My automated doubt development process

This process originated out of a lack of trust. I lost trust early in my AI-assisted development due to allowing our LLM partners to do too much, too quickly and without the standard engineering practices I had come to internalize. Trust was regained by automating as much doubt as I could muster. What does performing doubt look like? Critiquing the implementation of an artifact and doing so, repeatedly. If you are using AI to write code, specs, docs or any artifact, you may find this piece useful.

I use subagents, quite a bit. They inhabit the fulcrum of the entire process. They are specialized in ways that audit perspectival surfaces a standard instantiation of Claude wouldn't necessarily cover. The core idea in all of this is automated doubt from multiple perspectives and the front-loading of scrutiny. The more parallax coverage in AI development, the better; where different vantage points catch different defects, the way two eyes give you depth. The development process goes something like this:

It starts with an idea or a feature I'd like to build and a specification. Like any good development practice, it's usually wise to start with a spec, PRD, plan, or whatever flavor of design preferred. I ask Claude to write the spec and I spend 2–5 minutes skimming the file to verify the core implementation aspects of the idea are captured. This is where the iteration process begins.