When using Claude Code or Codex, that is all gone. Claude Code is extremely eager to reach the end goal to the point that it feels like a fever dream to write code with it. In the end, I have low confidence about edge cases and fit into the project's architectural and design goals.
On top of that, I enjoy programming, reverse engineering, etc. and I feel that the LLMs, while able to solve some problems or deliver some features, take that fun away. I'm trying really hard to find a workflow with them that I'm confident in, but I fear that workflow is just chat, search, and being a rubber duck for my thoughts.
working with AI forced me to write better specs but the way I write today is very different. I typically open Codex and have Linear MCP connected where my chat with the AI will end up writing the issue. Its a lot of back-end-forth where I tell what I want, the AI does all the code scanning, write something, I correct something, etc
The value for me is exactly that I tell what I want, the AI verify in the actual code if that's the path that makes more sense or not. In the end I have a pretty detailed spec that I'm much more confident is the correct path.
I find the spec easier to review than a huge PR so typically when executing is much faster and aligned with what I want.
The grill-me skill from Matt Pocock is great for this (https://github.com/mattpocock/skills/blob/main/skills/produc...)
This is exactly what I settled upon after my own trying really hard. It is liberating, I have no fear at all!
This isn’t a binary is/isn’t thing though. What if only 80% of my task is, how would I know that the other part isn’t, if I haven’t worked it through fully
What if my task is generally represented, but for my specific context, there are specific details that aren’t?
How would I know until I’ve reasoned through it myself? At that point having the LLM do the work doesn’t add much value