Unverified50% confidenceOpinionExact time
A new AI problem-solving paradigm is emerging: define an evaluation (eval), then perform hillclimbing optimization around it.
1
Sources
50%
Confidence
Long-term
Relevance
10/9/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedLiang Wenfeng understands AI development as a staircase: the previous stage was chain-of-thought, the current stage is Agents, and the next bottleneck is continuous learning.72% similarUnverifiedWhen the number of iteration rounds increases, AI may introduce new problems due to contextual misunderstanding, and basic troubleshooting capabilities are still required at that point.71% similarVerified在逆向工程中,AI提效的基础是人已经完成参数定位工作,AI放大已有能力而非凭空创造能力70% similarUnverifiedTesting found that first using AI to convert colloquial requirements into structured prompts before handing them to OK Computer for execution noticeably improves results.70% similarUnverifiedAt the current stage, AI competitive analysis tools are better suited as an augmentation layer for human analysts rather than a replacement.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/990942API
curl https://kongchang.com/api/v1/knowledge/claims/990942MCP
get_claim(id=990942)