How we solved Context Management in Agents — Sally-Ann Delucia
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AI Engineer
Author
AI Engineer
Date
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
subagent — A separate agent spawned by another to do one scoped piece of work in its own context, returning only the result.
Why it matters
If you're building agents that accumulate large context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → (like trace or log data), this walks through why naive truncation breaks reasoning and summarization cedes too much control, and offers a battle-tested pattern: head/tail preservation with a retrievable memory store plus subagentA separate agent spawned by another to do one scoped piece of work in its own context, returning only the result.Full definition → offloading.
Key quotes
“the best context strategy is one that lets your agents remember what it needs to um, and forget what it doesn't”
Sally-Ann Delucia
“context management isn't is a product and a UX problem, not just an engineering one”
Sally-Ann Delucia
“the main takeaway from this was that over truncation had broke the reasoning. It couldn't remember.”
Sally-Ann Delucia
“We were kind of hoping to get a little bit of a a secret from from them, but I guess we'll all just have to keep you know, doing our own research there.”
Sally-Ann Delucia
“agents don't fail because of prompts, they fail because of context”
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