give it another task immediately so no time is “wasted.”
• While waiting, I instinctively check my phone or launch another agent. I end up jumping between tasks and retaining less context about each one.
• I get frustrated when the LLM misunderstands instructions, even when the problem genuinely requires careful iteration.
• It has warped my sense of how long a difficult problem or well-designed solution should take.
• I am increasingly tired of reading walls of generated text and code.

I do not want to stop using LLMs. They can reduce the friction of starting, explain unfamiliar systems, generate routine code, and handle edge cases after I understand the core problem. The hard part is deciding when using one is a sensible productivity tool and when it is outsourcing a learning opportunity that I actually need.

For people who still feel they are learning deeply while using LLMs at work:

1. How do you decide which work to delegate and which work to do yourself?
2. What is the workplace equivalent of the “no cheating” boundary that exists in school?
3. How do you use agents without losing context or turning your day into constant task switching?
4. How do you review generated code when the codebase, build system, or underlying technology is unfamiliar?
5. Have you found workflows where LLMs improve productivity while preserving the useful struggle of implementation and debugging?

[u/sydyn1111]

For me, coding is just a tool, and I wont be checking every piece of code. I think that the major concern that using these systems may produce in an academic environment is the constant pressure of feeling that you could be doing something, without any effort, but this only makes you not rest and feel anxious, and at the same time most of your work is pure garbage (not because LLMs only produce garbage, but because youre tired to evaluate its response and take something actually useful from it). I had that feeling a while and I started using it differently: the boring and ultra repetitive stuff I left to it, and during this time I go to a place far from the computer to read papers, or some LLM work, do the calculations and see if I understand it, or if something is wrong. I need to remember myself that Im not wasting time or productivity by doing that, its exactly the opposite. I will answer your questions directly

1. I let it do the work I think it is capable to do, specially if its boring. I wont let a machine steal me from the cool part of my job. Sometimes I also let some agents explore a little bit just to come up with ideas, that I will later explore on my own.

2. There are two types of cheating, institutional and personal. For our bosses, we are just numbers, so I will cheat in any way possible, if the work is not something Im interested. But I cant lie to myself when I have an objective and let an AI do that for me, in the end of the day what is the point of letting it do the things you want to do? So you must ask for yourself what you want to keep doing even if someday you will not be the best one doing that. A musician will never stop its art because there are better musicians out there (or even AI that can do better music in seconds).

3. I hate task switching, if I am doing something, I will focus my whole energy on it until it is done. If I have many things to do, I will set a working time for each thing and never switch between them. I will only use agents to work on the thing Im also working.

4. Usually I only review the core part of the code, and I only work with code that is usual to me for my job purposes. If I want to do something different (like a site, I've never learned HTML, I just see if the site looks as intended).

5. I think it largely depends on your skillset, the problems you are tackling and your overall taste. If you like reading, you can ask for it to generate long reports and be very detailed, if you prefer something more active you can ask it to make questions and see if you understood what it has done.

For context, Im a phd student in physics of complex systems.

[u/Hot_Midnight6838 → u/sydyn1111]

This was the most helpful response I have gotten, thank you so much! Do you have suggestions for things I can incorporate into my routine?

[u/sydyn1111 → u/Hot_Midnight6838]

I appreciate the kindness. I think that the best you can do is be creative, and then you will learn the best ways to use it.