How to Use Bitget’s GetAgent: A Practical Walkthrough of the Exchange’s New AI Trading Assistant
Bitget has spent the past year positioning itself at the intersection of retail-friendly UX and advanced trading tools.
Its newest addition, GetAgent, aims to collapse the gap between analysis and execution by giving traders a single conversational interface that can interpret natural-language requests, generate market insights, and place trades directly inside the app.
In the review, the feature is presented not as another gimmicky chatbot, but as a functional assistant that helps reduce friction in day-to-day trading. Below is a concise recap of how GetAgent works in practice, paired with a step-by-step walkthrough anyone can follow.
A Seamless Entry Point Into Trading
Accessing GetAgent inside the Bitget app is intentionally simple. The assistant is available from several locations: the home screen’s More Services menu, the Assets dashboard, and directly through individual token pages. In certain markets, Bitget automatically displays a banner such as “GetAgent is analyzing” a cue that contextual insights are already being prepared for that specific asset.
Once opened, traders are greeted with a minimalist chat interface. Suggested prompts appear at the bottom, but the assistant works best through natural instructions.
Example from video: We gave the following command: “I want to buy ZEC, but I want to purchase it cheaper. What’s a good entry point?”
After a few seconds of generating a response, GetAgent provides a complete analysis, stating the current trading price, potential support levels, and resistance levels. It generates a short-term analysis, which issues a bearish signal. It then specifies the entry strategy, suggesting an entry point between $220 and $225.
It then went on to suggest that the user should allocate only 20% to 30% of their capital, rather than investing it all at once. It also provided the user with suggested stop-loss levels. Crucially, it always offered multiple options for both the stop-loss and the take-profit targets, categorizing them as very conservative, moderate, or high-risk placements. For the take-profit targets, it gave multiple options depending on how bullish the user might feel about the setup.
The goal is clear: eliminate the need to jump between charts, order forms, external tools, and on-chain dashboards.
The Assistant’s Responses: Fast, Structured, and Actionable
GetAgent’s output depends on the request. When asked for market insights, it produces a structured breakdown: a short-term outlook, technical indicators, relevant price levels, and sentiment cues that help traders quickly orient themselves without opening a full suite of charts.
When the user requests an actual trade, the assistant generates a preview card. This includes the token, estimated execution price, order type, and the exact amount, allowing traders to confirm with a single tap. If the action involves a Web3 token, an additional on-chain confirmation step appears.
Example from video:
This segment illustrates the direct, hands-on trading capabilities facilitated by the agent. We initiated a specific market action by issuing the command: “Place order for ZEC/USDT at 225$ for 25$.”
This was a clear, concise instruction executed within the volatile environment of futures trading, requiring precise management of risk and leverage. Crucially, before executing the command, we had ensured the required margin was available by manually transferring the funds into our futures account. The system processed the request immediately, and the buy order was subsequently filled at the specified price point, confirming the agent’s reliability in order placement.
The process then shifted to strategy, determining the optimal exit. We promptly consulted GetAgent for guidance on the ideal selling price, debating between a quick exit at the entry price of $225 or a more ambitious target of $230. Based on our analysis and the agent’s input, we ultimately decided on the $230 target. Upon the successful execution of the sell order at this higher price, we were pleasantly surprised by the rapid and favorable outcome: the chosen strategy proved successful, resulting in a 2.25% profit on the trade and validating the efficiency of using GetAgent for both execution and tactical decision-making.
Executing a Spot Trade Through GetAgent
The video demonstrates how frictionless spot trading becomes with the AI assistant. A typical flow looks like this:
- Open GetAgent from the home screen or token page.
- Enter a command such as: “Buy ZEC/USDT at 225$ for 25$.”
- Review the order card generated by the assistant.
- Confirm the trade.
- Verify execution inside the Order History tab.
The strength of this system lies in its consistency. Whether trading ZEC, ADA, or BTC, the process remains identical, reducing cognitive load and minimizing errors caused by busy mobile interfaces.
Portfolio Analysis Feature
One of the most powerful and time-saving features offered by GetAgent is its comprehensive portfolio analysis and reporting capability, which is activated via an extremely simple and intuitive command. This functionality allows users to bypass manual tracking and immediately gain deep insights into their investments.
Examples from video:
We initiated this process by issuing the command: “Generate a personalized daily report based on my portfolio.”
The agent processes the request rapidly, providing the output within mere seconds. This generated report offers full transparency into our asset structure, detailing our total held assets, precise purchase and sale timestamps for each cryptocurrency, and a statistical breakdown of our overall trading performance over the specified period. Furthermore, the daily report extends beyond personal holdings, giving us a crucial market overview, including a list of the day’s biggest gainers and losers and, most importantly, provides a thorough, automated technical analysis for our specific cryptocurrency of interest, which in this documented case was ZEC. This level of automated detail enables rapid, data-driven decision-making without the necessity of external research.
Moving beyond trade execution, we further engaged GetAgent to get its strategic assessment of our overall portfolio composition. Specifically, we asked the agent for its opinion on whether holding fiat currencies introduced an unacceptable level of risk. The agent analyzed the topic in great detail, providing a comprehensive breakdown of the associated factors. Its ultimate conclusion was that while holding fiat currency is not inherently risky from a security standpoint, it clearly stated that our funds are not protected from inflation. This highlighted the critical distinction between currency security and the erosion of purchasing power over time.
On-Chain Trades With a Single Prompt
For traders interacting with Web3 tokens, GetAgent streamlines on-chain purchases in the same conversational manner.
A simple request such as “Buy 200 USDT of ZEC on-chain” prompts the assistant to prepare a transaction preview. Here, traders will see the network, gas fee estimate, and token details, followed by a signing confirmation. The flow mirrors a typical Web3 wallet experience but removes several manual steps.
The design philosophy is consistent, with advanced features simplified through natural language.
Strategy Automation: Bot Creation on Command
One of the more advanced demonstrations in the video involves creating a trading bot directly from chat. Instead of navigating multiple setup pages, traders can describe the strategy they want:
- target price range,
- capital allocation,
- risk tolerance,
- take-profit and stop-loss logic.
GetAgent converts the request into a ready-to-deploy bot template. After reviewing parameters, users can activate the bot and track its performance in the dedicated dashboard.
For traders with intermediate knowledge, this feature effectively compresses the bot-creation learning curve.
Beyond its conversational features, GetAgent now includes a suite of AI-driven trading strategies that operate in real time, giving users a transparent view of how different trading philosophies behave under actual market conditions. Inside the Model Arena, Bitget showcases several specialized AI trading avatars—each representing a distinct style such as hedging, major-coin momentum, altcoin breakouts, or mechanical grid-based execution. These agents run live accounts and display ongoing performance curves, entries, exits, and drawdowns as they happen. For traders, this creates a rare opportunity to observe, study, and compare real-time AI strategies side by side, offering practical insights into how various models respond to volatility, trend shifts, and market structure. Whether users prefer conservative setups or high-beta plays, the transparent data helps them select approaches that align with their personal risk profile and trading style.
Trading With Oversight: Built-In Safety Checks
Although GetAgent speeds up execution, the assistant consistently nudges users to review details before confirming. This includes:
- token and contract verification,
- order sizing and slippage,
- risk parameters for bots,
- gas fees for on-chain actions.
Every trade, bot deployment, or portfolio change remains logged in the user’s Order or Activity history. The assistant’s role is to accelerate decision-making, not bypass standard security practices.
A More Natural Way to Trade
From a user-experience standpoint, GetAgent is Bitget’s attempt to bridge retail simplicity with professional-grade tools. Instead of opening multiple UI panels, the user interacts through a single conversational interface, something that feels increasingly intuitive as AI products become more integrated into trading platforms.
For beginners, it removes complexity. For experienced traders, it reduces friction. And for Bitget, it represents a move toward a more unified trading ecosystem, one where analysis, execution, on-chain interaction, and strategy automation can all be triggered in a single line of text.
Final Thoughts
Bitget’s GetAgent won’t replace critical thinking or risk management, but it does reshape how traders interact with an exchange. If the goal is to trade faster, obtain instant market context, or test automated strategies with minimal setup, the assistant offers a meaningful upgrade from traditional mobile trading flows.
As exchanges race toward AI-enhanced interfaces, Bitget has delivered one of the more functional, ready-to-use implementations on the market, one that genuinely reduces friction and feels immediately beneficial for everyday traders.
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