Grok Bot vs Dots vs Muse: Which Agent Fits Developers in 2027?

Grok Bot (xAI), Dots (OpenAI), and Meta Muse launched within seven weeks of each other, and each is an always-on AI agent that keeps working after you close the chat. If you’re weighing Grok Bot vs Dots vs Muse, ask two things: which agent can take on your work with the safeguards you need, and how much control you keep. Grok Bot fits teams already on Cursor, Dots fits cross-app work through ChatGPT, and Muse fits personal tasks - but none of them documents model choice or an API for creating an agent from code.

Let’s explore how Grokbot, Dots, and Muse differ in how they start work, what they connect to, how they handle security and data, and what they cost for coding workloads. We’ll also compare them with Hermes Agent on DigitalOcean Managed Agents and Claude Duet. Product details are changing quickly, but this information is up to date as of October 28, 2026.

What are always-on AI agents?

Always-on AI agents run on their own persistent cloud computers instead of living inside a chat window, so they can work on a schedule or in response to events without requiring your input. Each one pairs a model with a cloud machine or microVM (a lightweight virtual machine). The microVM holds a browser, files, memory, and often a shell, while connectors, plugins-and in some cases Model Context Protocol (MCP) servers-grant the agent access to your tools. They act through your logins and connections, so what they can do depends on the access you grant. You assign work, review results, and approve actions from desktop, mobile, or messaging apps.

Hosted agents vs coding agents

Hosted agents work more like coworkers than services. You assign a task in the provider’s own app, they work on their own machine with the logins you grant them, and you review the results and approve sensitive actions.

As of October 28, 2026, neither Grok Bot nor Dots nor Muse documents a way to call one from code the way you’d call an API. The Grok API from xAI and the Meta Model API serve models, not the agents. Therefore, hosted agents also don’t replace a coding agent: Codex, Cursor, and Muse Code (Meta’s coding tool) are coding tools, and always-on agents sit alongside them, handling tasks around the code.

What is xAI Grok Bot?

Grok Bot is the always-on agent from xAI and Cursor, launched in beta on August 11, 2026. Each user gets a dedicated Firecracker microVM, but all of a user’s Bots share one computer, so Bots aren’t a security boundary from each other. Separate Bots organize work at the same trust level, and work that needs its own credentials requires a separate Cursor user. Connectors follow your team’s Cursor policy, and the computers run in the US.

Grok Bot key features:

• Bots can run commands on a member’s own computer when that’s enabled and approved, not just on their cloud computer.
• Bots work as a team: you can group two to six in one chat, and they run in parallel and hand tasks to each other, so you don’t have to relay work between them.
• Enterprise teams can set Ask first and Allow automatically rules that members can’t edit, plus audit logs, Action Recording (tool calls, shell commands, and browser navigations, kept for 90 days), and OpenTelemetry export.

Grok Bot pricing: Grok Bot is included with The X Subscription’s Premium, Super, and Ultra plans. Free and Plus don’t include it.

• Premium - $30/month or $25/month billed annually ($300/year). Includes Grok Bot with 4x the base weekly usage, shared across Grok, Grok Bot, and Cursor.
• Super - $100/month or $84/month billed annually ($1,000/year). Includes Grok Bot with 15x the base weekly usage.
• Ultra - $200/month or $167/month billed annually ($2,000/year). Includes Grok Bot with 50x the base weekly usage.
• Enterprise - Contact sales for pricing. Admins must enable Grok Bot.

What is Open AI Dots?

Dots is the always-on agent from OpenAI inside ChatGPT, where each agent is referred to as a ‘dot’. It is powered by GPT-6 Astra, launched September 29, 2026, and is built for general work across your connected apps and projects. You can create a dot in the ChatGPT mobile app, the desktop app, or a desktop browser and message it in Slack. For cloud coding work, it uses a Codex cloud environment you’ve already created.

OpenAI Dots key features:

• Custom Rules set how much a dot does without asking. Some sensitive actions, like changing passwords, are left to you.
• Each dot runs on its own sandboxed computer, unlike Grok Bot, where all of a user’s Bots share one.
• Plugins connect your dot to 4,000+ apps, and a plugin can bundle MCP servers-so one install can add several tools.

Dots pricing: Dots are included with ChatGPT Pro and Business Premium, and with Enterprise once a workspace admin turns them on. Access is rolling out gradually, and Pro access is limited to users over 18 outside the EEA, UK, and Switzerland.

• There is no free tier. Chatting with your dot is free of usage limits, but tasks it starts in Work or Codex count toward those products’ limits.
• ChatGPT Pro - from $100/month. Includes your first dot.
• Business Premium - $125 per user per month, or $100 billed annually. Includes a dot.

What is Meta Muse?

Muse is the always-on agent from Meta, launched September 8, 2026, and it was built first for personal tasks, with a small business version now also available. Access it via the Muse app, muse.​ai, or WhatsApp. It runs on a dedicated Secure VM, and a separate agent called ‘Sentinel’ approves anything that reaches the internet. Muse is available in the US and Canada, and developers can use Muse models through the Meta Model API and Muse Code.

Meta Muse key features:

• Muse checks out purchases with Link by Stripe, which uses one-time-use cards to keep your real card details hidden, and Meta says it’s the first AI agent covered by Link’s purchase protections.
• You choose which apps Muse connects to and how much access each gets, such as letting it read your email without sending on your behalf.
• Muse keeps an audit trail of what it has done and plans to do, and asks before sensitive actions like sending an email or making a purchase.

Muse pricing:

• Free. Includes Muse with a usage limit.
• Power - $20/month. 500 million weekly tokens.
• Maximum - $100/month. 3 billion weekly tokens.

Grok Bot vs Dots vs Muse at a glance

Pricing and feature information in this article are based on publicly available documentation as of October 28, 2026 and may vary by region and workload. For the most current pricing and availability, please refer to each provider’s official documentation.

When to use Grok Bot vs Dots vs Muse

Choosing the right agent depends on what tasks you want to hand off:

Coding and repo work

Grok Bot is the option built around Cursor’s cloud. A developer on a Cursor team can ask a Bot to set up a nightly routine that runs the project’s checks in its shell and hands any failures to a Cursor Cloud Agent, and it already runs in Cursor Cloud under the same team policies. Flavio Copes, a developer and educator, runs a daily Grok Bot routine on his site that selects 10 posts with out-of-date version claims and passes them to a Cursor Cloud Agent. The agent returns one pull request for the ten files, and the Bot posts a one-line summary. In two days, it produced three merged pull requests, which he describes in his Grok Bot guide.

Dots covers the cross-app work around the code: it can send you a morning digest of the review requests waiting on you, build and test a small fix itself, and hand larger work to Codex while you review the result.

Muse is built for personal tasks rather than repo work, so developers who want to build on Meta’s models can use the Meta Model API and Muse Code instead.

For repo work, Grok Bot has the edge on a Cursor team, and Dots has it if you live in ChatGPT.

Every day work and personal tasks

Dots is the worker option. If you get a steady stream of requests by email and Slack, it can brief you each morning in an app like Slack.

Muse is the personal option. Suppose you want help with errands outside of work, such as reordering household items and drafting replies to personal email. Use Muse to execute this all from WhatsApp, with approval before sending or paying.

Grok Bot is the multi-agent option. If a job takes several steps, you can group Bots so one researches, one drafts, and one reviews, with outgoing email and Slack messages waiting as drafts for your approval.

Developer integration

Comparing Grok Bot vs Dots vs Muse, none documents an API for creating or messaging the agent itself, though Grok Bot routines can start from a webhook, Slack, or events such as Sentry and PagerDuty alerts.

On connectors, Grok Bot reaches the MCP servers your team’s connector policy permits, Dots plugins can bundle MCP servers, and Muse supports custom connectors, with MCP support for the consumer agent not stated.

Only Muse’s models and Grok Bot’s admin settings have documented APIs, and a Grok Bot routine webhook is the one documented way to trigger a run from your own code.

Security and data handling

Dots, Muse, and Grok Bot all share the same main security habit: give each agent only the access a task needs, and keep consequential actions behind approval. On isolation, Grok Bot separates users but not a user’s own Bots, Dots gives each dot its own sandboxed computer you can inspect, and Muse runs a Secure VM with Sentinel approving internet access. Meta says a Confidential VM is coming later in 2026, and a recent Meta security post says the current Secure VM “does not prevent Meta from accessing data when necessary to support, secure or operate the service.”

On training, Muse trains on your interactions by default after sanitizing personal information, with an opt-out in Muse settings. In Grok Bot, customer data isn’t used for training when Privacy Mode is on, and Privacy Mode (Legacy), a Cursor team setting, blocks Grok Bot entirely. OpenAI doesn’t train on Business and Enterprise content by default, and on personal plans your data controls decide.

Grok Bot Enterprise teams get audit logs, Action Recording, and OpenTelemetry export. Enterprise admins can pull dots records through the Compliance API, and Meta documents an activity log for individual users but no team audit logs as of October 28, 2026. Check each provider’s data use and retention terms before you connect work accounts.

Cost for coding workloads

Coding workloads run long, make many tool calls, and use more compute than a typical chat, and all three count usage against a plan allowance, so longer tasks may use it up faster.

Grok Bot usage resets weekly with no separate spend cap. Dots chatting doesn’t count against your limits but its deeper work draws on a plan allowance-tasks a dot starts in Codex or ChatGPT Work count toward those products’ limits. Muse plans reportedly cap usage by weekly tokens.

How to choose between Grok Bot, Dots, and Muse

Always-on agents solve different problems, and the right one depends on which of these situations is true for you:

• If you’re a solo builder, pick the agent whose plan you already pay for. If you already pay for ChatGPT Pro, Dots is included, but you reach it through ChatGPT, Slack, or Teams-not from code.
• If your team is on Cursor, Grok Bot is a natural starting point because it uses the same account and team policies as Cursor. Plan around the shared computer, since Bots on one account aren’t a security boundary from each other.
• If you want an assistant for your own life, Muse is built for it, though it trains on your interactions by default unless you opt out.
• If you need to choose the model, consider additional options like Hermes Agent on DigitalOcean Managed Agents, where you pick from 85+ models or Bring Your Own Model (BYOM).
• If you need to create and control agents from your own code, neither Grok Bot, Dots, or Muse documents an API for creating or messaging an agent, while Hermes starts from doctl, the API, webhooks, and cron. The trade-off is more setup on your end.

A path you control: Hermes on DigitalOcean Managed Agents

Hermes Agent on DigitalOcean Managed Agents is an open-source agent from Nous Research that runs on Harness Runtime, the managed environment that hosts each agent session, and opened in public preview in September 2026. It is designed as a developer-controlled option by comparison to Grok Bot, Dots, and Muse, since DigitalOcean runs the infrastructure and integrates the connectors and models for you. Each session runs in its own Firecracker microVM in one region (RIC1), and the agent acts according to the access you grant.

DigitalOcean doesn’t use your content to train, fine-tune, or improve generalized AI models, though any third-party model provider you connect has its own data-use practices. The trade-off is that you initially configure and operate Hermes Agent yourself, so the scope of access you grant is yours to manage. Note that an agent that can use a credential can also read it in its sandbox.

Hermes is suited to developers who want control. Say your platform team wants an agent that wakes on a webhook when an alert fires, looks up the related issue in Jira and the error in Sentry through Action Gateway, and posts a summary for an engineer to approve before anything changes. Hermes starts from webhooks and schedules, reaches those tools through one endpoint, runs on a model your team picks, and is controlled from doctl and the API.

Hermes Agent on DigitalOcean Managed Agents key features:

• Action Gateway gives the agent 16,000+ tools through one managed MCP endpoint, plus your own servers, and is designed to keep credentials out of the model’s context.
• You choose the model from DigitalOcean’s catalog of 85+ open-source models or BYOM.
• Start and control sessions from doctl, the control panel, and the API, and Harness Runtime supports scheduled and webhook triggers.

Hermes Agent pricing:

• $0.044 per vCPU-hour for CPU
• $0.0095 per GB-hour for memory
• $0.126 per hour for the default 2 vCPU, 4 GB session at full use
• $0.05 per GiB-month for session storage
• Free Trial - $5 credit for new customers. Lets you try Hermes on your own repo.
• Pro - $50/month. Includes a $50 plan credit with 15% off usage.
• Team - $200/month. Includes a $200 plan credit with 20% off usage.

For a self-hosted alternative on a plain server, deploy OpenClaw, another open-source agent, on a Droplet® with the 1-Click OpenClaw App. You can also run multiple OpenClaw agents at once on App Platform. For another self-hosted agent stack, read our NemoClaw setup tutorial.

Claude Duet, a newer option

Claude Duet is the always-on agent from Anthropic, opened as a research preview on October 21, 2026-after Grok Bot, Dots, and Muse launched. It runs on its own cloud computer with a browser. You assign work by text or voice in one ongoing thread in its iOS and Android apps or on claude.​ai, and it messages you first, starting with a morning brief across your connected apps through more than 6,000 connectors and plugins. As with the other always-on agents, it asks for approval before sensitive actions such as sending messages, paying, signing documents, and deleting anything, and Anthropic says it doesn’t see your passwords or sign-in tokens directly.

It is still an early preview. Access is a waitlist for Pro and Max subscribers in the US, Team and Enterprise aren’t included, and it shares your plan’s usage limits-including for its background checks-as of October 2026. It is another worker option, best for morning briefs and follow-ups via email, Slack, and other connected apps.

Grok Bot vs Dots vs Muse FAQs

Which AI bot is the best right now?

It depends on what you want to hand off. Grok Bot suits teams on Cursor that want several Bots to work a job together, Dots suits steady cross-app work through ChatGPT, and Muse suits personal tasks. If you need model choice and control from code, Hermes Agent on DigitalOcean Managed Agents is the developer-controlled option.

What is the difference between Meta Muse and OpenAI Dots?

Muse is built first for personal tasks like shopping and email, while Dots is built for general work across your connected apps and projects inside ChatGPT. Muse trains on sanitized interactions by default unless you opt out, and Dots doesn’t train on Business and Enterprise content by default. Neither documents a developer API for the agent itself, so if you need to start an agent from code, check out Hermes Agent on DigitalOcean Managed Agents.

How do I run an always-on AI agent on a cloud VM?

On DigitalOcean Managed Agents (in public preview), Hermes runs each session in its own Firecracker microVM, and you start and control it from doctl, the control panel, the API, webhooks, or a schedule. If you’d rather use a plain server, deploy OpenClaw on a Droplet® with a 1-Click Application, though that route is more hands-on.

How do I manage secrets and API keys for autonomous agents running in the cloud?

Give the agent only the access each task needs, and keep consequential actions behind approval. On DigitalOcean Managed Agents, Action Gateway gives the agent tools through one managed MCP endpoint designed to keep credentials out of the model’s context, though DigitalOcean notes that an agent that can use a credential can also read it in its sandbox. Any third-party model provider you connect has its own data-use practices.

How much does it cost to run an AI agent 24/7 in the cloud?

On DigitalOcean Managed Agents, a 2 vCPU, 4 GB session costs $0.126 per hour at full use, billed per second of active compute, so CPU is charged only for what the agent actually uses. Pausing a session stops compute charges while storage charges continue, and inference and metered tools are billed separately. Plans start with a Free Trial ($5 credit for new customers), then Pro at $50 per month with 15% off usage.

Run your own always-on agent on DigitalOcean Managed Agents

DigitalOcean Managed Agents runs a range of agents on managed infrastructure that you control from doctl and the API. Each session runs in its own Firecracker microVM, and Action Gateway provides your agent with tools via a single managed MCP endpoint, designed to keep credentials out of the model’s context. Managed Agents is now in public preview.

Key features include:

• Choose from 85+ open-source models or bring your own provider
• Start work from doctl, the control panel, a webhook, or a schedule
• Reach 16,000+ tools through one MCP endpoint, plus your own servers
• Pay for the CPU your agent actually uses with per-second active CPU billing
• Pause a session to stop compute charges, with storage charges continuing

Get started with Managed Agents today ->

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