The direct answer
Cue is a new standalone Manus app for a personal team of agents. Manus says each agent can have its own email address, phone number, wallet and computer, and that agents can pass work to one another around a shared goal. Cue is in early access, so the sensible response is neither to treat it as just another chatbot nor to hand it broad authority on day one. Start with a bounded, reversible job; decide which data, tools and spending limits are necessary; and keep a human responsible for the final decision.
Chat interfaces give answers. An operational agent raises one question: is its authority clear, inspectable and interruptible?
Manus describes Cue as an early-access web, desktop and mobile app. Its example is a three-agent team for venue research, a shortlist and a recommendation deck. The Manus 2.0 announcement is the primary source; The Next Web’s launch coverage independently describes the identity model and early-access status.
What Cue changes: from a single answer to a delegated workflow
Cue gives an agent team a persistent operational role: task-related email, phone-based summaries, work on a computer, payments within a user-set budget and group-chat hand-offs.
Those capabilities create real-world side effects when messages, bookings or sensitive documents are mishandled.
The important distinction: identity is not unlimited authority
An email should not silently mean “contact anyone”; a wallet should not mean “spend without a ceiling or confirmation”; and a computer should not mean “open every file or use every logged-in session.” The same lesson appears in our analysis of OpenAI’s Astra safety release gate [blocked]: capable systems make authority design more important, not less.
How to get Cue early access
Manus says Cue is currently early access and requires an invitation code. Its public launch post directs prospective users to Cue and says that MEETCUE is a limited, first-come, first-served code for early users. The Manus Help Center also says existing Manus users can open the Agents (Cue!) tab in the sidebar, scan the QR code to download the app and enter an invitation code when signing in.
Availability, code capacity and platform requirements can change, so use the official Cue site and Help Center rather than reposted codes or screenshots.
Three good first jobs for a Cue agent team
The launch examples point to a sensible team pattern: research, shortlist, then recommendation. That works because each stage can be made visible and reviewed.
What the public Cue example gallery adds
The Cue example gallery shared with this brief shows the product being positioned around practical requests: compare monthly cost per customer in Google Ads versus Meta and produce a budget recommendation; turn event business cards into a spreadsheet, enrich public company details and draft follow-ups; find travel options; monitor a threshold and alert a user; prepare a family, school or household task; and help with bookings or recurring bills. These are illustrative product examples, not evidence that any task will be completed correctly, safely or without human review.
They are useful precisely because they expose different authority levels. A read-only marketing report and an alert on a spend threshold are good first candidates. Creating a contact file or a follow-up draft needs data minimisation and a human send review. Booking travel, paying parking, renewing a domain, changing an advertising budget, handling medical information, insurance, credit-card records or a school form can have financial, legal, privacy or welfare consequences. Those cases require tighter permissions and explicit confirmation—not a longer prompt.
1. Research and evidence collection
Give one agent a narrow question, a defined source policy and an output format. For example: collect venues that meet a published location, date, capacity and accessibility brief. The agent can return sources, constraints and gaps. It should not silently agree terms, enter a contract or share confidential details.
2. Shortlist and comparison preparation
A second agent can turn the first agent’s evidence into a comparison table: options, price conditions, cancellation terms, contact details, evidence links and unresolved questions. The point is not to automate taste. It is to expose trade-offs before a human chooses.
3. Recommendation deck or brief
A third agent can create a decision-ready draft that clearly labels facts, assumptions and missing data. This is a productive use of multi-agent hand-off because the final human reviewer can see where each conclusion came from and challenge it before an external action is taken.
For B2B teams, the equivalent is research public account facts, prepare a qualified account brief, then create an internal recommendation—not unreviewed outreach or CRM, bid or public-claim changes. Our guide to agentic AI for GTM workflows [blocked] explains why bounded tasks and named hand-offs are a stronger starting point than an autonomy claim.
Edge cases that matter before you delegate more
The most useful Cue conversation is not a feature checklist. It is a set of edge cases that clarify where a workflow needs a stop sign.
A phone call can create an identity and consent problem
If an agent takes or returns a call, recipients should understand who or what they are interacting with and what the agent is authorised to say or do. A summary may omit tone, context or a commitment that a person would notice. For important conversations, require a transcript or recording where lawful, an escalation rule, and a human approval before the agent makes a material promise.
Email can turn research into representation
An email draft is low risk. Sending it can be consequential. The recipient may rely on it, forward it, or respond with confidential information. A robust first policy is draft-only external communication: the agent can prepare a message and a recipient rationale, but a person approves the final recipient, wording and send action. This is particularly important for customer support, commercial negotiations, regulated communications and recruitment.
A wallet needs boundaries beyond a number
A budget is a helpful control, but it is incomplete on its own. A useful payment policy defines the maximum amount, permitted merchants or categories, repeat-purchase rules, cancellation conditions and explicit-confirmation steps. A payment within budget can still be wrong on date, location, quantity or terms.
A computer can inherit more access than the task needs
A machine may contain logged-in accounts, browser sessions, documents and password-manager prompts. Use a dedicated environment and approved applications where possible, grant only task-necessary data, and remove access after completion. A restaurant search should not create a path to unrelated files or settings.
Agent hand-offs can magnify an early error
A team can make progress quickly, but it can also turn a mistaken assumption into a polished recommendation. Ask each hand-off to preserve the evidence it received, identify assumptions and label uncertainty. A downstream agent should not treat an upstream summary as a verified source without checking the relevant link or record.
QR codes and physical-world tasks need extra caution
Manus gives restaurant ordering or holding a place in line as an everyday Cue example. QR-code flows can lead to the wrong venue, a spoofed page, a changed menu or an unexpected payment screen. For any physical-world transaction, check the destination, merchant and totals before approval. Treat a QR code as a link to inspect, not proof that the next action is safe.
A practical authority envelope for Cue
Before creating an agent team, write a short authority envelope for the exact job:
- Purpose: What outcome is this team allowed to pursue?
- Inputs: Which accounts, files, contacts or public sources may it use?
- Actions: What may it draft, research, compare, message, book or purchase?
- Limits: What is the spending ceiling, time window and data sensitivity boundary?
- Approvals: Which external messages, commitments, payments, record changes or public actions require confirmation?
- Evidence: What receipt, log, source list or summary must it return?
- Stop rule: When should the agent pause and ask rather than infer?
This is not bureaucratic overhead. It is how a user retains agency when a system can do more than generate text. The same principle informs our explanation of contextual authority for AI agents [blocked]: access should be tied to a task and its context, not granted as a standing blank cheque.
How Cue compares with the ChatGPT, Claude, Gemini and Grok conversation
ChatGPT, Claude, Gemini and Grok remain powerful thinking and creation partners. They support research, analysis, writing, coding and many forms of tool-connected work. Cue is interesting because Manus is explicitly framing a personal agent team around operational identities and hand-offs: not only “give me a response,” but “keep this outcome-oriented task moving across a team.”
That is product framing, not proof of a universal capability or safety ranking. Compare tools at the workflow level: job, data and authority needed, approvals, review and stop mechanisms, and the action record.
For a related view on whether agents change the software layer itself, see Will AI Kill SaaS or Just the Interface? [blocked]. For the larger strategic question of increasingly capable AI systems, our AGI implications guide [blocked] separates present operating decisions from speculative timelines.
What business leaders should do this week
Start with one repetitive, bounded task with a visible definition of good work. Assign an owner, set source, data, tool and action boundaries, then define review and stop rules. Expand one permission at a time only if the pilot produces a better brief, shortlist or decision record.
Teams that need help designing a controlled first agent workflow can start with Integrated.Social’s Agentic AI service [blocked] or request a free AI growth audit [blocked]. The goal is a defined evidence, measurement and governance review—not a promise of autonomous performance, compliance, revenue or AI-search visibility.
About the Author
Modi Elnadi is the founder of Integrated.Social, a London-based growth marketing consultancy working across AI visibility, SEO, PPC and governed agentic-AI workflows. His approach is evidence-led: test a bounded use case and expand only where the evidence and controls justify it.
Frequently Asked Questions
How can I join Cue by Manus early access?
Go to Cue or open the Agents (Cue!) tab in the Manus sidebar. Manus says Cue is early access and requires an invitation code; its launch post lists MEETCUE as a limited, first-come, first-served code. If capacity, device support or the code changes, follow the current instructions on the official Cue site and Manus Help Center.
What is Cue by Manus?
Cue is a standalone Manus app for a personal team of agents on web, desktop and mobile. Manus says each agent can have an email address, phone number, wallet and computer, and a team can share work around a common goal while the user sets direction and makes the final decision.
Can a Cue agent spend money without approval?
Manus says Cue agents can pay within a budget set by the user. A budget alone is not a complete safety policy. For any material transaction, set a spending ceiling, permitted merchants or categories, confirmation rules, cancellation checks and a clear record of what the agent did. Review the current product controls and terms before enabling payments.
Can Cue agents send emails or take calls?
Manus says agents can have their own email and phone identities, and can take calls and leave a summary in Cue. Before enabling external communication, decide whether the agent may draft only or send messages, what it may disclose, who may be contacted, and which conversations must escalate to a person.
How should I test a personal AI agent team safely?
Choose a bounded, reversible workflow such as research, shortlist preparation or drafting an internal recommendation. Give the team minimum necessary access, name an accountable human owner, set approval points for external actions and payments, require evidence with each hand-off, and define when the team must pause for review.
Is Cue better than ChatGPT, Claude, Gemini or Grok?
The public launch materials position Cue differently: as a personal team of agents with operational identities and hand-offs. That does not establish a universal capability or safety ranking. Compare tools against the workflow, permissions, integrations, available controls, record of actions, approval mechanism and applicable terms—not a single feature list.
