Three consumer agent products show up often next to trading talk — Grok Bot, Meta Muse and Manus Cue — so this hub uses them as named hooks, not as a claim about search rankings. None of them is a perps product. They are general-purpose agents, and traders keep asking what happens when an agent like that meets a leveraged market. This post defines the term, walks through the five jobs an agent takes on, and says plainly what each product's official materials do and do not claim.

Agentic trading on perps means a software agent, usually built on a language model, takes part in trading perpetual futures: it reads market data, forms a view, places or stages orders, and operates under permissions a human granted. The market does not change because the trader is software. Funding, margin and liquidation apply the same way.

What is an AI agent?

A chatbot answers a question. An agent is given a goal and a set of tools, and it takes several steps toward that goal on its own, checking in with you at points you define. The word covers a wide range, from a research helper that only reads and summarizes, to a program that can click, sign in and spend.

Grok Bot's launch post describes AI teammates you can give real work to, with their own computer and sign-ins to the tools you already use. Meta's Muse Wonder post describes a personal agent that takes actions on a user's behalf. Those are different products with a shared shape: a model, tools, some memory, and a permission boundary. For the difference between a rules-based bot and a model-driven agent, see AI trading agent vs trading bot; for whether bots deliver at all, see Do AI trading bots work?

Five jobs when an agent participates in perps

It helps to split "the agent trades" into five separate jobs. Each can be given to an agent, withheld from it, or put behind a human approval.

1. Read data. Prices, open interest, funding, positions and history. This is the lowest-risk job because nothing moves. LeverUp's developer docs describe a read-only REST API with no authentication required for prices, markets, positions and trade history. An agent that only reads can still produce a bad summary, but it cannot open a position.

2. Decide. Turn data into a view: long, short, size, exit. Model-generated decisions need checks on their assumptions, inputs and proposed exposure. A model can sound confident and be wrong, so a decision is a proposal until something checks it. One proposed way to separate the two is the decision-layer architecture, which is a proposed design, not a live LeverUp feature.

3. Place or stage orders. Staging means the agent prepares an order and a human confirms it. Placing means the agent submits it. The gap between those two verbs is the most important design choice in the whole stack.

4. Permissions and keys. Whatever places an order needs a credential. A key that can only express trading intent is a much smaller risk than a key that can also move funds. The full argument is in scoped permissions for AI trading agents.

5. Guardrails and holding costs. Position limits, leverage caps and loss limits belong in code that the model cannot talk its way past. Holding duration matters regardless of how often a person or agent checks the position. On LeverUp, holding fees accrue while a position is open, and funding may be paid or received.

Hook one: Grok Bot (xAI)

Grok Bot launched in beta on August 11, 2026. The post says Bots have their own computer, sign into tools you already use, work across apps, and "only come back when something needs your approval." The docs describe each Bot as running on a persistent cloud computer with a browser, filesystem and terminal.

On access, the security page says Bots generally act with the signed-in member's access, with an exception for team-managed connectors that may use team or service-account credentials. It also says credentials stay out of the model and approval prompts show the proposed operation. It also says its Auto Review feature does not review every side effect, so it is one control among several.

What the materials do not say: in the launch post, Grok Bot docs and security page reviewed here, none mentions trading, crypto, perpetual futures or LeverUp. The examples are sales, operations, engineering and similar work. Any link between a general agent and a perps venue is something a user builds, not something these pages document. For a plain-language overview, see what Grok Bot is.

Hook two: Meta Muse

Meta's Muse Wonder post, dated October 12, 2026, introduces models aimed at "personal and professional agentic tasks." It says Muse Wonder is available through the Meta Model API and Muse Code, and that it will soon power experiences in Meta's Muse app, rolling out first to subscribers.

On safety, Meta's post says a personal agent "takes actions on a user's behalf," that this level of access demands a model that "exercises discretion with private information and resists misuse," and that it "checks in before taking important actions." Finance appears only as an evaluation area, in the context of understanding financial information. The page does not mention trading, crypto or perpetual futures.

To be direct: nothing in Meta's post describes a connection between Meta Muse and LeverUp, and this series does not claim one. Meta Muse is here as a named hook beside the other two products, and because the behaviour its post describes — checking in before important actions — is the same pattern a perps setup needs.

Hook three: Manus Cue

Manus announced Cue as part of Manus 2.0 on September 28. The post calls Cue a standalone app for personal agents and says each agent has its own email, phone number, wallet and computer, and can pay within a budget you set. Cue was in early access with an invite code at launch.

Again, the official Manus announcement does not document crypto trading, perpetual futures or LeverUp. A wallet and a spending budget describe how an agent pays for things. They do not describe how much market risk an agent may take.

That distinction is the point of why a spending budget is not a leverage limit. As an illustration with assumed numbers (not from any product page): a 100 USDC budget could, at an assumed 20x leverage, control a 2,000 USDC notional position — the same margin-vs-notional split LeverUp's opening-a-position docs describe for leveraged perps in general. In this hypothetical, 100 USDC committed as margin supports 2,000 USDC of notional exposure; a spending budget alone does not establish a limit on leveraged exposure. For product details, see what Manus Cue is.

A research assistant is not an execution agent

Grok Bot's documentation describes research and summarization among its example tasks. In a hypothetical market-research setup, an assistant could summarize news, explain terms and compare scenarios. That covers reading data and some analysis. If configured without trading credentials or order-submission tools, it cannot submit trades.

An execution agent is different because it holds a credential that can change a position. The risks are different too. A research assistant that is wrong costs you a bad idea. An execution agent that is wrong can open, resize or close a leveraged position before you read the message. When a product page says "agent," ask which of the five jobs it is allowed to do.

What does not change on the venue

Whether a person or an agent submits the order, the venue's rules apply. Using LeverUp's docs as the reference:

  • Funding. The funding docs say that when one side is crowded, that side pays funding to the other, and that the rate is 0 when long and short open interest are equal. Their worked example, with assumed market numbers, comes to roughly 3.51 USDC over 24 hours on a 10,000 USDC long.
  • Holding fee. The holding-fee docs say the holding fee accrues per second on position notional and is charged when the position closes. An agent that keeps positions open for long stretches accrues it for the whole time.
  • Liquidation. The liquidation docs say a position is liquidated when the market price reaches the liquidation price or when collateral cannot cover outstanding fees, with a loss rate of 85% of margin on most pairs and 80% on some.

LeverUp documents a hosted-agent integration mode for One-Click Trading. The developer docs say the signing key "can only express trading intent" and "cannot transfer tokens, cannot withdraw, and cannot act outside the permission bits the user granted." For the execution steps, see the Grok Bot trading walkthrough rather than repeating them here. The relevant point for this post is that the venue enforces margin and liquidation the same way, regardless of who or what holds the key.

LeverUp uses a protocol-managed virtual liquidity system powered by the VMMV, where trades reference oracle pricing while execution, settlement, and risk management are handled at the protocol layer. See the official documentation on pricing and execution, VMMV-based settlement and protocol risk controls.

Series roadmap

This is post one of the Agentic Trading on Perps series. The rest are upcoming and not yet published:

  • #2 AI Trading Bot vs AI Agent on Perps: What Changes When the Market Has Leverage
  • #3 Scoped Keys and Delegated Access: What an Agent Can Actually Do to Your Perp Position
  • #4 Risk Guardrails in Code: Pre-Trade Checks an Agent Cannot Skip
  • (#5 cancelled — Cue wallet companion merged into this hub)
  • #6 Funding and Holding Costs for a Round-the-Clock Agent
  • #7 Liquidation and Fee Drift: What Happens When an Agent Holds Overnight
  • #8 Meta Muse, Connectors and Human Approval: How Delegated Trading Differs From a Hosted Agent
  • #9 Stock Perps Hours and Force-Close: Markets an Agent Shouldn't Enter Blindly
  • #10 Pre-Deploy Checklist for an Agent Trading on LeverUp

If you are new to the underlying mechanics, start with the perpetual futures learning path.

Closing

Agentic trading on perps is the same market with a new kind of participant. The useful questions are the old ones, asked about software: what can it read, what can it decide, what can it submit, what key does it hold, and what stops it. Official materials for Grok Bot, Meta Muse and Manus Cue describe general-purpose agents and do not document perps trading; treat any claim beyond that as unverified.

This article is educational and is not financial advice. Perpetual futures use leverage and can result in the loss of your entire margin.