Beyond Recall: Compiling Experience into Executable Memory for LLM Agents

Long-horizon LLM agents must turn noisy, sparse-reward trajectories into reusable experience, yet complete trajectories retain incidental actions and summaries can omit execution conditions. We introduce Trace, which compiles executable Walk-through Memory with a fixed Actor: delayed credit identifies candidate preparation, cross-episode outcomes yield candidate prerequisites, and backward slicing links target facts to observed producers. Entry conditions, expected effects, and termination predicates support state-conditioned scheduling, monitoring, and resumption. Across WebShop, J-TTL, and ScienceWorld with three LLM backbones under episode resets, Trace outperforms eight baselines in AUC and Final-3. Relative gains over the strongest baseline in benchmark-averaged AUC and Final-3 average 30.9% and 41.6% across backbones. Ablations show complementary gains from dependency-grounded construction, executable representation, and prerequisite-aware scheduling.