MemoryLake
Engineering & Developerreproducing agent bugs through memory replay

Reproduce Production Agent Bugs Locally by Replaying the Exact Memory State

Production agent bugs are notoriously hard to reproduce locally. The memory state at the moment of the bug is gone by the time you investigate. MemoryLake's memory replay pins memory to the exact state when the bug fired — so local reproduction becomes possible.

Day 1“Production agent bugs are notoriously hard to reproduce”“locally.”✓ Got it, I will remember.Day 7 — new session“Same task again — can you keep the context?”× Sure — what was the context again?(forgot every detail you taught it)+ MEMORYLAKE LAYERMemory auto-loadedPin memory to a specific commitReplay toolingMemory diff between attemptsSESSION OUTPUT✓ Same prompt, on-brand answerNo re-briefing required.

Reproduce Production Agent Bugs Locally by Replaying the Exact Memory State

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The problem: agent bugs don't reproduce without the original memory

A customer reported a bug. You try to reproduce. The agent does something different because the memory is different now. The bug stays open because you can't get back to the state where it fired.

How MemoryLake makes agent bugs reproducible

Pin memory to a specific commit

Pin memory to a specific commit

Restore memory to the exact state at the bug's timestamp.

MEMORYReplay tooling

Replay tooling

Run the agent against frozen memory snapshots.

MEMORYMemory diff between attempts

Memory diff between attempts

See what changed between production and local environment.

Audit trail per replay

Audit trail per replay

Distinguish replays from production runs.

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How it works for reproducible bug debugging

  1. Connect — Memory commits happen automatically per write.
  2. Structure — Each commit timestamped and queryable.
  3. Reuse — Pin local agent to bug-time commit; reproduce bug.

Before vs. after: agent bug reproduction

DIY memoryMemoryLake
Reproduce bug from yesterdayOften impossiblePin to commit
Reproduce bug from 6 months agoImpossiblePin to commit
Local vs prod memory parityCustom syncSnapshot restore
Audit replay attemptsLimitedBuilt in

Who this is for

Engineering teams running production agents where customer bug reports go unreproduced because memory state has moved on by the time investigation starts.

Runnable demoabout 5 minutes

Try this use case on your own account

A fictional printer maker's support agent keeps one memory per customer account. On October 3 it shipped a replacement to an office that had closed the day before. Today an engineer picks up the ticket, and asking the agent again proves nothing: the complaint chat and a manual fix have changed its memory since. The agent's tool call and the facts it got back were stored in the conversation as TOOL_USE / TOOL_RESULT blocks. The same call re-run today gives a different address. Then fact trace and conv fact-actions rebuild the memory as it was at that exact message, dating every change by the message it came from. Every fact the agent saw comes back word for word, and a then-vs-now diff shows the source of each change.

What you will see

  • The agent's memory_search call and the fact ids it returned, stored as TOOL_USE / TOOL_RESULT blocks
  • The same tool call re-run today: Lyon then, Grenoble now. The bug does not reproduce by asking again
  • fact trace (ADD / UPDATE / FORGET) and conv fact-actions pin memory to the message: 6/6 facts identical to the record
  • A diff with a conversation, message and cookrun (or MANUAL) on every line, an audit record, and a local web UI

You need: a MemoryLake API key · the memorylake CLI · Python 3.9+

Run it

git clone https://github.com/memorylake-ai/memorylake-usecases.git
cd memorylake-usecases/agent-bug-replay
export MEMORYLAKE_API_KEY=sk-…
python3 demo.py          # or: python3 web/server.py
Open on GitHubRead the walkthrough

Watch it run · real, unedited recordings

CLI demo6:24Web demo6:25

Related use cases

Engineering & DeveloperMemory Replay for Reproducible Agent RunsReproducing agent behavior requires reproducing the memory state. MemoryLake provides memory replay for deterministic agent runs. Free to get started.
Engineering & DeveloperMemory Time-Travel for Agent DebuggingDebugging agents requires seeing memory at the time of the bug. MemoryLake provides time-travel queries on memory history. Free to get started.
Engineering & DeveloperMemory Snapshotting for Agent TestingTesting agents requires controllable memory state. MemoryLake provides memory snapshots agents can be tested against. Free to get started.
Engineering & DeveloperMemory for Agents That Need Deterministic ReplayDeterministic agent replay requires identical memory state. MemoryLake's commit history enables true deterministic replay. Free to get started.

Frequently asked questions

Retention for replay?

Configurable; default keeps full delta-encoded history.

Privacy for cross-environment replay?

Per-user scopes preserved; audit trail per replay access.

Self-host?

Yes — enterprise tier deploys in your VPC.

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