I have been developing headaches and brain fog when working with Claude lately - and it’s actually due to an improvement: It can now work for long stretches without me.
Working with recent frontier models with subagent heavy “workflows” enabled feels less like a chat and more like email:
Long complicated instructions in … wait … long complicated result out.
Obviously I don’t sit there waiting for the agents to finish, but I pick up another todo in a new tab. The more complex the tasks I work on, the longer the waiting time, the more tasks I end up multitasking on.
I end up waiting for one of the 4-5 Claude instances I have working simultaneously to finish.
This is mentally taxing because it forces me to continuously have to task switch, and the outputs I have to verify tend to be more complex.
Increasing the model’s output quality by having it work on the problems for longer made the interaction asynchronous in nature.
Depending on the type of task this type of async interaction is either exactly what I want, or counterproductive.
I split the tasks I have to work on in two categories:
- Tasks where I know what good output looks like
- Tasks where I have to figure out what good output looks like
If the desired output is already known, and it’s easily verifiable, I want to delegate the task to the model to disappear for an hour and report back to me when it’s done.
But for all other tasks, tasks where I am actively building an understanding of what it is that I want to build , I actually want a conversational interaction with speed that is as close to realtime as possible. That way I can stay focussed on working on one thing at a time.
So there are essentially two modes I need:
- One “ thinking partner ” interactive mode where responses are as fast as possible, with sufficient output quality to augment my ability to research and implement while staying inside the same thread of thought
- One “ fire and forget ” delegation mode that finishes tasks for me that I can easily verify with little to no effort (currently either Claude / Codex)
The thinking partner is used to build an understanding, and this is arguably the most important part. LLMs make it trivial to create huge amounts of “volume”, the quality is more than ever the distinguishing feature.
The only way to output better quality work than other people using the same models is to augment the model in some area it’s lacking, so it’s necessary to understand the problem as deeply as possible.
I experimented with different models and currently use Cursor’s Composer 2.5 model for these types of interactive tasks, which is incredibly fast.
I analyzed the average response time from the last couple of days and it was around 25 seconds. My average Claude session (with subagents) is about 80 seconds, up to an average of 6 minutes in sessions with subagents.
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