Lesson 1616 of 2116
AI agents and memory eviction policies
Decide what an agent forgets so context windows stay useful.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2memory
- 3eviction
- 4context
Concept cluster
Terms to connect while reading
Section 1
The premise
Unbounded agent memory poisons future runs; eviction is a real product decision.
What AI does well here
- Implement TTL and relevance-scored eviction
- Surface what was evicted so behavior is debuggable
What AI cannot do
- Decide what users expect the agent to remember
- Define the privacy boundary
Understanding "AI agents and memory eviction policies" in practice: AI agents can take actions, run loops, and call tools — giving one instruction can start a chain of automated steps. Decide what an agent forgets so context windows stay useful — and knowing how to apply this gives you a concrete advantage.
- Apply memory in your agentic workflow to get better results
- Apply eviction in your agentic workflow to get better results
- Apply context in your agentic workflow to get better results
- 1Design an agent spec: goal, tools, permissions, stop condition
- 2Run a simple web-search agent in a sandbox environment
- 3Instrument an existing workflow to identify where an agent could save time
End-of-lesson quiz
Check what stuck
15 questions · Score saves to your progress.
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