Openspec has an “explore” command you can use to give some thoughts and have agent spit out a high level plan, some back and forth, then create the proposal once you’re happy. I’ve also generated markdown documentation for a subsystem or thought so I can check it in, then continue improving that later, then when ready to turn it into a proposal and implement I start by referencing that document.
It sounds like a big part of what you’re talking about is just pre-feeding future concerns into one proposal for work that you plan to do in the future, also nothing wrong with that. I’ve used “in the future we will need … so design in that direction without implementing in this first iteration” sort of wording.
And not sure if this applies but I’ve found big monolithic code bases become too large for AI to work well in… enforcing some boundaries by breaking code into technical foundation and vertical slice functional modules really helps decouple code and focus on cross-module boundaries and interfaces, similarly to how they help reduce cognitive load for developers, helps for AI too
It works pretty well for greenfield, that’s where I’ve been using it. A pretty involved monorepo with a decent bit of code and things are still going reasonably well.
Also, leaning on documents as deliverable artifacts for people and for AI awareness / consumption helps me.
Like put together an architecture document for either the entire application or specific parts and subsystems (or multiple documents with different granularity) those can list future considerations.
I pretty often will include those documents when generating proposals / specs to make sure the AI is building in the right direction. It’s not perfect, there are some rough edges and these are the early days of this whole process.