Memory → Context Pipeline
Having a vector DB is not the same as the model seeing the right fact.
Warehouse vs the shopping basket you carry to the counter.
Visual Workflows
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Overview
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This turn
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Warehouse vs the shopping basket you carry to the counter.
Key Takeaways
- 1.Memory is the store. Context is the pack for this call. They are two jobs.
- 2.Retrieve, rank, budget, assemble. Do not retrieve the whole store.
- 3.Write-back happens after the turn, not by stuffing the window.
- 4.Working memory is the pack itself.
- 5.Having a vector DB is not the same as the model seeing the right fact.
Learn elsewhere
- →Agent Memory — Phase 5
Real Example
Scenario
Pipeline: pack only what this turn needs.
What you would do
In Context Engineering, apply Memory → Context Pipeline to this scenario: Pipeline: pack only what this turn needs. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.
Commands
Commands to Remember
Memory is the store. Context is the pack for this call. They are two jobsRetrieve, rank, budget, assemble. Do not retrieve the whole storeWrite-back happens after the turn, not by stuffing the windowWorking memory is the pack itself
Cheat Sheet
Quick recap
quick ref- •Pipeline
- •Budget
- •Don't dump
Common Mistakes
- ✕Skipping evaluation for Memory → Context Pipeline before production
- ✕No logging or tracing around memory context pipeline steps
- ✕Ignoring cost and latency implications