Design Context and Memory for a Long-Running Agent System Design Interview

1. Problem Statement

2. Architecture Discussion Map

Use this as one discussion aid, not a single correct answer. Your design should follow from the requirements, scale, and trade-offs you establish.

graph LR
    A["Design Context and Memory for a Long-Running Agent"]
    A --> F1["Memory tiers and source-of-truth model"]
    A --> F2["Context selection, compaction, and eviction"]
    A --> F3["Retrieval indexing, freshness, and provenance"]
    A --> F4["Concurrent updates and consistency"]
    A --> F5["Quality, privacy, cost, and long-horizon evaluation"]

3. Key Focus Areas

• 1
  Memory tiers and source-of-truth model
• 2
  Context selection, compaction, and eviction
• 3
  Retrieval indexing, freshness, and provenance
• 4
  Concurrent updates and consistency
• 5
  Quality, privacy, cost, and long-horizon evaluation

4. What Strong Candidates Should Demonstrate

• ✓Treat context as a finite attention budget rather than an append-only log.
• ✓Separate working state, episodic memory, semantic memory, and source-of-truth artifacts.
• ✓Measure whether compaction and retrieval preserve task-critical facts.

Evaluation Guide

This is an evaluation framework, not a single model answer. Strong designs may make different choices when their assumptions and trade-offs are explicit.