The products currently on the marketplace have architectures that are far more sophisticated than just an LLM. Even something as simple as “Deep Research,” which both Anthropic and Claude have available, is using multiple interconnected systems to provide a single response.

Consider Agentic AI, like Claude Code, where they’re using tools, analyzing the results of those tools, iterating, possibly calling out to MCP servers to do other things, etc… The tools allow them to do things like read or modify files in the working directory, execute programs (i.e., your linter, installing dependencies, running your app), querying against your app itself, and so on.

And of course note that the single “Claude” box in that diagram has an architecture that’s more sophisticated than just being an LLM. At minimum, consumer facing LLMs generally have a supervisor that censors problematic inputs and outputs; this doesn’t make the system more competent but the same concept can be applied to any other sort of transparent wrapper.

It seems to me that we already have consumer systems that are doing what you described, and we’re already working on enhancing their architectures further.