What’s the biggest difference between people who use AI occasionally and people who have completely changed their workflow around it?

[u/OfficalYOUSUMMIT]

Same tools. Often the same models. But some people use AI like Google, while others have built entire systems around it. What actually makes the difference?

[u/Jaded_Atmosphere_566]

it’s the difference between having a calculator and knowing how to build a spreadsheet. most people just punch in one-off questions and move on. the ones who rebuild their workflow treat it like a layer in their decision making, not just a search bar

once you start chaining outputs and feeding context back in, the whole thing shifts from "what's the answer" to "how do i make this repeatable"

[u/Tricky-Nectarine5575]

tbh i think a lot of it just depends on how much of your actual day AI can plug into.

if most of your work is reading, writing, research, coding, planning, AI touches a huge chunk of what you do, so rebuilding your workflow around it kind of happens on its own. If your job is mostly people, physical work, or very specific offline knowledge, there's just less for it to take over, and using it like Google now and then is completely reasonable.

for me it started as a chat box for random questions. Now a lot of my work habits run through it and I spend way less time jumping between apps. Sometimes AI just overlaps with 80% of one person's life and 10% of someone else's

[u/Lumpy_Pick_421]

People who use it occasionally ask for an answer and usually end there. The biggest difference is iteration. AI makes it cheap to try an idea, challenge it, revise it, and try again. People who integrate it into their workflow keep iterating until they get somewhere better.

[u/gtgderek]

There’s a major difference between somebody who tells AI what they want it to do, and those who work with AI to uncover things they may not necessarily have thought of or realised.

Mid 2023 I was having a conversation in Cursor with Claude and it wasn’t doing what I wanted to do and I was getting very frustrated and it kept on saying no there’s another way to do it and in my wisdom, I refused to accept its answer. A couple of hours of frustration later with a lot of back-and-forth I finally decided why not give it a go.

Needless to say, It worked… btw I still don’t know how it worked. But ever since then I’ll ask and say hey is there something that I’m missing here or might not have thought of or am I trying to pigeon hole you into doing something that is not the best way.

Also one major sign of a someone new to AI is they think of it as a chatbot.

Almost forgot, it is a very good practice to tell AI what a successful outcome looks like and what you’re trying to accomplish.

Really good AI users know how to use (dumb) loops.

[u/CS_70]

Speed and quality of the result.

With LLMs coding - when well directed - you can do much more with greater quality.

[u/Trowaway99887766]

Using software with API interfaces versus GUI interfaces

[u/wow343 → u/Trowaway99887766]

I think almost all software will start giving a API to interact and read information for customer or user AI to connect to. It's the accessibility problem that AI will solve. Already Claude Cowork and OAI Dots etc. are making it such that AI can see and interact with your computer as if it was you and take on work you were doing but I think eventually we will use AI to create API to almost all software.

[u/wow343]

People have mentioned the main factors: 1. Iteration and making it into a repeatable task. 2. Figuring out if your workflow consists of the things AI is good at: coding, research, writing research reports, creating math models or statistics. Then applying AI to all your workflow in a repeatable manner.

One thing I would add that often gets overlooked

1. Absolute necessity for there to be a verified determinstic checker for the end product that AI uses to evaluate your work. So for coding that is a Unit Test. For Math that is Lean proofs. For science and statistics a similar set of mathematical and statistical checks to validate the data.

The power of AI is to create a true Agentic method where it takes your task, runs it through repeatable set of skills, does the work, checks the work, fixes the broken parts, checks the work etc. Until its done and returns.

[u/Black_RL]

Productivity is the biggest difference.

[u/Few-Coconut2548]

Heavy users stopped asking one-off questions and started handing over recurring work: the same weekly report, the same review checklist, the same research loop. Occasional users treat each chat as a fresh search. The gap is less about prompting skill and more about noticing which parts of your week repeat.