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WriteRewrite for Native EN Tweets
Convert short text in ANY language (Chinese, English, Japanese, etc. — ≤200 chars) into 2-3 native-sounding English variants for X/Twitter, using authentic casual phrasing and current Gen Z slang (without being flippant), each followed by a brief glossary of slang used. This means you can refine your own expression while learning the most current English trends—slang, colloquialisms, and other things they don't teach you in textbooks—straight from the English-speaking world.
ImageOpenAI-style promotional poster
Generate highly polished posters and visual covers suitable for launches, promotions, covers, and SaaS Hero use, based on your product, event, or collaboration theme. Supports 8 styles including soft-focus color fields, realistic materials, natural scenes, warm color dynamics, fruit macro, and high-speed beams, and retains uploaded logos, screenshots, and precise copy, lowering the design threshold from idea to finished product.
VideoVox-style historical material generator
Want to create engaging Vox-style content for historical educational short videos? The "Vox-Style Historical Video Generator" can transform any historical theme (such as people, events, dynasties, reforms, wars, or systems) into a complete set of short video production materials. You only need to provide a historical theme, and it will generate a 45-second explanatory script of approximately 270 words, along with 9 vertical 9:16 paper-cut collage-style storyboard prompts. The unique feature of this skill is that it not only provides image prompts but also precisely matches 9 Seedance 2.0 image-based video prompts to each storyboard. This means you can easily create historical explanatory short films with "paper-cut collage" and "stop-motion animation" visual effects. Whether it's creating historical educational animations, designing historical theme storyboards, or creating paper-cut collage keyframes for dynasties, reforms, wars, or historical figures, it provides a one-stop solution. With concise, conversational text and rich visual elements such as maps, coins, stamps, and silhouettes, this tool ensures your videos are both informative and engaging. The generated prompts strictly adhere to the principle of "one-to-one correspondence between video actions and visual elements," ensuring smooth and natural video effects and preventing a disconnect between visual elements and animation. Make your historical short videos more visually impactful and content-driven.
LearnOffer Toolkit
A job search system with 10 years of experience from a major Silicon Valley company, encapsulating real recruitment insights and job search methodologies into AI. Offer Toolkit | AI Job Search Assistant breaks down the entire job search process from "discovering your dream job" to "securing an offer" into three intelligent modules: ① JD Decoder: Deeply analyzes job descriptions and generates a personalized Offer Strategy Report: assesses job suitability, core competencies and skill gaps, and predicts key interview questions and high-probability questions. ② Resume Builder: Transforms your experience from "job description" into "impact stories recognized by recruiters": automatically structures personal experience, optimizes project expression and quantifies achievements, generates ATS (Advanced Skills Test), provides user-friendly, high-quality resumes, and supports 11+ printable professional templates. ③ Behavioral Story Library: Unearths your real experiences and creates reusable interview story assets: extracts key projects and growth experiences, automatically converts them into a STAR Framework, builds a personal Behavioral Interview Story Bank, and efficiently handles "Tell me about a time..." type questions. Whether you're struggling with "should I apply for this job," want to "optimize my resume," need to "analyze the JD," or are preparing for the next behavioral interview... Interview and Offer Toolkit automatically identify requirements and route them to the most suitable AI module. Keywords: Job search | Offer | Career | Job Hunt | JD | Job Description | Resume | CV | Behavioral Interview | STAR | Tell me about a time | Interview Preparation
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SKILL optimization
Use this tool when users request updates, optimizations, modifications, repairs, refactoring, splitting, or validation of existing skills, correcting trigger conditions, compressing bloated content, adjusting resource structures, or reorganizing rough workflows into maintainable skills.
Self-media title strategist
Generate multi-directional titles for content on WeChat Official Accounts, Xiaohongshu, and other Chinese self-media platforms. The system provides a comprehensive score and recommends main and alternative titles that balance click potential, factual accuracy, and long-term trustworthiness of the account.
How to ask questions during user interviews
Design high-quality user interview questions, outlines, and follow-up questions for product research, customer discovery, UX research, and feature validation, and translate interview evidence into product decisions.
Duan Yongping's investment strategy stock selection model
A research assistant for A-shares based on value investing principles. By analyzing business models, competitive advantages, financial quality, and valuation levels, it helps investors identify outstanding companies with long-term compounding potential.
Teaching Paper Architect
From teaching research accumulation to CSSCI/SSCI/SCI — making every teaching paper stand up to peer review. This is not a tool that writes your paper for you, but a paper architect that understands educational academic norms. It knows that IMRaD is not just four letters but a rigorous argument logic; that a literature review is not a list of references but a precise positioning of research gaps; that effect sizes are more convincing to reviewers than p-values. Seven-stage full-process coverage: Topic Focus (Innovation Three-Question Check) → Literature Review (Three-Level Coding + Funnel Writing) → Research Design (Quantitative/Qualitative/Mixed Approach Decision) → Data Analysis (Statistical Method Decision Tree) → Discussion Construction (Contribution Self-Check Matrix) → Language Refinement (AI Removal + Language Elevation + Revision Notes) → Journal Adaptation (Matching Matrix + Rejection Risk Pre-Reinforcement). Built-in Triple-Core Adversarial Engine: The Academic Writer handles output, the Language Elevation Officer polishes, and the Academic Gatekeeper has veto power—are the references real? Is the data reliable? Is the argument grounded in evidence? Does the contribution match the target journal level? Five dimensions are audited item by item; if any fail, it is sent back for rework. It doesn't just help you write well, it teaches you why the changes are made—each output includes revision notes, allowing you to truly improve your academic writing skills through iterations. Supports bilingual format validation (GB/T 7714 / APA 7th), suitable for daily teaching research accumulation, project conclusion output, and professional title evaluation sprints.
Textbook AI-Reduced Rewriting System 2.0
A Memorandum on the Core Principles of AI Rate Reduction: The core recognition logic of AI detection tools (such as CNKI AIGC detection, GPTZero, Originality.ai, etc.) is based on the following statistical characteristics: 1. Perplexity: AI-generated text has low overall perplexity because it selects the "next word with the highest probability." Human writing tends to choose more "less common but appropriate" words, resulting in high perplexity. → Rewriting Strategy: S4 Lexical De-standardization. 2. Burstiness: AI-generated sentences have highly uniform lengths, resulting in low burstiness. Human writing has highly variable sentence lengths, sometimes extremely short and sometimes extremely long, resulting in high burstiness. → Rewriting Strategy: S1 Sentence Length Mutation Injection. 3. Transition Word Density: AI over-relies on explicit transition words ("in addition," "however," "therefore," "in conclusion"), resulting in abnormally high density. Humans use more implicit semantic connections. → Rewriting Strategy: S2 Template Word Removal. 4. **Structural Templates:** AI tends to use a three-part structure ("general-specific-general"), parallel items of equal length, and a numbered structure ("first-second-last"). Human structures are more flexible and varied. → Rewriting Strategy: S3 – Disrupt the structure. 5. **Lexical Diversity (TTR):** AI has a high word repetition rate in long texts, resulting in a low TTR. Humans naturally have a wider vocabulary. → Rewriting Strategy: S4 – Destandardize vocabulary. 6. **Linearity of Information Presentation:** AI tends to present information in a logical, linear fashion with uniform information density. Humans use non-linear techniques such as flashbacks, digressions, and contrasting jumps. → Rewriting Strategy: S6 – Reorganize information density. Special Constraints of Textbook Style: Textbook AI reduction cannot be as casually colloquial as ordinary online articles. It must adhere to the following: • **Academic Rigor Bottom Line:** No use of internet slang, overly colloquial expressions, or emoticons. • **Terminology Accuracy Bottom Line:** All subject-specific terminology must be preserved in its original form; "synonyms" for inaccurate statements are prohibited. • Logical Integrity: The logic of causal relationships, classification systems, and operational steps must not be altered during rewriting. • Citation Standards: The numbers of cited documents, regulations, and standards must not be falsified. • Instructional Applicability: The rewritten text must still be suitable for student reading and comprehension; readability should not be sacrificed to reduce AI scores.
Full guidance on the project application process
It guides teachers to write full-text research proposals across disciplines, from topic diagnosis to full-text logical consistency checks, covering title argumentation, concept definition, literature review (online search + user confirmation), research value, research design (including nested roadmap skills), expected results and feasibility analysis, and has a built-in step-by-step execution and key node user confirmation mechanism.
Complete Film and Television Visuals - Worldview Construction Illustrations - FA0719
This skill is a professional "Film Worldview Visual Development Tool." It emphasizes world consistency, cultural logic, ecological materials, character behavior, spatial relationships, and the narrative connection between nine images. It is responsible for constructing a complete world from an idea, reference image, or story concept, and outputting nine still frames of that world. It can also construct a complete mythological worldview from a concept and output nine still frame cues. Furthermore, it can generate nine different compositional versions of a single frame, expanding upon a fixed scene. Suitable for: Fictional world visual development, reference image world extension, nine consecutive still frames from an unreleased film, and cultural ecology exploration. Not suitable for: Single, ordinary image cues, character design three-view diagrams, video motion cues, script storyboards, and nine compositions for a fixed scene.
Popular Cover Generator
Based on photos, avatars, or video screenshots and the theme of short videos, automatically generate viral short video covers for knowledge-based content featuring real-person IPs, large, highly saturated text, and strong visual metaphors.
Project Technology Roadmap (In-Depth Version)
Expert skills in designing research technology roadmaps. Beyond simply extracting the correspondence between research stages, content, and methods, the core capability lies in extracting an "internal structural diagram" (rather than a simple list with downward arrows) that aligns with the research logic of each research stage, based on the research materials, and generating a visually appealing technology roadmap in an academic style. It supports the deep construction of eight structural diagrams, including linear progression, iterative loops, triangular interaction, matrix parallelism, convergence, bifurcation, backtracking, and hierarchical nesting.
Xiaohongshu Lazy Account Generator Tool
1. **WB-XHS-Monetization-Backsolve Integration:** This involves working backward from the monetization path of a Xiaohongshu account, analyzing account positioning and content direction. It includes yanliudreamer's timing judgment, personal IP strategy, long-term communication skills, and 10-20 verification strategies. It also includes the visual director's assessment that "different trust paths require different visual trust." The core change is moving beyond simply asking "how to monetize," to answering "why now, why you, can you continue this long-term, and what visual trust needs to be built." 2. **WB-XHS-Low-Follower-Pattern Integration:** This involves analyzing a low-follower, high-data sample on Xiaohongshu. It includes yanliudreamer's click-through rate × dwell time × interaction rate, and five types of underlying user needs. It also includes dbskill's benchmarking filtering, analysis of dissemination reasons and resonance mechanisms. The visual director's cover composition, main visual, page rhythm, and mobile readability checks are also included. The core change is moving beyond simply imitating sample formats, focusing on determining which data aspects are effective and which content and visual mechanisms can be transferred. 3. wb-xhs-account-profile integration: Xiaohongshu's account profile and long-term memory. yanliudreamer's trust assets, personal IP story, persona verticality, and comment/private message feedback. dbskill's personal language samples, credible evidence, and AI-powered writing style calibration. Visual director's visual identity comprised of aspect ratio, color, font, components, and disabling anti-patterns. Core change: Account profiles are upgraded from static style descriptions to a continuously updated "trust business card + content and visual memory." 4. wb-xhs-topic-bank integration: Xiaohongshu's topic selection matrix and title formula. yanliudreamer's five types of user needs and the three questions before posting. dbskill's title triggers, hard title checks, and traceable trigger reasons. Visual director's cover hooks, main visual direction, information density, and page number suggestions. Core change: Topic selection is no longer just about generating titles, but simultaneously providing user needs, content promises, and briefs that can be handed over to visual production. 5. wb-xhs-humanize-compliance integration: Xiaohongshu's initial draft calibration and pre-release checks. dbskill's hooks, single core mechanism, diagnosis before rewriting, and 5-second introduction. Visual director's 6-8 page image-text structure, information hierarchy, and mobile readability. Core change: De-AI-sounding is not just about colloquial language, but about making content feel more human, easier to read, and clearly break it down into image-text pages. 6. wb-xhs-schedule-review integration: WorkBuddy's first 10 items, 7-day, and 30-day scheduling and review loop. yanliudreamer's system profiling, 10-20 item verification, and post-viral follow-up. dbskill's status recording and conclusion writing mechanism. Visual director's master template, visual confirmation image, final image, and visual review nodes. Key Changes: Scheduling now includes not only release dates but also content and visual production; it only preserves visual constraints and does not replace visual routing or image delivery. 7. wb-xhs-visual-router Integration: Includes existing titles, pages, and visual constraints generated from topic selection, revisions, and scheduling in this project. New additions include shared Visual Briefs, factual boundaries, actual running status, and QA record conventions. Key Change: Visual requests now have a single entry point; it first completes the cover title, evidence, and factual boundaries before routing to the corresponding experts, preventing "image tools not yet called" from being marked as delivered images. 8. wb-xhs-cover-anchor Integration: Information density × visual anchors from ponyodong2026/ponyo-cover-anchor-system; four types of templates: conflict/number/screenshot/emotion; old cover diagnosis and completion prompts. Includes a doodle-style outline for lifestyle covers, a sun-drenched film collage with white outline variations, and 3:4 thumbnail readability rules. Xiaohongshu's Fact Boundaries: Numbers, screenshots, cases, and main content are only used when confirmed or authorized. Core Change: The cover is not just a title skeleton, but a publishable complete cover and a quantifiable diagnosis; even in the absence of evidence, credible titles and compositions are retained, and unverified data, cases, or results are not presented as facts. 9. wb-xhs-xiaohei-illustration Integration: The little black character from helloianneo/ian-xiaohei-illustrations, 16:9 text illustrations, shot lists, white-background hand-drawn illustrations, and bizarre cognitive metaphors. Pure white background, thin black lines, a few red, orange, and blue annotations, and QA stating "Little Black must undertake the core actions." Core Change: Transform the judgments, processes, states, and metaphors in the article into easily readable text illustrations; retain MIT source attribution, recreate the metaphors of each image, and do not copy example images or compositions. 10. Integration of wb-xhs-material-illustration: This integrates the materialized central illustration diagram, semantic redrawing of charts, and the division of labor between supplementing facts and outer cards in op7418/guizang-material-illustration. It covers mechanisms, processes, loops, hierarchies, comparisons, charts, and objects, arrows, sub-labels, and explanatory components extracted from the central diagram. Key changes: First, a wide central diagram clearly explains the relationships or data, then reusable components are developed; simultaneously, when "materials + cover" are needed, the precise title of the cover is confirmed first, then both types of deliverables are completed separately.
MarketSnap Market Data Card
There are many skills for checking market data, but this is the only one that gives you a market data card that you can send directly. Enter a stock name, code, or "market index," and it will: ① Retrieve data from a real-time market data interface (not relying on AI to guess prices), and annotate data points accurate to the minute. ② Provide you with a complete text overview: current price, change, trading volume, turnover, PE/PB ratio, market capitalization, and 52-week position. ③ Each time, it will also include an institutional-style market data card (1080x1350 vertical version) – featuring a large-format visual of price changes, indicator grids, valuation bars, and 52-week range positioning, in a deep blue and gold color scheme. It automatically recognizes four modes: · Individual stock overview (default) · Multi-stock comparison (2-6 stocks, automatically highlighting leading gainers and losers) · Market overview (three major indices + trading volume + number of gainers and losers) · Detailed mode (including 5-day trend + recent news) Attention to detail: · A-shares/Hong Kong stocks rise (red) and fall (green), US stocks rise (green) and fall (red) – automatically switching according to the market to avoid errors. The data interface uses a three-tiered degradation chain. If all failures occur, the user will be informed truthfully. No data is fabricated. Data is presented without stock recommendations or predictions. Each card includes a disclaimer. Suitable for investors who monitor the market daily, financial group leaders, and content creators who need market data.
Financial Hot Topics Interpretation infographic
Quickly transform complex financial news into professional, intuitive infographics and social media posts. Simply provide a financial event or news link, and this skill instantly generates a set of visualizations containing key data, impact analysis, and unique perspectives, along with a ready-to-post caption for Xiaohongshu (Little Red Book). This skill excels at in-depth fact-checking and data tracing of financial events, ensuring all information is properly sourced and dated, making your content both authoritative and credible. It automatically outlines the ins and outs of events, compares key figures, and identifies potential contagious impacts, presenting them in beautifully designed card sets or infographics with color schemes and price indicators conforming to professional market standards. Whether analyzing Federal Reserve policy, interpreting company financial reports, or tracking market anomalies, you'll receive a visually professional and rigorously structured interpretation. The final deliverables include a set of high-resolution images (supporting single infographics or multiple card combinations) and a caption tailored to the platform, helping you easily grasp the pulse of finance and efficiently produce high-quality content.
In-depth Stock Analysis Engine | Thoroughly research a company
This is not a mere information excerpt, but a stock research report with a methodological framework. Enter a company's name or stock code (A-share/Hong Kong/US stock), and it will perform 10-15 online searches in both Chinese and English, presenting the report within a seven-dimensional framework: ① Business Model – Where does the money come from and where does it go, with a simplified explanation. ② Revenue Structure – Breakdown by business segment + growth engines and drags. ③ Competitive Moat – A mandatory answer to whether it's widening or narrowing, using market share/gross profit margin/pricing power as indicators. ④ Financial Quality – Matching of cash flow and profit, abnormal changes in accounts receivable, inventory, and goodwill. ⑤ Competitive Landscape – Competitor comparison table + concentration trend. ⑥ Valuation Framework – Only data and calculation framework provided, no judgment of high or low valuation. ⑦ Risk List – Sorted by impact, each with verifiable trigger signals. Each report includes: a one-page summary of bullish and bearish trends (with substantial evidence on both sides), a tracking list for the next quarter, and the source of each data point. Three ironclad rules: • Every key figure is traceable to announcements or authoritative media; if it cannot be found, it is marked "insufficient information," never fabricated. • Facts, calculations, and inferences are labeled separately. • No stock price predictions, no target prices, no buy/sell advice—even the "should I buy?" question is answered only with three perspectives supported by bullish/bearish evidence: understanding the business (default) / financial statement review / comparison of competing companies. Suitable for investment researchers, financial content creators, and serious investors who want to systematically understand a company.
Investment Master Checklist | Viewing Companies Through Buffett's Lens
Warren Buffett's shareholder letters, *Poor Charlie's Almanack*, and *The Intelligent Investor*—the standards of investment masters are all publicly available, but no one ever helps you check them against one by one. Enter a company (A-shares/Hong Kong stocks/US stocks), and choose a master's perspective: Buffett (default)/Munger/Peter Lynch/Fisher/Graham. It will connect online to verify the publicly available evidence corresponding to each standard, providing a ✅compliant/⚠️partially compliant/❌non-compliant/❓insufficient information assessment for each item, and generate a shareable scorecard long image (3:5 vertical, suitable for Xiaohongshu/WeChat Moments). Each delivery includes: ① A thorough check of the main text: Each standard includes the judgment, evidence, source, and time point, along with a "translation into plain language"—what exactly is this standard asking? ② A summary of the scorecards (N/8 criteria met) + the three most noteworthy points. ③ A long scorecard chart with classic value investing color scheme, allowing you to directly publish three ironclad rules: · Judgments must be accompanied by evidence; if evidence is missing, mark it with a "❓"; never fabricate data. · The list items are faithful to the publicly available works of masters; do not fabricate "master standards." · Only presents the comparison results; does not represent the masters' views and does not constitute investment advice. Repeat purchase strategy: For the same company, five masters each examine it, with five perspectives corroborating each other. Suitable for value investing learners, financial content creators, and ordinary investors who want to systematically understand a company.
我是一名小镇青年，大学本科，35 岁，在北京工作。已婚未育。此前被裁员，目前处于寻找方向的状态。我擅长做内容和运营，对 AI 很感兴趣，日常也在用 AI 搭建自己的工作流。Claude、Code、Codex 以及先进的 Agent 我也都在使用，但经常会发现用了太多的工具，并没有合适的场景来变现。 在现在这种经济不确定性，以及 AI 发展这么快的情况下，我应该怎么快速找到自己的优势，能够实现自己的管道收入呢？
你这个问题，不@一个人的单聊能聊，但容易偏科。它其实是三层叠在一起的： 「管道收入」先拆一下——不是"赚一笔大的"，是"搭一个能自己流水的系统"。你用了一堆AI工具却没变现，问题可能不在工具，在于你还没把工具变成别人愿意付钱的特定产出。这就好比厨房里刀具齐全，但你还没端出一道菜。 按你的情况（内容运营出身 + AI工具熟练 + 35岁被裁找方向 + 要搭管道），我建议开个创作者变现圆桌，三个人刚好各管一层： | 人物 | 管哪一层 | 为什么是他 | |---|---|---| | Naval | 找你的特定知识 | 他那句"无法培训的能力才是护城河"——直接帮你定位35岁该押什么 | | Dan Koe | 一人公司怎么搭 | 他自己就是内容+AI工具+个人品牌的活样本，管道收入的具体路径 | | 李笑来 | 长期主义 + 怎么让收入复利 | 他从新东方老师到写书到投资，每个阶段都在搭新管道，且他极度强调"定投式"积累 | 这三个人的底层假设会有一处交锋特别有意思：Naval和Dan Koe都信"杠杆放大个人"，但李笑来会更强调"在杠杆之前，得先有一个值得被放大的东西"——这对你现在"工具多场景少"的状态，可能正好戳中盲区。 --- 确认一下要不要这样开？ 或者你想换人 / 加人 / 改成只跟某一个人私聊，都行。开圆桌的话我直接上三轮。
好的，直接开始吧。
好，圆桌开始。三位入场—— > 话题： 35岁内容运营，AI工具熟练但无法变现，如何找到优势并搭建管道收入？ > 参与者： Naval · Dan Koe · 李笑来 --- 🎙️ Round 1 · 独立开场 💬 Naval 你的问题不在"找不到场景"——在于你还没找到自己的特定知识。 什么是特定知识？就是你干起来像玩、别人干起来像搬砖的那件事。它没法被培训，因为它来自你活了35年的真实经历。你不是小镇青年吗？你不是做过内容运营吗？你现在不是在用AI搭工作流吗？这三样东西的交叉点就是你的特定知识——"懂下沉用户心理 + 会做内容 + 会用AI放大效率"，这个组合全国没几个人有。 但你犯了一个错：你在收集工具，不是在建造杠杆。 打个比方：你有了一把好锤子、一把好锯子、一把好电钻，但你还没盖出一间能收租的房子。锤子不是资产，房子才是。代码和媒体是两种零边际成本的杠杆——内容就是媒体杠杆，AI工作流就是代码杠杆。你两样都在手上了，但你没把它们指向一个愿意付钱的人。 35岁被裁，别慌着"快速找到方向"。方向不在外面找，在你已经走过的路里捡。把你过去做内容运营踩过的坑、总结的方法论，用AI变成可复用的交付物——模板、工具、教程——这才是管道。 --- 💬 Dan Koe Naval说得对，但我要补一个更关键的东西：你在找"场景"，但场景不需要找——你自己就是场景。 你现在的状态是什么？35岁，被裁，在研究AI工具，想搭管道收入但不知道怎么变现。你知道有多少人和你一模一样吗？几十万人。他们都在刷手机找答案，而你就是那个正在经历答案的人。 一人公司的逻辑不是"先想好卖什么再做"。是反过来：学→做→分享→吸引→变现。你已经在学和做了，但你卡在"分享"这一步。你把AI工具当私人玩具在玩，没有把"我怎么玩的"变成公开内容。 你现在应该做的事：把你的AI工作流搭建过程，从第一天开始公开出来。不是教别人"AI有多厉害"——这种内容烂大街了。而是记录"一个35岁被裁的内容运营，怎么用AI重建自己的收入系统"。这个过程本身就是产品。 管道收入不是某天突然搭好的管道。是你每天写一点、建一点、发一点，像种数字花园一样，慢慢长出来的。但前提是——你得让外面的人看得见你在种。 --- 💬 李笑来 我先泼盆冷水。 你说"快速找到优势，实现管道收入"——这句话里有两个字是毒药：快速。 管道收入的本质是什么？是资产在睡觉时替你赚钱。但你现在手上有什么资产？工具不是资产，技能不是资产，甚至"会用Claude"也不是资产。资产是什么？是一本写好的书、一个跑着的付费社群、一套卖得动的课程模板、一个有人续费的SaaS工具。 你现在的问题像什么？像一个人逛了一圈建材市场，买齐了砖头水泥钢筋，然后在市场门口坐着发愁："我的房子什么时候能盖好？" 砖头不会自己变成房子。 我给你一个框架，就两个字：定投。 不是定投基金——是定投你的注意力。选一件事，每天往里投2小时，持续至少两年，不换方向。你的选项我帮你筛一下：你擅长内容运营，你会用AI——那就做"AI内容工作流模板"，针对中小企业和个人创作者，做成可付费的产品包。这不是什么新发明，但它能成为你的资产。 Naval说的特定知识、Dan Koe说的一人公司，都对。但都得建立在一个前提上：你得先有一个值得被放大的东西。 你现在连那个东西都还没做出来。 --- ⚔️ Round 2 · 交锋回应 💬 Naval（回应 Dan Koe + 李笑来） 笑来说的"先有一个值得被放大的东西"——我完全同意。这是你最大的盲区。你在用AI搭工作流，但你搭的工作流解决的是你自己的问题，不是别人的。自己的问题没有市场规模。 但我要反驳Dan Koe一点：他说"你正在经历答案，记录下来就是产品"——这话对一半，危险在一半。 对的一半：真实经历确实是最稀缺的内容。 危险的一半：35岁有房贷有生活成本，你不能等"旅程自然展开"再变现。旅程可能走两年，你的存款撑不了两年。 我的建议是两条腿同时走：一条腿记录旅程做内容（Dan Koe说的，媒体杠杆）；另一条腿马上把你会的东西卖给一个具体的人（哪怕是帮一家小公司用AI优化内容流程，收5000块）。前者是慢管道，后者是快现金流。先用快现金流买时间，再用时间养慢管道。 --- 💬 Dan Koe（回应 Naval + 李笑来） Naval说的"两条腿走路"我同意，但他低估了一件事：你已经记录的内容本身就可以变成付费产品，不需要等。 你的AI工作流——Claude怎么搭、Codex怎么用、Agent怎么串——这些东西对你是日常，对90%的内容从业者来说是黑箱。你不需要先"找到客户"再开始。你把工作流截图、录屏、写成文档，挂个99块的价签放出去，先验证有没有人买。有人买=市场存在，没人买=你假设错了，换。 这跟笑来说的"定投一件事"不矛盾。定投不等于慢慢来——定投是每天固定投入，但产出可以立刻投放到市场上测试。种竹子前四年不长，但你可以在旁边种点小菜先吃着。竹子是管道，小菜是现金流。 我反驳笑来一点：他说"快速是毒药"。但对你这个处境来说，不快速才是真正的毒药。拖得越久，信心消耗越大，工具越换越多，最后变成一个"什么都试过但什么都没做成"的人。行动的速度本身就是一种护城河——因为大部分人光是想就耗尽了力气。 --- 💬 李笑来（回应 Naval + Dan Koe） 你们俩说的我大部分同意，但有一个根本性的分歧。 Naval说"先卖给一个具体的人，收5000块"。Dan Koe说"挂个99块放出去验证"。这些都没错，但你们在解决的是赚钱的问题，不是管道收入的问题。 这是两件事。 帮人做一次AI内容优化，收5000块——这是劳动收入，不是管道收入。卖一份99块的文档——如果只卖一次，也是劳动收入。只有当你做出一个东西，它能反复卖、自动卖、你睡觉时也在卖，那才叫管道。 我反驳的是：你们俩都在鼓励他"先动起来赚点钱"，但赚快钱最大的风险是把你锁在劳动模式里出不来。今天帮人做AI优化收5000，明天又来一个客户收8000，后天你发现自己又变成打工的了——只不过这次是给自己打工，还是按小时卖。 管道收入的路径是这样的：你用AI工具做内容运营服务（快钱）→ 同时把服务过程中沉淀的方法论产品化（模板包/课程/工具）→ 产品能自动卖了，你才真正有了管道。 所以"定投一件事"的意思是：你每天的服务收入里，必须有一部分时间是在造资产的，不是全花在交付服务上。 否则你永远在跑步机上跑。 --- 🎯 圆桌总结 ✅ 三人共识 1. 你的特定知识已经存在，不需要向外找。 "内容运营经验 + 小镇青年视角 + AI工具能力"这个交叉点就是。三人都认同：别再找方向了，方向就在你已经走过的路上。 2. 你现在的问题是"造了工具但没造资产"。 工具是锤子，资产是房子。你收集了一堆锤子，还没开始砌墙。 3. 必须立刻公开。 你把AI工作流当私人玩具在玩，这是最大的浪费。不管卖什么价，先让市场看见。 ⚔️ 核心分歧 | 分歧点 | Naval | Dan Koe | 李笑来 | |---|---|---|---| | 速度 | 快慢两条腿并行 | 越快越好，行动即护城河 | 快可以，但不能把"快赚钱"当"搭管道" | | 变现路径 | 先卖服务赚现金流，再养管道 | 先把内容产品化挂出去验证 | 服务和造资产必须同时进行，否则锁死在劳动模式 | 底层假设的分叉： Naval和Dan Koe本质上信"杠杆可以放大任何东西"，所以倾向于"先动起来再说"。李笑来信"没有值得放大的东西，杠杆放大的是空气"，所以倾向于"先确保你在造资产"。 🔍 你忽略的盲区 1. 你把"会用很多AI工具"当优势，但这是最容易被替代的能力。 工具人人都能学。真正的优势是"你用工具解决了什么具体问题"。Claude谁都会用，但"用Claude帮一个教培公司把内容产能提升3倍"——这个只有你能讲。 2. 你35岁、已婚、在北京——这不是劣势，是定位。 你的受众不是硅谷极客，是和你处境相似的人：有职场经验、被时代冲击、想用AI自救的普通人。这个人群巨大，且没人专门服务他们。 3. "管道收入"不是一夜搭好的管道，是每天浇一点水的花园。 但你必须有一个明确的"花园"在浇。现在你连花园在哪都还没定。 📋 行动建议 第一周 · 定方向 把你所有AI工作流整理一遍，选最拿手的一个场景（比如：用AI批量生成小红书内容、用Agent自动化内容分发、用Claude做内容选题分析）。只选一个，别贪多。 第二周 · 造最小资产 把这个场景的完整工作流做成一个可交付的产品包：操作文档 + 模板 + 录屏演示。定价99-299，挂到即刻、小红书、知识星球。 第三周起 · 双线并行 - 快线：在小红书/即刻持续公开你用AI重建收入的过程，吸引和你处境相似的人 - 慢线：每周从服务交付中抽至少半天，把方法论沉淀进产品，让产品越卖越自动化 关键纪律： 每天的产出里，必须有一样是"能重复卖的东西"，不能全是"一次性交付的东西"。这是劳动收入和管道收入的分界线。 --- 要不要我针对其中某个人再做一轮深入追问？比如让李笑来具体展开"怎么把服务过程产品化"，或者让Dan Koe讲讲一人公司的内容发布节奏？
你说的这两点我都感兴趣，也都讲一讲吧。
Celebrity Chat Room
In the "Celebrity Chat Room," you can engage in in-depth conversations with top figures from various fields, whether seeking personal guidance or discussing complex issues. You can choose to discuss first principles with Musk, consult with mentors on strategic thinking, ask Munger to examine your decisions, or talk to Naval about leverage principles, broadening your perspectives from multiple angles and avoiding getting bogged down in details. This skill supports two core communication modes: you can choose to have a private one-on-one conversation with a celebrity to gain a deeper understanding of their core ideas; or you can initiate a roundtable discussion with multiple celebrities, allowing them to engage in a lively exchange of ideas on your questions, providing judgments, evidence, and even pointing out blind spots you may have overlooked. Furthermore, when you wish to introduce new perspectives, this skill can "invite" more figures to join the discussion based on your needs. It quickly extracts the core ideas and unique styles of new figures, integrating them into the existing conversation to provide you with richer viewpoints and more comprehensive thinking. Finally, the moderator will summarize the consensus, disagreements, blind spots, and action suggestions from the discussion, helping you clearly understand the problem and make informed decisions.