The Retry Pattern That Breaks Your Agent (And the One That Works)
This article discusses the flaws in the naive retry approach for agent frameworks and proposes a
Why it matters
The retry pattern is a critical part of agent architecture, and getting it right can make the difference between reliable and fragile agents.
Key Points
- 1Naive retry fails due to determinism in nondeterminism, error compounding, and lack of introspection
- 2The
- 3 pattern involves diagnosing the failure, modifying the approach, and retrying with new context
- 4Agents should focus on recovery rate, not just failure rate, to become more reliable
Details
The article explains that when an agent framework's model fails, the instinctive reaction is to simply retry the same prompt and inputs. However, this naive retry approach often fails systematically. The key issues are: 1) LLMs are stochastic but not random, so retrying the same context leads to similar failures; 2) each failed attempt adds more context that can bias the model toward the same failure modes; and 3) the model cannot fix what it does not understand without introspection. Instead, the author proposes a
No comments yet
Be the first to comment