Ask HN: How do you get into a flow state when using AI to code?

I think planning is a big part. ironically, this wasn't a part of my typical routine as an engineer before AI came around. Sure I thought through the work or ticket I was assigned but not always at as much of a birds eye view.

Nowadays with AI I try to start most tasks with a plan, review each phase/step, research parts I'm more unsure of, and try to refine it. Ironically it's more of a dev cycle like process anyway IMO.

What works for me is:

- Use a fast model like DeepSeek Flash V4 on high (it's Sonnet level, but fast and cheap).

- While the LLM is working, start writting your next prompt. A good prompt usually takes between 1 and 10 minutes to write anyway.

Doing this should keep you busy enough to never leave flow.

But it is intense and demanding when the LLM is fast, I'll tell you that.

I've actually embraced the asynchronous element of AI programming in my personal projects.

Playing Star Citizen? There's pockets of 5 minutes all over the place traveling from A to B. I keep my laptop nearby and have a prepared todo list of items to work through. Those moments wasted on Reddit are now moments wasted on feature experiments!

Waiting for a cup of tea? Run an experiment. Waiting on wife? Run an experiment.

Piece by piece an app is coming together built from 5 minute increments of reclaimed time.

While I don't have the answer, I will leave my thoughts here, maybe my comment helps you or some of the responses might...

I was thinking about this when I tried a faster model (Cursor released something fast about a month ago?). It was such a joy to use (well, at least compared to other models, where you wait 5-10 mins for even simpler tasks), and I noticed I felt much closer to the problems, and I got closer to a "flow" state... ...but unfortunately, the models are faster for a reason, and the output got worse. While I did enjoy my job more, I was also left worried that the model missed important things (and it did when cross referenced with other models or just doing the thinking myself).

IMO we need much faster yet capable models to bring back a bit of a flow state.

Another approach worth trying is to get some agents researching 4-5 tasks thoroughly in the background, discovering all the relevant details, collecting all the files likely to be edited, their content etc..., then work on one thing at a time with a better focus for yourself, maybe use a faster model.

One thing I try to do is code manually if I know that I can be faster and better. It's convenient to stick to one tool, the agents, when editing code, but for smaller clean up tasks, they just never get it right, and sometimes it's better to do 1 min manual work over 5 mins of explaining what you want and the agents still not delivering it...

I think "without being obtrusive" is a key point here, because any type of popups in the midst of working would break flow as well. Fixing compiler warnings is flow-inducing because it's very linear and has a fast feedback loop, so it would have to be something akin to that.

Side-note, I wonder if audio cues would work well here. When another person is commenting on something, we as humans can typically remember their point while still being focused on text, but if a popup with text comes up we usually get distracted by it. Just my two cents.