this is a pretty important piece and the research backs you up. Moving that context out of your system prompt dynamically is going to help reduce your lost in the middle effect. Context rots almost immediately. I've got a project that is being built to address this directly as well, but I'm still very early days.
Keep it up! you're on the right track.
Hong, K., & Chroma Research Team. (2025). Context rot: How increasing input tokens impacts LLM performance. Chroma Research. https://research.trychroma.com/context-rot
Liu, N. F., Lin, K., Hewitt, J., Paranjape, A., Bevilacqua, M., Petroni, F., & Liang, P. (2024). Lost in the middle: How language models use long contexts. Transactions of the Association for Computational Linguistics, 12, 157–173. https://doi.org/10.1162/tacl_a_00638
Keep it up! you're on the right track.
Hong, K., & Chroma Research Team. (2025). Context rot: How increasing input tokens impacts LLM performance. Chroma Research. https://research.trychroma.com/context-rot
Liu, N. F., Lin, K., Hewitt, J., Paranjape, A., Bevilacqua, M., Petroni, F., & Liang, P. (2024). Lost in the middle: How language models use long contexts. Transactions of the Association for Computational Linguistics, 12, 157–173. https://doi.org/10.1162/tacl_a_00638