Raw LLM Responses

The concept of "agents in headphones" is the perfect way to describe the current state of most frameworks. We keep building these massive orchestrators, but if the agents can’t actually look at the same piece of paper (or filesystem) at the same time, the human ends up being the high-priced delivery driver moving context back and forth. The persistent identity and git-diffable memory in `.trinity/` is a smart move. It solves that "goldfish memory" problem where you spend the first 10 minutes of every session re-explaining the project architecture. Having the agents essentially "eat their own dogfood" by maintaining their own framework is the ultimate stress test. If the system can handle 400+ PRs of its own evolution, it's definitely past the toy project phase. I’ve hit a similar wall with the "babysitting" aspect of dev-tools. You want to trigger a process and walk away, but you usually end up staring at the terminal just in case. I actually started using Runable for my project landing pages and technical documentation for this exact reason it automates the professional presentation layer so I don't have to manually bridge the gap between my raw code and how the world sees it. It’s that same philosophy of removing the "human glue" from the workflow so you can actually scale your output. That `watchdog` addition is huge for trust. Once you stop checking the terminal every 30 seconds to see if an agent crashed, you’ve officially moved from "tinkering" to "engineering." Great work on hitting PyPI!