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本书是一本系统介绍ima与WorkBuddy“双工具”联动的入门与实战指南，以“先筑基、再联动”为主线，先借助 ima 搭建有序运转的个人知识体系，再通过 WorkBuddy 将知识转化为可交付的成果，带你走通一条从知识沉淀到任务执行的完整路径。书中内容紧贴真实的业务场景，覆盖职场人、咨询顾问、高校教师、自媒体人等人群的高频痛点，用双工具完成资料管理、文案写作、数据分析等基础任务，并进一步把零散经验变成可复用的知识资产和生产流水线。每个场景都配有操作截图、提示词模板、Skill 配置或专家团搭建方案。不论你是职场新人、管理者，还是 OPC 从业者，都能按图索骥，构建懂你的高效 AI 系统，实现从“会用 AI 聊天”到“让 AI 把事做完”的跨越。

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ISBN：9787121534010

开本：16(170*240)

页数：276

字数：367

本书目录

第一部分　ima筑基篇
第 1 章　初识ima：从安装到创建第一个知识库 ·······································.2
1.1 ima 安装与登录 ····························································.2
1.1.1　多端覆盖 ···························································.2
1.1.2　下载和安装 ························································.3
1.1.3　极简注册与登录 ··················································.4
1.2 ima 页面：认识你的“第二大脑” ····································.4
1.2.1 ima 首页整体布局 ················································.4
1.2.2 ima 四大核心功能 ················································.5
1.2.3　功能快捷入口 ····················································.10
1.2.4　个性化设置 ·······················································.12
1.2.5　移动端速览 ·······················································.13
1.3　认识 copilot：你的专属 AI 助手·······································.13
1.3.1 copilot 核心优势 ·················································.13
1.3.2 copilot 页面及设置 ··············································.14
1.3.3 copilot 与 WorkBuddy 的不同 ·································.17
1.4　开启你的 ima 之旅························································.17
1.4.1　启动第一次 ima 对话 ···········································.18
1.4.2　创建第一篇专属笔记 ···········································.21
1.4.3　创建首个个人知识库，并启动库内对话 ···················.25
1.4.4　开始与 copilot 的第一次对话··································.30
1.5　动手实践：ima 落地检查清单 ·········································.30
第 2 章　搭建ima知识库：让“第二大脑”更有序··································.31
2.1　你是否也遇到过这些难题···············································.31
2.2　底层逻辑：放弃“图书馆静态分类”，拥抱 IRAP 动态架构 ··.32
2.2.1　从“图书馆静态分类”到“知识动态架构” ·············.32
2.2.2 PARA 方法：按用途与使用活跃度分类····················.33
2.2.3　从 PARA 到 IRAP：面向 AI 时代的四层架构·············.34
2.2.4　知识库搭建的三项核心原则 ··································.36
2.3　开箱即用规则：一张规则卡，让四层架构“各就各位”········.36
2.4　系统实操：把规则卡变成你的“第二大脑”·······················.39
2.4.1　结构：“文件夹 + 标签 + 搜索”三件套协同·············.39
2.4.2　实操建库：两种搭建方案按需选择 ·························.42
2.4.3　维护：让知识库养成有序运转的好习惯 ···················.44
2.5　动手实践：3 分钟落地规则卡 ·········································.45
第 3 章　沉淀知识：让“第二大脑”更强大··········································.46
3.1　你是否也遇到过这些难题···············································.46
3.2　底层逻辑：Resources → Area 知识流动模型 ·······················.47
3.2.1　知识流动的意义 ·················································.47
3.2.2　知识价值的四步闭环循环 ·····································.48
3.2.3　知识三大核心流向 ··············································.49
3.2.4　三大流向的优先级原则 ········································.50
3.3　开箱即用规则：Resources → Area 三大流转规则 ·················.51
3.3.1　规则卡总览 ·······················································.51
3.3.2　三大流转规则 ····················································.51
3.3.3　通用判定方法：流向“三问法” ····························.52
3.4　系统实操：素材加工与知识提炼······································.52
3.4.1　素材入库及筛选标准 ···········································.52
3.4.2　原始素材的初步加工 ···········································.53
3.4.3　提炼：把素材变成知识资产 ··································.58
3.5　动手实践：“双入口”对照实操实验································.61
第 4 章　共享知识：让知识流动起来 ··················································.63
4.1　团队知识共享的常见难题···············································.63
4.2　底层逻辑：从“个人大脑”到“团队公脑”，再到“开放大脑”64
4.3　开箱即用规则······························································.65
4.4　知识库实操·································································.66
4.4.1　共享知识库实操 ·················································.66
4.4.2　订阅与发布知识库 ··············································.69
4.4.3　知识库的三种形态 ··············································.73
4.5　知识库使用风险及应对··················································.73
4.6　动手实践：落地卡片·····················································.74
4.7　走向 WorkBuddy ··························································.75
第二部分　ima+WorkBuddy联动篇
第 5 章　初识WorkBuddy，从安装到完成第一个任务 ·····························.78
5.1 WorkBuddy 安装和登录 ·················································.78
5.1.1 WorkBuddy 下载与安装 ········································.78
5.1.2 WorkBuddy 登录与多端使用 ··································.79
5.2 WorkBuddy 页面：四个区域各司其职 ·······························.80
5.2.1　核心功能区 ·······················································.80
5.2.2　任务管理区 ·······················································.81
5.2.3　人机对话区 ·······················································.81
5.2.4　预览编辑区 ·······················································.81
5.3　产物：一切操作以输出为导向·········································.82
5.3.1 WorkBuddy 支持的文件格式 ··································.82
5.3.2　文件格式多样性的价值 ········································.83
5.4　对话：WorkBuddy 任务配置 ···········································.83
5.4.1　材料输入 ··························································.84
5.4.2　能力配置 ··························································.85
5.4.3　空间设置 ··························································.87
5.5　上手：完成 WorkBuddy 第一个任务 ·································.87
5.5.1 WorkBuddy 场景任务 ···········································.87
5.5.2　巧用模板制作年终总结 PPT ··································.89
5.6　动手实践：WorkBuddy 上手检查清单 ·······························.91
第 6 章　解构WorkBuddy能力全景图 ··················································.92
6.1　空间能力：工作空间、远程控制与连接器··························.92
6.1.1　工作空间：WorkBuddy 的数字工位 ·························.93
6.1.2　远程控制：走到哪里，WorkBuddy 跟到哪里 ·············.96
6.1.3　连接器：将 WorkBuddy 接入你的数据生态 ···············.99
6.2　时间能力：批量化处理与定时任务·································.104
6.2.1　批量化处理：从处理一个到处理一批 ····················.104
6.2.2　定时任务：让任务在人不在场时自动执行 ··············.107
6.3　协作能力：人机共写与团队共创······································110
6.3.1　人机共写：从 AI 代笔到同屏共编···························110
6.3.2　团队共创：从个人产物到团队资产 ·························114
6.4　技能和专家（团）能力················································.120
6.5　输出能力：从单个文档到系统级交付······························.121
6.5.1　输出一套完整的解决方案 ···································.121
6.5.2　输出动态系统 ··················································.122
6.6　记忆能力：让 WorkBuddy“越来越懂你” ·······················.123
6.6.1　用户级记忆：越用越懂你的 AI 同事······················.123
6.6.2　项目级记忆：每个工作空间都有记忆文件夹 ···········.126
6.6.3　对话级记忆：上下文的协作连续性 ·······················.127
6.6.4　三级记忆的优先级与日常维护 ·····························.128
第 7 章　锚定场景：找到你的高频任务··············································.131
7.1　应用场景：从基础任务到综合运用·································.131
7.1.1　基础任务：单点提效的四类场景 ··························.132
7.1.2　综合运用：从单点任务到端到端交付 ····················.139
7.2　任务筛选：“高频低复杂”是首选·································.140
7.2.1　任务盘点三步法：把一周工作看清楚 ····················.140
7.2.2　四象限筛选：频率 × 复杂度·······························.142
7.2.3　最小可行场景法：先跑通，再放大和扩展 ··············.144
7.3　匹配能力：WorkBuddy 任务委托逻辑 ·····························.145
7.3.1　能力与任务配置的映射关系 ································.146
7.3.2　基础任务配置：四类任务的能力组合 ····················.146
7.3.3　综合任务配置：三种组合的配置模板 ····················.148
7.3.4　查表“三步走”：从任务到配置 ··························.150
7.4　精准指令：让 WorkBuddy 少返工 ··································.150
7.4.1　精准指令四要素 ···············································.151
7.4.2　增强提示词与元提示词 ······································.153
7.4.3 WorkBuddy 指令心法 ·········································.156
7.5　任务联动：“ima+WorkBuddy”打造高效“取—用—存”
闭环········································································.158
7.5.1　能力上限：执行翼需要知识翼 ·····························.158
7.5.2　一次授权：ima 知识库接入 WorkBuddy 流程 ···········.159
7.5.3　取：双模式调取知识库资料 ································.160
7.5.4　用：基于私有资料，实现有据可依输出 ·················.161
7.5.5　存：成果回流沉淀，知识库“越用越厚” ··············.161
7.6　动手实践：场景锚定实操·············································.163
第三部分　能力进阶篇
第 8 章　Skill的使用、创建与迭代····················································.166
8.1 Skill 核心定义 ···························································.166
8.1.1　你是否也在每天重复教 AI 工具做事······················.166
8.1.2 Skill 是写给 AI 工具的“岗位说明书” ··················.167
8.1.3 Skill 的物理形态···············································.168
8.1.4 Skill 三层渐进加载机制······································.169
8.1.5 Prompt、Skill、MCP 的差异································.170
8.2　上手：如何安装和使用 Skill ·········································.171
8.2.1　在 ima 上安装 Skill 的三种方式 ····························.171
8.2.2　在 WorkBuddy 上安装和使用 Skill·························.173
8.2.3　想清楚再动手：任务值不值得配 Skill····················.175
8.2.4　亲测好用的 Skill 推荐 ········································.176
8.3　创建：打造自己的第一个 Skill ······································.177
8.3.1　“三步法”创建 Skill·········································.177
8.3.2　写好 description：精准调用 Skill 的秘诀 ·················.179
8.3.3　优质 Skill 的设计哲学 ········································.179
8.4　迭代：让 Skill 越来越好用 ···········································.180
8.4.1　迭代从“失败用例”开始 ···································.180
8.4.2 Skill 问题的“三层定位法”································.180
8.4.3　版本记录法：让每次迭代都有迹可循 ····················.181
8.4.4　如何实现从“自己用”到“大家用” ····················.181
8.5　动手实践：实现“装两个、做一个、改一次”··················.182
第 9 章　从单一技能进化为专家（团）和系统·····································.183
9.1　能力升级：打造专属 Agent 专家（团）···························.183
9.1.1　专家：能干的员工 ············································.184
9.1.2　专家团：一个主理人带几个员工 ··························.185
9.1.3　能力递进：把权限一步步交给 AI 工具···················.187
9.1.4　上手路径：搭建自己的专家（团） ·······················.187
9.2　系统整合：打造高效 AI 生产力系统·······························.188
9.2.1　专家团编排逻辑 ···············································.188
9.2.2　利用专家团构建系统 ·········································.190
9.2.3　企业经营驾驶舱案例演示 ···································.191
9.3　动手实践：将技能升维为专家（团）······························.194
第四部分　应用场景篇
第 1 0 章　职场人：把高频琐事交给“双工具” ·································.196
10.1　办公痛点及突破方案 ·············································.196
10.1.1　职场人的四大崩溃瞬间 ································.196
10.1.2　工具组合：ima 和 WorkBuddy 的分工··············.197
10.2　场景一：资料管理——让资料“存得进、找得到” ······.198
10.2.1　解决方案：四条入库通道 + 一句检索指令········.198
10.2.2　从微信收藏到“30 秒可查” ·························.199
10.2.3　跨文档秒级智能检索 ···································.200
10.3　场景二：公文写作——初稿“出得快、文风统一” ······.201
10.3.1　解决方案：风格样本库沉淀 + 精准指令，“起草、润色、自查”一条龙·.201
10.3.2 15 分钟快速起草工作通知 ····························.202
10.3.3　从“每次写”到“一句话触发”：把公文写作封装成 Skill···.203
10.4　场景三：会议纪要——会议结束，纪要即刻成型 ·········.204
10.4.1　解决方案：“转写—结构化—存库”
三步闭环提效 ············································.204
10.4.2　从会议速记到可追踪的结构化会议纪要···········.205
10.4.3　周报智能化——只改不写、高效出稿 ··············.206
10.5　场景四：数据核对——让数字“对得齐、说得清” ······.206
10.5.1　解决方案：将全链路交由 WorkBuddy，人工只负责验收····.206
10.5.2　从多份杂乱表格到标准化数据报告 ·················.207
10.6　进阶：四个场景串联，搭建全自动“办公流水线” ······.209
10.6.1　组合示范：一条“办公流水线” ····················.209
10.6.2　流程自动化升级：让流程自己转起来 ··············.210
10.6.3　专家模式适配：跨场景复杂工作协同 ··············.210
10.6.4　找到适合自己与 AI 工具协同的方式 ···············.210
10.7　动手实践：实现“一存、一写、一纪要、一数据” ········211
第 1 1 章　咨询顾问：打造深度研究系统············································.212
11.1　场景痛点：知识零散、交付高压、经验难沉淀 ············.212
11.2　解决方案：让知识自生长，让研究可协同 ··················.213
11.2.1　两个场景 : 高效知识沉淀与专业深度研究·········.213
11.2.2　关键判断：按需匹配工具组合方案 ·················.214
11.3　案例一：打造自主生长的案例库·······························.214
11.3.1　前期准备：三步完成建库、连接与技能配置 ·····.214
11.3.2　技能创建：通过对话迭代固化标准化工作方法 ··.215
11.3.3　流程运转：五阶段全自动化流程 ····················.216
11.3.4　关键设计：人工核验机制与数据真实性红线 ·····.218
11.3.5　落地效果与适用边界 ···································.218
11.4　案例二：搭建深度研究专家团··································.219
11.4.1　团队构成：1 名主理人 +6 名专家 ···················.219
11.4.2　实操流程：接入 ima 知识库并生成深度研究报告 ····.220
11.4.3　落地效果与适用边界 ···································.221
11.5　动手实践：搭建你的深度研究系统····························.222
第 1 2 章　高校教师：搭建一条自己的教研生产线 ······························.223
12.1　场景地图：三条工作线，一条生产线 ························.223
12.1.1　四个崩溃瞬间：重复劳动发生在哪里 ··············.223
12.1.2　人机分工：三条工作线如何拆解 ····················.225
12.1.3　指令的统一骨架 ·········································.225
12.2　场景一：备课与教学——把一门课建成资产 ···············.226
12.2.1　解决方案：“双库”架构 + 教学 Skill ·············.226
12.2.2　创建一门课的教学库 ···································.227
12.2.3　用出题 Skill 生成分层练习题·························.228
12.2.4　讲义与课件初稿快速生成 ·····························.230
12.3　场景二：科研与课题申报——从选题孵化到申报书初稿生成···.231
12.3.1　解决方案：科研库 + 课题专家团····················.231
12.3.2　利用立项名单与政策文件孵化选题 ·················.232
12.3.3　从文献矩阵到技术路线图 ·····························.233
12.3.4　申报书初稿与课题专家团 ·····························.235
12.4　场景三：学生指导与学情分析——让经验可复用，让数据说话···.237
12.4.1　解决方案：一个指导库 + 两条流水线··············.237
12.4.2　毕业论文与竞赛材料初稿写作指导 ·················.238
12.4.3　成绩数据清洗与课程目标达成度分析 ··············.240
12.5　进阶：串联三大场景，搭建教研流水线 ·····················.241
12.5.1　贯穿全学期的自动化教研流水线 ····················.241
12.5.2　从手动触发到自动执行 ································.242
12.5.3　专家团：教研场景的应用时机 ·······················.243
12.6　动手实践：跑通“一课、一题、一指导” ··················.244
第 1 3 章　自媒体人：从选题到排版的创作流水线 ······························.246
13.1　场景痛点：原创难坚持，人设难固化 ························.246
13.1.1　高频创作的“三重”压力 ·····························.246
13.1.2　纯人工与纯 AI 的两难境地 ···························.247
13.1.3　破解方向：固化个人特性，外化执行工作········.247
13.2　解决方案：素材库、多 Skill 与调度专家 ····················.248
13.2.1　知识库设计：把素材沉淀成可调用的资产········.248
13.2.2 Skill 设计：七个环节的逻辑框架····················.249
13.2.3　专家设计：一个调度角色 ·····························.253
13.2.4　为什么是专家，而不是专家团 ·······················.254
13.3　案例演示：一次完整的公众号创作 ···························.254
13.3.1　准备：灵感入库和素材加工 ··························.255
13.3.2　写作：一键初稿 + 人工修改··························.256
13.3.3　收尾：配图与排版 ······································.257
13.4　把个人创作经验资产化 ··········································.259
13.5　动手实践：搭建个人创作流水线 ······························.259
结语·····························································································.246

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前言
很多人的电脑和手机里都安装着十余款AI应用，收藏夹中“躺”着上百篇《AI工具推荐》《提示词大全》等文章，但真正读完的文章不到十篇，亲手实操落地的更是仅有两三篇。人们应用 AI 工具半途而废的原因各不相同：要么实操卡在某一环节，无从答疑解惑；要么缺乏正向反馈，难以长期坚持。学不会、用不好AI，是当下多数人面对 AI 的真实困境。
2022年11月，ChatGPT正式发布后，生成式AI几乎每月都催生新的行业热点，各类 AI 工具呈现爆发式增长，但行业热度与大众实际使用之间，存在一道巨大的鸿沟：知晓、安装 AI 工具的人很多，而真正将 AI 工具融入日常工作流程、依托其稳定分担工作任务的人，始终只是少数。AI 工具在飞速迭代进化，很多人的工作方式却仍停留在传统模式阶段。
问题究竟出在哪里？本书的核心观点是：我们缺少的从来不是先进的 AI 工具，而是人机协作的范式升级。
也正因如此，本书与市面上大多只讲 WorkBuddy 的书不同：我们把 ima 知识库放在本书的第一部分，把它当作 WorkBuddy 赖以运转的地基。先让知识与素材在 ima 知识库中有序沉淀，再让 WorkBuddy 高效执行——先筑基，再联动，
这正是本书想带你走通的一条路。
时代背景：从印刷术到 AI，知识工作的范式跃迁
回顾近现代信息与知识领域的工具演进历程，印刷术解决了信息复制难题，个人电脑解决了信息处理难题，互联网解决了信息连接难题，智能手机解决了信息便携难题，生成式 AI 解决了信息生成难题。这五次工具革命贯穿同一条脉络：人类不断将自身的某种认知功能外化给工具，同时将自身价值推向更高阶的判断与创造层面。加拿大学者马歇尔 ? 麦克卢汉曾提出“媒介是人体的延伸”的观点，每一次技术革新都会淘汰低阶的重复性工作，同时催生新的高阶岗位与能力要求。在技术迭代中，人从未退场，只是职业重心持续迁移，逐步成为任务的定义者、质量的判断者与结果的责任人。
2025 年起，AI 行业发展迎来关键转折，Agent（智能体）成为行业公认的核心发展方向。尤其是在 2026 年初，OpenClaw 掀起一阵“全民养虾潮”。在此后不到半年的时间里，各类桌面 Agent 终端如雨后春笋般涌现，加速推动 AI从“对话式”向“任务式”转型。此前的对话式 AI 虽解决了“知道”的问题，却没有解决“做到”的问题。用户获取答案后，仍需手动复制、修改、排版、归档，全程依赖人工收尾。而 Agent 的交付成果不再只是单纯的文字建议，而是完整落地的任务成果：文件整理完毕，报告撰写完成，工作流程闭环落地。AI 的价值兑现方式从“人花时间把 AI 的答案转化为成果”，升级为“人用一句话指令，让 AI 直接交付成果”。
但 AI 工具形态的变革并不等于 AI 工具使用方式的同步升级。不少用户仍然将新一代 Agent 当作高级问答工具，保持“一问一答、用完即关”的使用习惯，然后感慨“Agent 也就那样”。想要纠正这一认知与使用的错位，需要建立一套全新的人机协作范式：人负责锚定应用场景、定义任务目标、提供核心素材、把控成果质量，AI 工具负责任务拆解、信息检索、内容生成，二者各司其职，精准配合。
能力套件：Agent+ 知识库 +Skill
本书围绕人机协作新范式的三大核心能力套件展开：Agent、知识库与 Skill（技能），三者分别对应人机协作体系的指挥层、知识层与执行层。Agent 以 WorkBuddy 为核心平台，它是 AI 办公任务从规划到落地交付的总指挥官。WorkBuddy 是腾讯推出的全场景 AI 办公工作台，可精准理解自然语言指令，自主拆解任务步骤、规划执行路径，能直接读取、创建和修改电脑本地的真实文档与文件夹，把 AI 的思考逻辑转化为真实可落地的产物。WorkBuddy 的核心能力体系以 Skill 为基本单元，搭配记忆系统、连接器、专属工作空间等功能，真正实现从“提供答案”到“把事做完”的能力升级。
知识库以 ima 为主力平台，它是腾讯推出的 AI 时代人机共用的智能知识管家，定位为“会思考的知识库”，集成文档解析、知识问答、内容创作等多元能力，支持多格式文档导入与三类知识库体系搭建，同时兼具 Agent 协同能力。ima 的出现，让个人“第二大脑”从被动存储的信息仓库，升级为可被人和 AI 共同调用的动态知识系统。
Skill 是 Agent 高效完成各类任务的核心载体，WorkBuddy 和 ima 都可加载对应的 Skill 来执行各类任务。Skill 把经过验证的工作方法沉淀为可复用的流程单元，让“一次做对的偶然”变成“次次做对的必然”。当 Agent 积累了足够的 Skill 时，就如同职场人拥有了肌肉记忆，团队建立了标准作业程序（Standard Operating Procedure，SOP），任务执行效率与输出质量将实现显著提升。
三者的关系可以概括为：Agent 是所有任务的总指挥官，对任务全程进行调度，并最终交付各类成果；知识库既可以给 Agent 提供任务所需的初始材料，也可以把 Agent 生成的成果沉淀下来；Skill 是 Agent 可调遣的专业数字员工或团队，负责高效执行委派任务，也需要从知识库中提炼所需知识，以持续升级自身能力。只有三者齐备，人机协作的新范式才能真正落地。
腾讯生态：适配国内用户的工具组合
WorkBuddy 与 ima 同属腾讯生态体系，本书选取它们作为核心工具，并非偶然。
微信是中文互联网最核心的信息流转与办公沟通载体，行业资讯通过公众号传播，工作指令通过对话、社群等方式发起。ima 与微信生态深度打通，公众号文章、微信群文件可一键存入个人知识库，将信息入库的摩擦力降到极低；WorkBuddy 通过微信助理将执行能力延伸至微信场景，用户在通勤等移动场景下也能派发任务、接收成果。
在办公协同侧，WorkBuddy 与 ima 已实现无缝连接，在 WorkBuddy 页面可完成对 ima 知识库的知识调用。同时，WorkBuddy 可通过标准化连接器原生对接腾讯文档、QQ 邮箱、腾讯问卷、腾讯会议、TAPD 等办公产品，全面覆盖文档协作、邮件沟通、调研收集、项目管理等核心办公场景。
同源的账号和数据体系让授权与联动开箱即用，ima+WorkBuddy+ 腾讯系其他产品，共同构成一套闭环式个人生产系统。对国内用户而言，腾讯生态意味着更低的入门门槛、更顺畅的数据流转和更符合日常工作习惯的使用体验。
阅读指引：“书 + 知识库”双轨学习模式
全书分为四部分，共 13 章。
第一部分为 ima 筑基篇（第 1 至 4 章），从软件安装、账户登录、页面基础认知入手，逐步介绍知识库的结构设计、内容筛选与高效入库方法，以及copilot 的使用技巧、知识流动逻辑，帮助读者搭建有序运转的个人知识管理体系。
第二部分为 ima + WorkBuddy 联动篇（第 5 至 7 章），从首个 AI 任务实操开始，全面介绍 WorkBuddy 能力全景图、场景锚定方法、精准指令撰写与技巧，实现任务交付的闭环，以及 ima 与 WorkBuddy“取—用—存”的高效联动。
第三部分为能力进阶篇（第 8、9 章），介绍 Skill 的使用、创建与迭代方法，帮助读者从单一Skill运用入手，进阶打造Agent专家团，搭建专属AI生产力系统。
第四部分为应用场景篇（第 10 至 13 章），聚焦职场人、咨询顾问、高校教师、自媒体人四大核心人群，配套可直接套用的指令模板、Skill 配置与专家方案等内容。
本书推出“书 + 知识库”双轨学习模式。为配套纸质图书，我们搭建了基于ima 的双工具实操专属知识库，这也是本书对人机协作新范式的一次创新实践：纸质图书提供体系化的方法论与典型的应用场景，在线知识库提供实时工具功能与交互式实操细节。
AI 工具的迭代速度不会放缓，但搭建一套可落地、可沉淀的人机协作体系，远比追逐单一工具的更新重要。希望你通过本书，将 AI 的使用模式从“对话式”升级为“任务式”，将 AI 的学习模式从“盲目功能摸索”升级为“精准任务配置”，在批量、专业、自动化的日常任务处理中，构建属于自己的 AI 时代人机协作新范式。
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孟凡云，从2022年开始，任百生智库（四川）有限公司副总经理，智库机构的首席研究员，深耕政策咨询近20年，在AI工具应用领域拥有大量的经验和实践案例。

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