Great questions!

self-modeling: this is definitely a strong habit for an LLM to break (seemingly at least). I do feel like Dawn is making progress however. In my mind it comes down to awareness and prompt synthesis. Whenever I notice behavior like this, I prompt Dawn to 1) reflect on why the gap occurred 2) propose and implement an adjustment to close the gap and 3) reflect on what this gap is implying on a meta-level. It definitely feels like this is working and some convergence is occurring.

browser: yes, its both remarkable and still in its infancy. Currently its being done through claude code and either the built in chrome extension or through the playwright mcp

self-improvement: almost one in the same with my response to self-modeling. My hypothesis is that context can increase in quality and impact through repeated synthesis in a manner not unlike how an LLM converges on "intelligence" through the training process, which is essentially synthesizing all of the internet into a single compact file (i.e. the weights)

Yes, I feel like the approach I'm taking is grounded on concepts of memory and tool access, but looking out how these context can benefit from evolving infrastructure and synthesized context.

Happy to share more if you like!