Seriously and beyond productivity, flow state was what I liked most about the job. A cup of coffee and noise cancelling headphones and a 2 hour locked in session were when I felt most in love with programming.
That said I don't dispute the value of agents but I haven't really figured out what the right workflow is. I think the AI either needs to be really fast if it's going to help me with my main task, so that it doesn't mess up my state of flow/concentration, or it needs to be something I set and forget for long periods of time. For the latter maybe the "AIs submitting PRs" approach will ultimately be the right way to go but I have yet to come across an agent whose output doesn't require quite a lot of planning, back and forth, and code review. I'm still thinking in the long run the main enduring value may be that these LLMs are a "conversational UI" to something, not that they're going to be like little mini-employees.
Never used headphones - if the environment is too loud, make it quieter. I once moved into a new office area that had a dot-matrix printer that "logged", in the worst sense of the word (how could you find any access on such a giant printout), every door open/close in the block. It was beyond annoying (ever heard a DM printer? only thing worse is a daisy wheel) so I simply unplugged it, took out the ink ribbon and twisted off the print head. It was never replaced, because as is very often the case nobody ever used the "reports" it produced.
>if the environment is too loud, make it quieter.
we shifted to open office setups over the decades. There may not even be anyway to make things "quieter" externally.
But LLM prompting requires you to constantly engage with language processing to summarize and review the problem.
It helps that I don't outsource huge tasks to the LLM, because then I lose track of what's happening and what needs to be done. I just code the fun part, then ask the LLM to do the parts that I find boring (like updating all 2000 usages of a certain function I just changed).
To me, flow is a mental analogue to the physical experience of peak athletic output. E.g. when you are are at or near your maximum cardiovascular throughput and everything is going to training and plan. It's not a perfect dichotomy. After all, athletics also involve a lot of mental effort, and they have more metabolic side-effects. I've never heard of anybody hitting their lactate threshold from intense thinking...
My point is that the peak mental output could be applied to many different modes of thought, just as your cardiovascular capacity can be applied to many different sports activities. A lot of analogies I hear seem too narrow, like they only accept one thinking task as flow state.
I also don't think it is easy to describe flow in terms of attention or focus. I think one can be in a flow state with a task that involves breadth or depth of attention. But, I do suspect there is some kind of fixed sum aspect to it. Being at peak flow is a kind of prioritization and tradeoff, where irrelevant cognitive tasks get excluded to devote more resources to the main task.
A person flowing on a deep task may seem to have a blindness to things outside their narrow focus. But I think others can flow in a way that lets them juggle many things, but instead having a blindness to the depth of some issues. Sometimes, I think many contemporary tech debates, including experience of AI tech, are due to different dispositions on this spectrum...
My inner dialogue is always chatty; that doesn't stop when I enter a flow state. It just becomes far more laser focused and far less distracted. LLMs help to maintain the flow because I'm able to use it to automate anything I don't care about (e.g. config files) and troubleshoot with me quickly to keep the flow going.