Having somewhat accidentally also discovered this pattern, I do recommend figuring out some kind of compaction/deprecation method, potentially history-preserving, potentially just letting the git commit messages themselves serve as the canonical history.

The biggest problem I encountered using a similar setup for doing long-term and iterative data analysis is error propagation. My team and I are characterizing and modelling a physical system, there are real-world experiments that need to be run and then fed back into the analysis pipeline and then the next frontier of questions comes up. Any time there has been an erroneous analysis somewhere along the line, that error continues to be treated as a correct fact until it has been decisively eradicated. If one analysis script or document has the error written as a correct fact, that error will continue to pollute future analyses. Oh and these errors can also end up in the agents’ memory files as well. I have gotten very careful about making sure that every reference is corrected everywhere because it seems that the initial error is weighted heavier than the correction.