Unverified50% confidenceOpinionExact time
Agents rarely fail at the code level; they fail at runtime.
1
Sources
50%
Confidence
Long-term
Relevance
10/29/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedTraditional software engineering debugging methods (breakpoints, step-by-step execution, log output) fail in multi-agent systems because agent behavior is probabilistic rather than deterministic.72% similarUnverifiedCoding agents rarely proactively seek out every caller when modifying a function unless explicitly instructed to do so.72% similarUnverifiedEven if all API calls succeed, an agent may produce no valuable output, so the entire run must be observed rather than just the success or failure of individual calls.70% similarVerifiedBugs in AI products are often not crash errors but outputs that appear reasonable yet are actually incorrect—so-called silent failures—which are harder to catch and more destructive.70% similarUnverifiedReasons for agent task failure may include prompt defects, execution framework limitations, random fluctuations, and judge model noise; not all failures stem from the prompt itself.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1113035API
curl https://kongchang.com/api/v1/knowledge/claims/1113035MCP
get_claim(id=1113035)