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告别繁琐，拥抱高效：捣鼓了 1 年半，基于 Fluter 的跨平台 AI SSH/Local 命令行终端 Gm. 没有只涨不跌的市场， 市场总有回调时。 但确实存在只跌不涨的市场 跌90%之后， 还能再来一个腰斩。 所以， 我们定投美股的态度应该是： 以买到“跌90%后还能再腰斩的山寨币”那种心态去参与。 AI & 美股， 至少未来五年，依然是主线之一。 慌什么？怕什么？ 要是你相信龙国会全面崛起、全面冲击， 那就去定投A股好了。 我就不定投大A了。 —————————————— 我那刚退伍没多久的战友， 都在问我能不能在今年买到4.5W的BTC了， 我就... ... A job-seeker asks whether to pursue an IT career amid scarce junior vacancies. They are learning Flutter and already know Provider, Firebase (Auth, Firestore), and Clean Architecture; they plan to study Rive
Cross-platform AI tooling built with Flutter signals opportunities for UI-centric AI developer tools and terminals. Tech professionals should note demand for Flutter skills in hybrid desktop/mobile AI apps and implications for developer workflows.
Dossier last updated: 2026-05-19 02:36:37
告别繁琐，拥抱高效：捣鼓了 1 年半，基于 Fluter 的跨平台 AI SSH/Local 命令行终端
Gm. 没有只涨不跌的市场， 市场总有回调时。 但确实存在只跌不涨的市场 跌90%之后， 还能再来一个腰斩。 所以， 我们定投美股的态度应该是： 以买到“跌90%后还能再腰斩的山寨币”那种心态去参与。 AI & 美股， 至少未来五年，依然是主线之一。 慌什么？怕什么？ 要是你相信龙国会全面崛起、全面冲击， 那就去定投A股好了。 我就不定投大A了。 —————————————— 我那刚退伍没多久的战友， 都在问我能不能在今年买到4.5W的BTC了， 我就... ...
A job-seeker asks whether to pursue an IT career amid scarce junior vacancies. They are learning Flutter and already know Provider, Firebase (Auth, Firestore), and Clean Architecture; they plan to study Riverpod next. The writer worries that applications are ignored despite these skills and wonders if switching to a sysadmin role would be more practical. This matters because early-career hiring frictions shape career paths in software and influence skill choices (mobile frameworks, state management, cloud backend). The situation highlights common junior challenges: signaling competence, portfolio building, networking, and aligning learning with market demand.
Meta’s rapid pivot to AI-first priorities is reportedly harming employee morale as engineers and product teams face intensified performance pressures, reorganization, and layoffs. Staff describe rushed projects, shifting roadmaps toward generative AI and large models, increased surveillance and metrics, and a sense that human-centered product work is devalued. Managers and HR are wrestling with burnout and retention as the culture moves to prioritize speed and model-driven features over long-term user-experience investments. The shift matters because Meta’s ability to execute AI products depends on talent retention and healthy engineering practices; continued turmoil could slow product quality and affect competitive positioning in AI-driven social and advertising products.