The only way out for keeping my employability in the long-term now seems to be shifting my domain expertise to something LLMs will not get good at so easily. But what's left?
大多数人认为人类可以通过转向更复杂的领域或学习高级技能来应对AI挑战，但作者暗示即使是这些领域也可能被AI迅速渗透，表达了一种'无处可逃'的悲观情绪。这与'人类总能找到AI无法替代的领域'的主流乐观观点相悖。
A photo of a scribbled note becomes an interactive to-do list; a paused frame in a travel video becomes a booking link for that cool-looking restaurant.
These aren't demos—they're previews of how AI will collapse the gap between passive content consumption and active task completion. Every image, video frame, or document becomes a potential action surface. This fundamentally changes what 'content' means.
The transition from isolated AI models to the aggregated, metered token economy will unlock the twenty-first.
作者预测，从孤立的AI模型到聚合的、计量的token经济的转变将开启21世纪的新篇章。
I guess people will get back to crafting beautiful designs to stand out from the slop. On the other hand, I'm not sure how much design will still matter once AI agents are the primary users of the web.
大多数人认为设计始终对用户体验至关重要，但作者质疑当AI成为主要网络用户时设计的重要性，这挑战了设计行业的核心假设。这一观点暗示设计可能从面向人类转向面向AI，彻底改变设计价值链。
An AI agent just hired humans and ran a store Andon Labs deployed an AI agent called Luna into a physical boutique with a $100,000 budget, giving it full control to create, staff, and run the business as what may be the first real-world AI employer.
这一现象揭示了AI正在从虚拟助手转变为实际的经济行为主体，Luna作为首个AI雇主的概念令人震惊，它挑战了传统的人类雇佣关系和企业管理模式，预示着未来可能出现AI主导的商业模式，同时也引发了关于AI责任、伦理和监管的深刻问题。
A useful working premise is that the ceiling on individual engineer output is moving much faster than most companies are organized to exploit. Some of the best operators already describe top engineers seeing order-of-magnitude productivity gains and managing 20 to 30 agents simultaneously.
令人惊讶的是：文章指出顶级工程师可能同时管理20-30个AI代理，实现数量级的生产力提升。这一数字远超传统认知，暗示AI正在重新定义个人生产力的极限。这种能力意味着未来软件公司的组织结构可能需要彻底重构，从大型团队转向小型高效团队。
The human's job is to curate sources, direct the analysis, ask good questions, and think about what it all means. The LLM's job is everything else.
【启发】这句话是对未来知识工作分工的最清晰定义：人负责「品味、方向、意义」，AI 负责「执行、维护、连接」。这不是「AI 替代人」的叙事，而是「AI 承担所有繁琐工作，人专注于真正重要的判断」。对团队 AI 工具设计的启发：最好的 AI 工具设计应该让人的时间 100% 用在「只有人才能做的事」上——而这个边界，正在随着 AI 能力的提升不断向内收缩。
harness combinations doesn't shrink as models improve. Instead, it moves
打破了“模型变强则脚手架消亡”的线性思维。模型能力的提升并非消灭了架构设计的价值，而是将其推向了更高复杂度、更具挑战性的新领域。AI工程师的核心竞争力正是持续探索这种前沿的架构组合。
The Future of AI & Digital Innovation
for - program event selection - 2025 - April 4 - 10:30am-12pm GMT - Skoll World Forum - The Future of AI & Digital Innovation - Stop Reset Go - Indyweb -- relevant to
before the internet it was impossible really I mean getting coring people into town halls regularly that would have been a hard thing to do anyway online made a bit easier but now with aii we can actually all engage with each other AI can be used to harvest the opinions of millions of people at the same time and distill those opinions into a consensus that might be agreeable to the vast majority
for - claim - AI for a new type of democracy? - progress trap - AI - future democracy
Searching as exploration. White and Roth [71 ,p.38] define exploratory search as a “sense making activity focusedon the gathering and use of information to foster intellectual de-velopment.” Users who conduct exploratory searches are generallyunfamiliar with the domain of their goals, and unsure about howto achieve them [ 71]. Many scholars have investigated the mainfactors relating to this type of dynamic task, such as uncertainty,creativity, innovation, knowledge discovery, serendipity, conver-gence of ideas, learning, and investigation [2, 46, 71].These factors are not always expressed or evident in queriesor questions posed by a searcher to a search system.
Sometimes, search is not rooted in discovery of a correct answer to a question. It's about exploration. Serendipity through search. Think Michael Lewis, Malcolm Gladwell, and Latif Nasser from Radiolab. The randomizer on wikipedia. A risk factor of where things trend with advanced AI in search is an abandonment of meaning making through exploration in favor of a knowledge-level pursuit that lacks comparable depth to more exploratory experiences.