I have been working on a new service from scratch and AI has spat out 1000s of LOC and while I leveraged on it quite a bit for the design of the service, I need to know exactly what is happening in every single line of code. This has increasingly become a problem for me, especially when working on something new from scratch, is there any plugin, skill, prompt that makes it easier to understand a codebase in-depth?
I think a lot of folks ended up in a world where you write specs and designs in Markdown documents and use that to drive the outcome (the code, the system, tests, etc). So you drive intend through those specifications and design docs.
Lately though, I've switched tact a bit and have resurrected some ~20yr old research called Behaviour Tree Engineering or Behaviour Trees, so I'm now writing specifications called BT specs.
For tools and architecture,I design data structures and let the LLM write the code, in small steps. Lots of discussion with the LLM. What Cory Doctorow calls centaur mode - a human mind augmented with a more powerful body. Applies to side projects and $DAYJOB.
For applications, I rewrote a framework of mine that I used 2003-2009. It is highly constrained so the LLM has few options to improvise. I can just tell it what features to add and it adds them without much in the way of slop. I still find code repetition which I just tell it to clean up.
ponytail plugin is good for reducing amount of code. i have a different ai that code reviews it and i tell it that it is smarter than the ai that wrote the code. i had to tweak it to not be too nitty.
I think a lot of folks ended up in a world where you write specs and designs in Markdown documents and use that to drive the outcome (the code, the system, tests, etc). So you drive intend through those specifications and design docs.
Lately though, I've switched tact a bit and have resurrected some ~20yr old research called Behaviour Tree Engineering or Behaviour Trees, so I'm now writing specifications called BT specs.
e.g: https://bte.mills.io/s/v4Mjbyf0OBJWm5YRLwG5XiIH
Two distinct strategies.
For tools and architecture,I design data structures and let the LLM write the code, in small steps. Lots of discussion with the LLM. What Cory Doctorow calls centaur mode - a human mind augmented with a more powerful body. Applies to side projects and $DAYJOB.
For applications, I rewrote a framework of mine that I used 2003-2009. It is highly constrained so the LLM has few options to improvise. I can just tell it what features to add and it adds them without much in the way of slop. I still find code repetition which I just tell it to clean up.
ponytail plugin is good for reducing amount of code. i have a different ai that code reviews it and i tell it that it is smarter than the ai that wrote the code. i had to tweak it to not be too nitty.