> but it’s also a token fire lol.
I get much better results out of having Claude much much more task focused. I only want it to ever make the smallest possible change.
There seems to be a fair bit of research to back this up: https://medium.com/design-bootcamp/when-more-becomes-less-wh...
It's also may be why people seem to find "swarms" of agents so effective. You have one agent ingesting what you're describing. Then it delegates a task off to another agent with the minimal context to get the job done.
I would be super curious about the quality of output if you asked it to write out prompts for the days work, and then fed them in clean, one at a time.
I also find value in minimizing step width so that seems to track.
On this particular project, there are a lot of moving parts and we are, in many cases , not just green-fielding, we are making our own dirt… so it’s a very adaptive design process. Sometimes it’s possible, but often we cannot plan very far ahead so we keep things extremely modular.
We’ve had to design our own protocols for control planes and time synchronization so power consumption can be minimized for example, and in the process make it compatible with sensor swarm management. Then add connection limits imposed by the hardware, asymmetric communication requirements, and getting a swarm of systems to converge on sub millisecond synchronized data collection and delivery when sensors can reboot at any time…as you can imagine this involves a good bit of IRL experimentation because the hardware is also a factor (and we are also having to design and build that)
It’s very challenging but also rewarding. It’s amazing for a small team to be able to iterate this fast. In our last major project it was much, much slower and more tedious. The availability of AI has shifted the entire incentive structure of the development process.