Alibaba treats agent context management as a programming problem
omarsar0 · x · 2026-08-25
Elvis Sarma highlights an Alibaba approach for long-running agent memory (bookmark-worthy). Core idea: treat agent context management as a programming task instead of rewriting memory schemas.
How it works:
- Each session is backed by an append-only event log plus a sandboxed persistent Python kernel
- Tool outputs, retrieved history, and derived state bind to typed variables across model calls rather than being serialized into the prompt each turn
- Model-written code searches and transforms that state; only explicitly printed projections enter the working view
- The event log keeps lossless ground truth, so nothing is committed to a compressed form prematurely
- When the working view nears budget, stale spans are evicted but remain recoverable via an eviction index of compact landmarks tied to exact events
Related event: Alibaba's Scroll Manages Long-Horizon Agent Context via Code(2 posts)→
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