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Agent Memory
Tier 3

MemoryLens

View on GitHub Fetched 2026-07-02 1 related flow

Summary

Observability and debugging for AI agent memory: instruments the memory pipeline (write, read, compress, update) to show exactly why an agent 'forgot' something. pip-installable with framework integrations.

Key Takeaways

  • Instrument the memory pipeline like any other production system
  • 'Why did it forget' becomes answerable with write/read traces
  • Memory observability pairs naturally with run observability

Reliability Note

Open-source tool; concept applies to any memory stack.

Flows informed by this source

1
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Harness Engineering

Observability for Agent Runs

Instrument your agent like production software: traces, session replay, cost tracking, and failure analysis on open standards.

01Instrument spans across the loop
02Build session replay
03Track the economics

+1 more steps to Done

Best forbuilders who have shipped a basic app before

4 steps90-120 minutesIntermediate

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