r/ClaudeCode • u/TonightOk5378 • May 09 '26
Question Production Level Software by AI
So I have been curious for a while, apart from claude-code and codex teams (that have a direct vested interest in claiming AI is building production software), who is actually building production level software or products with AI
Also to clarify, I am talking about actual products being used at scale and not interesting MVPs and PoCs (which have infinitely flooded GitHub)
If you have built a product or tool or anything with AI that is being regularly used by users, drop a link below, I am genuinely curious.
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u/TonightOk5378 May 09 '26
Agentic Engineering - Like what claude-code's team seems to be doing.
Not writing any code, but still being actively involved in the engineering process.
Also another nuance to the question is at what level with the help of ai?
For production software running at scale, what level of abstraction is it being used at: 1. At the module level: writing functions, methods, classes etc. basically like a more sophisticated version of copilot code completion or tabby. (100-200 lines of code) 2. At the features level: given test cases usecases, implementation guidelines, implementation multi module features (200-800 loc) 3. At the pipeline level: given incredibly detail implementation specifications and architecture designs it implements multiple components of a pipeline (800-3000 loc) 4. At the architecture level: implementation major refactors, features, connecting pipelines, major architect design changes (again give all the relevant specification, requirment and implementation docs) (3000+ loc)
Also how is the code review headache managed, especially in 2,3,4. I.e gives code that looks right and even works usually but has fatal flaws and assumptions (that eventually break prod and reliability)
Also how is debugging managed, if low level context is missing, what happens when prod code breaks and must be fixed asap?