三个 AI 同事：谁在卖省心，谁在卖好看，谁在卖可控
前几天有人在群里发了一段演示：一个人在聊天窗口里指挥一排 bot——一个拆需求，一个写代码，一个跑测试，一个验收。字幕打着「一个人，一支研发团队」。
我打开官网准备下单。
三个域名，全部 000 超时。x.ai、docs.x.ai、api.x.ai，一个都没通。
这条路从一开始就不是给这边的人准备的。但这不重要。重要的是那段演示里有一个词是假的——「团队」。
我把三个东西拆开看了一遍：Grok Bot、它的开源替代 MausBot、还有我天天泡在里面的 Hermes。看完的结论是三句话：
一、它们根本不在同一层，比「谁更强」是问错了题； 二、「AI 团队」这个词，三个都配不上； 三、真正稀缺的不是会写代码的 bot，是那个敢签字的人。
一、先把桌子摆对：三个东西不在同一层
大部分对比文章一上来就列表格比参数，这是错的。因为这三个东西压根不是同类项。
产品层（给你体验） Grok Bot MausBot
都是「AI 同事」成品，非工程师直接用
────────────────────────────────────────────────────────
运行时层（给你造东西） Hermes
是 agent 基础设施，你用它搭系统
Grok Bot 和 MausBot 卖的是一个已经装好的东西：你打开，里面有一排 bot，你跟它们聊天，它们干活。
Hermes 卖的是一套零件：你自己决定分成几个角色、每个角色用什么模型、谁来验收、失败了怎么重试。
所以正确的问法不是「哪个更强」，是：
你要买一个成品，还是要一套能搭成品的底座？
这两件事的评判标准完全不同。成品看体验，底座看可编程性和可观测性。
二、运行机制：它们各自在干什么
Grok Bot：云端黑盒，一台共享电脑
手机/桌面 app 里跟 bot 聊天
→ 消息进 xAI 后端
→ bot 在【共享云电脑】上执行（浏览器 / 终端 / 文件）
→ 结果回到消息流
它是 xAI 的产品，形态是一个消息应用里的一排 bot，每个 bot 是一个独立 agent，像聊联系人一样跟它们说话。
按第三方逐项对比文档（OpenMausBot 2026-08-23 发布、10-02 更新）的记载：
| 维度 | 事实 |
|---|---|
| 执行位置 | xAI 云端 |
| bot 的电脑 | 所有 bot 共用一台 |
| 模型 | 只有 Grok，不可换 |
| 触发 | 你说话；外加「看你操作学流程」后自动跑 |
| 持续运行 | 云端保障，关电脑继续跑 |
| 数据 | xAI 服务器 |
| 价格 | 含在 SuperGrok（$30/月）、Cursor Pro（$20/月）及更高档，另有周用量上限 |
| 可改 | 不能，专有 |
「共享一台电脑」这一条，是整个产品最要命的架构选择。后面再说为什么。
MausBot：一个漂亮的壳，底下是你的 Claude
Electron 桌面 app（侧边栏一排 bot，像微信联系人）
→ 每个 bot 底下是一个 CLI 子进程：Claude Code 或 Codex
→ agent 在你的电脑 / 或它给的云桌面上执行工具
→ 结果回到聊天流
MausBot（仓库叫 OpenMausBot，5,608 星，数据截至 2026-10-26；Apache-2.0，TypeScript + React 19 + Electron，macOS 签名公证、Windows x64、Ubuntu 24.04，另有手机 app）。
关键事实：它自己不含模型。它是一个壳。 你必须先自己装好并登录 Claude Code 或 Codex——它官方引导流程的原话是「install and sign in to one supported agent, such as Claude Code or Codex」。
| 维度 | 事实 |
|---|---|
| 底层引擎 | Claude Code / Codex（不是自研） |
| 模型 | 跟你的 Claude / ChatGPT 订阅走，或自带 key |
| bot 的电脑 | 免费版 = 你自己的电脑；付费版 = 每 bot 一个云桌面，可实时看屏、可接管 |
| 数据 | 免费版本地 ~/.openmausbot；云计划在它服务器 |
| 价格 | 免费 $0（电脑开着才跑）／Starter $15（always-on，100 computer-hours/月，2 vCPU 2GB）／Pro $49（300 hours） |
| 应用集成 | Gmail / GitHub / Notion + 数百个，2,000 app events/天（付费档） |
| 附加 | 手机端推送、语音通话（用你的 OpenAI key）、定时 automation |
这个设计很聪明：它赌的是你已经有 Claude 或 ChatGPT 的订阅。你已经付过的钱，它帮你榨出更多价值。
Hermes：一个能编程的运行时
入口：CLI / TUI / Electron desktop / Web dashboard / 消息网关（Telegram、Discord、WhatsApp、微信…）
→ 一次运行 = 一个 agent loop（模型 ↔ 工具）
→ 工具在本地执行（二十多个内置工具集：web / browser / terminal / file / code_exec / vision / image_gen / skills / todo / memory / session_search / delegation / cronjob …）
→ 会话落 SQLite，记忆分三层，技能可复用
它和上面两个最大的区别，是多 agent 有两套机制：
第一套，父子进程。 父 agent 开子 agent，子 agent 的上下文是隔离的，只把摘要回传给父。适合「把一大坨脏活扔出去，只要结论」。
第二套，任务板。 一条命令生成整张图：
hermes kanban swarm "把目标做成能上线的东西" \
--worker pm:需求拆解 --worker dev:实现 --worker qa:测试 \
--verifier reviewer:验收 --synthesizer writer:汇总交付文档
底层是 SQLite：任务可依赖、可原子领取、崩溃可恢复，每个 profile 一个隔离工作区。
注意那个 --verifier。它不是装饰——它的意思是写代码的那个人不许自己说通过。
| 维度 | 事实 |
|---|---|
| 模型 | 任意 OpenAI 兼容：DeepSeek / Qwen / Claude / GPT / 本地 vLLM |
| 成本分层 | 可以按角色分模型：pm 用便宜的、dev 用贵的、reviewer 换第三家交叉验证 |
| 触发 | 手动 / cron / webhook / 消息网关 / kanban daemon |
| 数据 | 全本地 |
| 扩展 | MCP（既能接 MCP server，也能把自己当 MCP server 暴露）、plugin（git 安装）、skill、hooks |
| 价格 | 软件 0 元，只付模型费 |
| 无人值守 | cron + gateway + kanban daemon |
三、各自最锋利的那一刀
Grok Bot 强在三件事。
一是看你操作学流程。你演示一遍，它记下来，之后自动跑。这是 skill 的自动化生成，比手写 prompt 高明一个时代，也是它唯一真正领先的地方。
二是关电脑继续跑。不用养机器，不用管进程，云端替你扛。
三是生态捆绑。$30 的 SuperGrok 和 $20 的 Cursor Pro 都捎带上了它，用户获取成本极低。
MausBot 强在三件事。
一是每 bot 一台独立云桌面，可以实时看屏、可以接管。这是「信任」设计——你能看着它干，随时接手。Grok Bot 是共享电脑，做不到这一点。
二是零模型成本。它不卖模型，卖的是壳。
三是产品感。「把 bot 当联系人」这个界面隐喻，把复杂的 agent 编排藏得干干净净。
Hermes 强在三件事。
一是可编程、全透明。源码能改、日志能看、失败能复现。做生产系统，可观测性比智能重要得多。
二是真无人值守。cron + gateway + webhook + daemon 四件组合起来，是一个「能跑一年不用看着」的系统。上面两个都是「你得在旁边看着」的产品。
三是可私有化交付。你能把它装到客户机器上，数据不出门。这是做 B 端生意的前提。
四、缺点，一条不省
Grok Bot
| 优点 | 缺点 |
|---|---|
| 体验最成熟，零配置 | 只有 Grok，不能换模型——中文电商客服不如 DeepSeek，英文不如 Claude |
| 关电脑继续跑 | 所有 bot 共享一台云电脑——真做开发会互相踩 git、端口、依赖目录 |
| 学流程能力独一档 | 周用量上限，做重活会撞墙 |
| $30 打包，便宜 | 数据在 xAI 服务器，不可用于客户代码 |
| 手机端体验好 | 国内完全不可用（x.ai / docs.x.ai / api.x.ai 实测全部超时） |
| — | 不可私有化、不可改造、单一供应商锁定 |
MausBot
| 优点 | 缺点 |
|---|---|
| Apache-2.0，可改可分发 | 本质是壳——底层必须自己装 Claude Code / Codex，国内还得先解决这两个的访问和支付 |
| 免费版无限 bot、无限模型 | 免费版电脑开着才跑，关机即停 |
| 每 bot 独立云桌面 + 实时看屏 | 本质是单机桌面 app，不是服务器，7×24 生产不行 |
| $15 起就有 always-on | 没有编排：没有任务板、没有依赖、没有 verifier，多个 bot 靠你自己在聊天里协调 |
| 应用集成开箱即用 | 云计划数据在它服务器，2 vCPU / 2GB / 20GB 也偏小 |
| 手机 app + 语音 | 成本随「电脑小时数」线性涨，没有分层优化的空间 |
Hermes
| 优点 | 缺点 |
|---|---|
| 任意模型，可按角色分层控成本 | 没有「bot 花名册」式的 GUI——CLI/TUI 优先 |
| 真无人值守 | 学习曲线陡，非工程师用不了 |
| 多 agent 有 verifier 阶段 | 没有内置云电脑，机器自己出 |
| 数据全本地，可私有化 | 没有内置几百个应用集成，MCP 要自己配 |
| MCP 双向 | 没有「看操作学流程」，skill 靠手写或 agent 自己写 |
| 中文原生 | 多人协作弱（多 profile 不等于多人） |
五、成本账：分层才是真本事
| Grok Bot | MausBot | Hermes | |
|---|---|---|---|
| 软件 | $30/月（或 $20 Cursor Pro 附带） | $0 / $15 / $49 | $0 |
| 模型 | 含在订阅里，有周上限 | 你自己已有的 Claude/ChatGPT 订阅 | 按量自付 |
| 机器 | 免费（xAI 云） | $0（自己电脑）或含在 $15/$49 | 自己出 |
| 重活会不会撞墙 | 会，周限额 | 不会，但按小时烧钱 | 不会，但按 token 烧钱 |
| 能否分层降本 | 不能（只有一个模型） | 部分（每 bot 选模型） | 能（每角色一个模型） |
最后一行才是关键。
同样一个「产品→研发→验收」的项目，Hermes 可以这么配：
pm → DeepSeek（便宜，拆需求和写文档够用）
dev → Claude（写代码准，贵但值得）
qa → DeepSeek（跑测试、写报告）
reviewer → GPT（换一家交叉验证，避免同一个模型自我背书）
总成本大约是「全线用 Claude」的三分之一，而质量差别很小——因为贵模型只用在真正需要它的那一步。
Grok Bot 结构上做不到这件事。它只有一个模型。这是它最被低估的劣势：你没法让它「便宜的活便宜干」。
顺便说一个我自己踩的坑。我在这台 Windows 11 上实测：
$ time hermes -z "只回复ok两个字"
ok
real 0m22.383s
一个两个字的回复，22.4 秒。里面大部分不是模型慢，是启动和上下文装配的开销。所以这类东西不能塞进「每条消息同步等回复」的链路里——做客服、做实时回复，会死得很难看。它该站在后台：定时任务、批处理、复盘、无人值守。这也是我为什么一直说，通用 agent 干的是「慢但聪明」的活。
六、按场景选，别按参数选
| 场景 | 选谁 | 为什么 |
|---|---|---|
| 个人助理：日程、邮件、找资料、写东西 | MausBot（已有 Claude 订阅） | 开箱即用，手机端能用，$0 |
| 非技术人员要「一支 AI 团队」 | Grok Bot（能访问的话） | 体验最好，不用懂任何技术 |
| 7×24 自动化流水线（爬数据、巡检、告警） | Hermes | cron + webhook + gateway，另两个做不到 |
| 交付给客户的系统（B 端） | Hermes | 唯一能装到客户机器上、数据不出门 |
| 需要不同角色用不同模型 | Hermes | 另两个要么一个模型，要么没有编排 |
| 快速验证「AI 团队」这个想法 | MausBot 免费版 | 0 成本，先看看到底有没有用 |
| 学产品设计 | 两个成品都看 | 见下一节 |
七、三个共同的谎言
谎言一：它们都不是「团队」。
三个都是单人放大器，不是组织。没有真正的角色分工、交接制度、评审文化。
Hermes 的 kanban swarm 是最接近的——因为它强制有 verifier 阶段，不允许写代码的人自己说通过。但那也只是流程模拟，不是团队。团队的本质是责任可以被追究到具体的人，代码模拟不出来。
谎言二：都不解决「验收责任」。
verifier 是流程，签字的还是人。
客户投诉的时候，「是我的 AI 团队验过的」不是理由，是笑话。
谁能签字，谁收钱。 这条决定了这类工具的商业天花板——它们能把交付成本压到原来的三分之一，但压不掉那个必须签字的人，所以永远卖不出「替代一个团队」的价格。
谎言三：瓶颈都在你身上。
三个产品的共同瓶颈是同一件事：你的需求描述质量。
需求写得烂，AI 团队只会更快地产生更多垃圾。我见过的所有失败案例，根因都不是模型不行，是「要做什么」没说清。
所以：工具决定下限，你的需求描述能力决定上限。
八、结论
如果你只是想要个助理，MausBot 免费版就够了，它好看、免费、手机能用。
如果你想要「一整支 AI 研发团队」——先想清楚你要的是那个词，还是那个结果。要词的话，Grok Bot 的演示确实最漂亮，前提是你能用。
如果你想做的是别人的生产系统——卖给客户、装进别人的机房、跑一年不能出事——那就只剩一个选项。
Grok Bot 卖的是省心，MausBot 卖的是好看又免费，Hermes 卖的是可控。
你要做的是别人的生产系统，只能选可控的那个。
版权没有，随意转载。过意不去就加一句「原文发表于 cn-res.vip」，不加也无所谓。
A demo made the rounds last week: one person in a chat window, barking orders at a row of bots — one scopes the product, one writes the code, one runs the tests, one signs off. The caption read: one person, one engineering team.
I went to the site to buy it.
Three domains, all 000. x.ai, docs.x.ai, api.x.ai. Not one of them answered.
That path was never built for anyone on this side of the wall. But that's not the interesting part. The interesting part is that one word in the demo is a lie: team.
So I took the three things apart — Grok Bot, its open-source replacement MausBot, and Hermes, the one I live inside every day. Three conclusions:
First, they're not even in the same category. "Which is stronger" is the wrong question. Second, none of them deserves the word "team." Third, what's actually scarce isn't a bot that writes code. It's a human willing to sign.
One: Put the table right first
Every comparison post opens with a spec table. That's the wrong move, because these three aren't the same kind of object.
Product layer (an experience) Grok Bot MausBot
finished "AI colleagues" — no engineer required
──────────────────────────────────────────────────────────────
Runtime layer (a foundation) Hermes
agent infrastructure — you build with it
Grok Bot and MausBot sell you a thing already assembled. You open it, there's a row of bots, you talk to them, they work.
Hermes sells you parts. You decide how many roles, which model each role runs, who verifies, how failures are retried.
So the real question isn't "which is better." It's:
Are you buying a product, or a foundation to build products on?
Those are judged by completely different criteria. Products are judged on feel. Foundations are judged on programmability and observability.
Two: How each one actually runs
Grok Bot — cloud black box, one shared computer
You chat with a bot in the mobile/desktop app
→ message hits xAI's backend
→ the bot executes on a SHARED cloud computer (browser / terminal / files)
→ result comes back into the message thread
It's an xAI product: a row of bots in a messaging app, each an independent agent you talk to like a contact.
Per a third-party line-by-line comparison (OpenMausBot, published 2026-08-23, updated 10-02):
| Dimension | Reality |
|---|---|
| Where it runs | xAI cloud |
| The bot's computer | all bots share one |
| Models | Grok only, not swappable |
| Triggers | you talk to it; plus "learns a workflow by watching you" |
| Persistence | cloud-side, keeps working after you close the laptop |
| Data | xAI servers |
| Price | bundled into SuperGrok ($30/mo), Cursor Pro ($20/mo) and up, with its own weekly cap |
| Modifiable | no. proprietary. |
That shared computer is the single most consequential architectural choice in the product. More below.
MausBot — a pretty shell over your Claude
Electron desktop app (a sidebar of bots, like a contact list)
→ each bot is a CLI subprocess: Claude Code or Codex
→ the agent executes tools on your machine / or its cloud desktop
→ results land in the chat stream
MausBot (repo: OpenMausBot, 5,608 stars, Apache-2.0, TypeScript + React 19 + Electron; signed macOS, Windows x64, Ubuntu 24.04; plus mobile apps).
Critical fact: it contains no model. It's a shell. You first install and sign in to Claude Code or Codex yourself — its own onboarding says "install and sign in to one supported agent, such as Claude Code or Codex."
| Dimension | Reality |
|---|---|
| Engine underneath | Claude Code / Codex (not in-house) |
| Models | whatever your Claude / ChatGPT subscription gives you, or your own key |
| The bot's computer | free tier = your own machine; paid = one cloud desktop per bot, live screen, take over |
| Data | free tier local ~/.openmausbot; cloud tiers on their servers |
| Price | Free $0 (only while your computer is on) / Starter $15 (always-on, 100 computer-hours/mo, 2 vCPU 2GB) / Pro $49 (300 hours) |
| Integrations | Gmail / GitHub / Notion + hundreds more, 2,000 app events/day (paid) |
| Extras | mobile push, voice calls (your OpenAI key), scheduled automations |
Clever bet: it assumes you already pay for Claude or ChatGPT. It monetizes the subscription you've already bought.
Hermes — a runtime you can program
Entry points: CLI / TUI / Electron desktop / web dashboard / messaging gateways (Telegram, Discord, WhatsApp, WeChat…)
→ one run = one agent loop (model ↔ tools)
→ tools execute locally (20+ built-in toolsets: web / browser / terminal / file / code_exec / vision / image_gen / skills / todo / memory / session_search / delegation / cronjob …)
→ sessions in SQLite, three-tier memory, reusable skills
The real difference is that it has two distinct multi-agent mechanisms.
One: parent-child. A parent agent spawns children with isolated context; only summaries come back. Good for "throw this mess over the wall, I just want the conclusion."
Two: a task board. One command builds the whole graph:
hermes kanban swarm "ship this goal" \
--worker pm:scope --worker dev:build --worker qa:test \
--verifier reviewer:sign-off --synthesizer writer:package
Backed by SQLite: tasks can depend on each other, are claimed atomically, survive crashes, and each profile gets an isolated workspace.
Note the --verifier. It's not decoration. It means the person who wrote the code doesn't get to declare it good.
| Dimension | Reality |
|---|---|
| Models | any OpenAI-compatible: DeepSeek / Qwen / Claude / GPT / local vLLM |
| Cost layering | model per role: cheap for pm, expensive for dev, a third vendor for the reviewer |
| Triggers | manual / cron / webhook / messaging gateway / kanban daemon |
| Data | all local |
| Extension | MCP (consume servers, and expose itself as one), plugins via git, skills, hooks |
| Price | software $0, model usage only |
| Unattended | cron + gateway + kanban daemon |
Three: The sharpest edge each one has
Grok Bot — (1) learns a workflow by watching you. Show it once, it remembers, it runs it. That's skill generation by demonstration, a generation ahead of hand-written prompts, and it's the one thing it genuinely leads on. (2) keeps working after you close the laptop — no machine to babysit, no process to supervise. (3) ecosystem bundling — SuperGrok at $30 and Cursor Pro at $20 both carry it, so acquisition is nearly free.
MausBot — (1) one cloud desktop per bot, watchable and takeover-able. That's a trust design: you can watch it work and grab the wheel. Grok Bot's shared computer can't do this. (2) zero model cost — it doesn't sell models, it sells the shell. (3) product sense — "bots as contacts" hides an enormous amount of orchestration behind an interface anyone can use.
Hermes — (1) programmable and transparent: source readable, logs readable, failures reproducible. For production systems, observability beats intelligence. (2) genuinely unattended: cron + gateway + webhook + daemon compose into something that runs a year without supervision. The other two are products you watch. (3) deliverable on-premise: you can install it on a customer's machine and never move their data. That's the precondition for any B2B business.
Four: The downsides, none omitted
Grok Bot
| Upside | Downside |
|---|---|
| Most polished, zero setup | Grok only, no swapping — weaker than DeepSeek for Chinese support, weaker than Claude for English |
| Runs after you close the laptop | All bots share one cloud machine — real dev work stomps on git state, ports, dependencies |
| Workflow learning is unique | Weekly usage cap — heavy work hits the wall |
| $30 bundled, cheap | Data on xAI servers — unusable for client code |
| Good mobile experience | Unreachable from mainland China (all three domains timed out in my test) |
| — | No on-prem, no modification, single-vendor lock-in |
MausBot
| Upside | Downside |
|---|---|
| Apache-2.0, modifiable, redistributable | It's a shell — you must already run Claude Code / Codex, which in China means solving access and payment first |
| Free tier: unlimited bots, any model | Free tier only runs while your computer is on |
| Per-bot cloud desktop with live screen | It's a desktop app, not a server — no 24/7 production |
| Always-on starts at $15 | No orchestration: no board, no dependencies, no verifier. You coordinate bots by talking to them |
| Integrations out of the box | Cloud tiers keep data on their servers; 2 vCPU / 2GB / 20GB is thin |
| Mobile apps + voice | Cost scales linearly with computer-hours, with no layering to optimize |
Hermes
| Upside | Downside |
|---|---|
| Any model, cost layered by role | No "roster" GUI — CLI/TUI first |
| Truly unattended | Steep curve, non-engineers can't use it |
| Multi-agent with a verifier stage | No built-in cloud computer — supply your own |
| Local data, on-prem delivery | No hundreds of pre-built integrations — configure MCP yourself |
| MCP both directions | No "watch me and learn" — skills are written, not demonstrated |
| Native Chinese | Weak at multi-human collaboration (multiple profiles ≠ multiple people) |
Five: The cost math — layering is the real skill
| Grok Bot | MausBot | Hermes | |
|---|---|---|---|
| Software | $30/mo (or bundled with $20 Cursor Pro) | $0 / $15 / $49 | $0 |
| Models | included, weekly cap | your existing Claude/ChatGPT sub | pay per use |
| Machine | free (xAI cloud) | $0 (your PC) or included at $15/$49 | your own |
| Does heavy work hit a wall? | yes, weekly cap | no, but bills by the hour | no, but bills by the token |
| Can you layer costs? | no (one model) | partly (model per bot) | yes (model per role) |
That last row is the whole game.
For the same product → build → verify cycle, Hermes can be configured like this:
pm → DeepSeek (cheap; scoping and docs are easy work)
dev → Claude (writes correct code; expensive but worth it)
qa → DeepSeek (runs tests, writes reports)
reviewer → GPT (different vendor, so the same model can't rubber-stamp itself)
Roughly a third of the cost of running Claude everywhere, with almost no quality gap — because the expensive model only runs where it matters.
Grok Bot structurally cannot do this. One model. You can't let cheap work be done cheaply. That's its most underrated weakness.
One data point from my own machine (Windows 11):
$ time hermes -z "reply with just ok"
ok
real 0m22.383s
Two characters out, 22.4 seconds round trip. Most of that is startup and context assembly, not the model. Which is exactly why this category of tool cannot sit inside a per-message synchronous path. Put it in customer support and it dies ugly. It belongs in the background: scheduled jobs, batch processing, retrospectives, unattended runs. That's what general-purpose agents are for — the slow, smart work.
Six: Choose by scenario, not by spec sheet
| Scenario | Pick | Why |
|---|---|---|
| Personal assistant: calendar, email, research, writing | MausBot (if you already pay for Claude) | Instant, works on your phone, $0 |
| A non-technical person who wants "an AI team" | Grok Bot (if reachable) | Best experience, zero technical knowledge needed |
| 24/7 automated pipelines (scraping, monitoring, alerting) | Hermes | cron + webhook + gateway; the other two can't |
| A system you deliver to clients (B2B) | Hermes | The only one you can install on a customer's machine with data staying put |
| Different roles on different models | Hermes | One has a single model, the other has no orchestration |
| Testing whether "AI team" is even useful | MausBot free | Zero cost, find out before you commit |
| Learning product design | both products | See next section |
Seven: Three lies they all tell
Lie one: none of them is a team.
All three are one-person amplifiers, not organizations. No real division of roles, no handoff discipline, no review culture.
Hermes's kanban swarm is the closest thing — it forces a verifier stage so the author can't sign off on their own work. But that's a simulated process, not a team. The essence of a team is that responsibility can be traced to a specific human. You can't simulate that in code.
Lie two: none of them solves acceptance responsibility.
The verifier is a process. The signature still comes from a person.
When a client complains, "my AI team verified it" isn't a defense. It's a punchline.
Whoever can sign, gets paid. That caps the business model of every tool in this category: they can cut delivery cost to a third, but they can't remove the person who signs — so they can never charge as if they replaced a team.
Lie three: the bottleneck is you.
All three share the same bottleneck: the quality of your requirements.
Write bad requirements and an AI team just produces more garbage, faster. Every failure case I've seen traced back not to a weak model but to "we never said what we wanted clearly."
So: the tool sets your floor. Your ability to specify sets your ceiling.
Eight: Conclusion
If you just want an assistant, the MausBot free tier is enough — pretty, free, works on your phone.
If you want "a whole AI engineering team," decide first whether you want the phrase or the result. For the phrase, Grok Bot's demo is genuinely the prettiest, assuming you can reach it.
If what you're building is someone else's production system — sold to a client, installed in their datacenter, expected to run a year without an incident — there's exactly one option left.
Grok Bot sells peace of mind. MausBot sells pretty and free. Hermes sells control.
You're building other people's production systems. You can only pick control.
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