One of the use cases i see for this tool is helping companies to understand the output coming from the llm blackbox and the process which the employee took to complete a certain task
Except it doesn't capture the majority of uses of AI, in my experience. In my current practice, the the vast majority of AI use is autocompletions, or small inline prompts. ("Fix this error."; "Open an ALSA midi connection" (things that avoid a to trip into awful documentation); "if (one of the query parameters is "gear='ir') ..." (things that break flow by forcing a trip into excellent but overly verbose Javascript URL API documentation)). Only very occasionally will I prompt for a big chunk of code.
Claude Sonnet 4.6. With some brief experimentation with Gemini 3 Pro and GPT 5.3 Codex (both of which seem excellent so far). Perversely, I'm more comfortable at the moment with Claude Sonnet 4.6, just because I have a ballpark sense of how far it can be pushed before it loses it, and haven't yet developed the corresponding bat-sense for Gemini 3 Pro and GPT 5.3 Codex.