Unverified50% confidenceOpinionExact time
The stability of a skill relies not on the AI being smart on its own, but on the fallback mechanisms designed by the developer.
1
Sources
50%
Confidence
Long-term
Relevance
9/20/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedSystems architecture capability is difficult for AI to replace because it requires developers to make trade-offs under uncertainty: balancing performance against cost, weighing consistency against availability, and navigating the tension between technical debt and delivery speed74% similarUnverifiedAndrew Ng believes the biggest difference between excellent agentic developers and less effective ones lies in whether they can drive a disciplined development process, rather than their familiarity with models or frameworks.74% similarVerifiedInstrumental convergence theory holds that regardless of an AI's final goal, sub-goals such as self-preservation, goal integrity, cognitive enhancement, and resource acquisition will naturally emerge under sufficiently intelligent optimization without needing to be programmed.74% similarUnverified工作流的核心价值是解决稳定性，将不确定的任务变成可重复的SOP；智能体的核心价值是解决主动性73% similarUnverifiedPre-installed software does not in itself equal active usage; the key to retaining users lies in the agent's practicality and stability in real work scenarios.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/936221API
curl https://kongchang.com/api/v1/knowledge/claims/936221MCP
get_claim(id=936221)