AI产品缺乏可靠的可重复性与上下文透明机制
问题概述
用户普遍指出当前AI系统在可重复性、上下文管理和事实核查方面存在严重缺陷，导致工具使用不可预测、误导性语言泛滥。这些痛点包括对确定性输出的需求、对上下文透明可视化的缺失以及对事实错误的容忍。
痛点标签
- 缺乏可重复的、可审计的AI输出机制
- 上下文管理不透明、难以编辑或审查
- 缺乏可靠的事实核查功能
- 人格化输出导致误导
待验证问题
- 您是否愿意为此类功能（如可重复的AI输出、上下文可视化）支付费用？
- 您目前在使用AI工具时最常遇到的上下文管理问题是什么？
- 您对AI事实核查功能的可靠性有何期望？
证据
原话 · @Anonymous
I'm very thankful for the section on reproducibility. I argue this is the single biggest hangup for the entire space. You CAN have temperature and determinism. I've been waiting for six years for a major provider to offer it, there is demand, but I've slowly come to realize the current game theory does not support it.
原话 · @Anonymous
The thing about the "AI can make mistakes, so double-check responses" thing is the essence of our future hellhole — deterministic software replaced with AI and legal disclaimers.
原话 · @Anonymous
The scrollback that most agents show is not what the model is reading. Things get summarised, dropped, cached or never included at all, and the transcript carries on showing the original as though it were still there.
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