Unverified50% confidenceFactExact time
The core proposition of ADRs for AI is to produce a "deliberation record" from every collaboration with AI, containing the prompt, the AI's reasoning process (if obtainable), the human's choices and corrections, and the finally adopted solution, and to commit it to a Git repository.
1
Sources
50%
Confidence
Long-term
Relevance
10/26/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedProviding AI with the same level of granular requirement descriptions as would be given to a human programmer—including acceptance criteria, user stories, and detailed ticket structures—yields better AI performance77% similarVerifiedAI-automated topic selection systems should follow the division-of-labor principle that AI is responsible for filtering and recommending while the final decision-making authority rests with the creator.77% similarVerifiedThe platform adopts a design philosophy of AI generation with human editability, where AI handles the first draft and the final judgment and revision authority is handed over to testers.76% similarVerified目前被广泛认可的高效AI协作模式是'人类在环'（Human-in-the-Loop）：AI负责信息收集、初步分析和方案生成，人类负责问题定义、质量把关、价值判断和最终决策76% similarUnverifiedIn AI-assisted development scenarios, using ADRs to record why a solution was accepted, which alternatives were ruled out, and what the known limitations are can help rebuild the severed chain between output and understanding.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1098492API
curl https://kongchang.com/api/v1/knowledge/claims/1098492MCP
get_claim(id=1098492)