Written in advance: Research background and evaluation motivation
The information density and strategy complexity of the cryptocurrency market are increasing day by day. Even users familiar with K-line, understanding fundamentals, and reading on-chain data often feel overwhelmed with information.
This is also why I have always maintained a high interest in the combination of AI and cryptocurrency trading. In recent years, more and more platforms have begun to integrate AI functions, but most remain at the functional level or simple information aggregation, while Bitget's launch of GetAgent is promoted as 'the world's first all-in-one cryptocurrency trading assistant', helping users obtain information, strategy analysis, and order trading. I also unexpectedly benefited from a surge in BTC during the testing process.
This article evaluates GetAgent in the context of daily trading scenarios, primarily validating two specific questions: 'Can it simplify the decision-making process?' and 'Can it bring higher returns?'. The evaluation results are for readers' reference and discussion.
1. Product positioning and basic function sorting
GetAgent is actually an AI trading assistant embedded in the Bitget App. Its positioning is similar to an 'AI personal investment advisor', completing tasks such as information processing, strategy generation, position diagnosis, and simple trading suggestions through natural language interaction. Its biggest highlight is chat interaction + over 50 professional-level MCP tools.
Currently, there are many usable scenarios tested, including market analysis, position suggestions, and even automated trading:
Market analysis and trend interpretation: You can directly ask 'How is the BTC market today?', and the system returns a comprehensive interpretation combining K-line indicators, on-chain data, and market sentiment;
Strategy suggestions and risk warnings: For example, 'Is it suitable for me to increase my position in ETH now?', GetAgent will provide range references and profit-taking stop-loss suggestions based on technical signals and individual risk preferences;
Smart money tracking and hotspot simulation: In a sense, it simulates a hotspot warning by tracking on-chain capital, whale transfers, and KOL social mention frequencies;
Position analysis and rebalancing recommendations: Based on the composition, concentration, and correlation of the coins in your account, it provides adjustment suggestions;
Conversational learning AI: Supports basic Q&A, such as 'What is AMM?', 'Who is suitable for regular investment strategies';
Automated trading: Supports direct trading through dialogue, such as 'Buy 1 ETH', 'Increase position by 100BGB', placing orders directly through commands.
From a functional logic perspective, GetAgent attempts to cover the entire closed loop from information input to execution suggestions, acting as a true 'AI personal investment advisor'.
2. Actual user experience: Interaction process from input to output
The most direct feeling is: as an 'AI personal investment advisor', you can converse with GetAgent in natural language like using ChatGPT, without switching interfaces or checking chart data, and the overall user experience is quite smooth.
For example, during testing, I asked: 'Is it suitable to buy BTC now?' GetAgent will enter a thought state, and in the UI, I can click to see its thought process:
“Understanding user needs, deeply analyzing the best solutions”
“Strategy determined, now initiating a step-by-step professional analysis process,” this step will be broken down into multiple sub-steps, including:
Based on user investment needs, now obtaining the Fear Index trend to insight market sentiment pulse
Linking exchange data sources to present you with a complete overview of BTC market
Analyzing user query intent, retrieving daily K-line data for interpretation
Understanding the need for technical analysis, now performing multi-indicator deep analysis on BTCUSDT
Unlike the thought process of DeepSeek, which has recently been frequently joked about, the above is clearly a standard thought process defined by developers to enable GetAgent to provide good vertical service, aligning with basic analytical paths.
Ultimately, GetAgent provided a relatively detailed analysis, including:
Price trends and trading volume changes over the past month;
Key indicator statuses such as RSI/MACD/Bollinger Bands;
Whether BTC has capital inflow during market hotspot changes;
The technical support and resistance range at the current position;
External sentiment references (such as community sentiment and mention frequency of major figures);
The format of this output text is highly structured and can basically serve as a direct decision reference.
In terms of interaction experience, I believe its most successful point is translating complex quantitative and fundamental analysis into plain language for users. Beginners can lower the learning threshold, while veterans can improve decision-making efficiency.
However, when asking similar questions that require analysis of specific coins, GetAgent's response time generally takes 30 seconds or even longer, which feels a bit long for mobile product experience; this is an area I believe should be optimized.
3. Three core function tests: The actual capabilities of GetAgent
Market interpretation
First, testing basic market analysis. I posed similar questions regarding BTC, ETH, and PEPE: 'Is it suitable to buy at the current position?' The information returned by the system includes price ranges, support and resistance levels, main technical indicator statuses, and changes in sentiment indicators. The completeness of this part of the data is quite good, especially as it combines three dimensions: technical + on-chain + sentiment.
Compared to traditional methods—where I needed to use multiple different platforms to obtain this information—GetAgent accomplishes it with a text summary, saving a lot of switching time.
Smart Money Tracking
This feature is a highlight that I focus on. After trying to ask 'Have there been any large movements for PEPE recently that are worth referencing?', GetAgent provided on-chain large address data, DEX inflow and outflow trends, and hot KOL mention frequency. When asking 'What are whales buying recently?', GetAgent offered some token and related data (24-hour increase, current trading volume, and market value) for reference. When inquiring about 'Cathie Wood's recent actions', it provided investment trends, investment logic analysis, investment references, and market impact analysis.
The content provided by this function may seem a bit thin for seasoned traders, but overall it has already approached the analytical depth of a professional investment research team, and it is very user-friendly and understandable for retail investors, especially newcomers, bridging the information gap with professional traders at a very low cost.
Position diagnosis
This is also a little feature that surprised me. GetAgent analyzed the structure of my account holdings and pointed out risks such as high concentration of ETH, lack of hedging coins, and missed opportunities to build positions using stablecoins, and also suggested establishing a 'market cap balancing mechanism' to reduce the weight of altcoins.
This different third-party perspective, clearly, is highly valuable in assisting trading decisions. Especially since the system can provide detailed reasons and thought processes rather than mechanically directing what to do. This 'explainability' greatly enhances my trust in the suggestions themselves.
4. So can it bring 'excess returns'?
This is a question that all readers care about. During testing, I used GetAgent to execute several small strategies, completely following the suggested entry points, and unexpectedly caught BTC on a rise, with the buying and increasing positions precisely timed. The spot made an 8% gain in one day, but unfortunately, I did not follow the advice to open a contract and missed a wave of contract profits!
Therefore, in my view, GetAgent is a valuable decision optimization tool that can help you make better decisions and earn profits. Its main advantages are:
Saving time in information searching and integration;
Outputting structured entry suggestions;
Highlighting potential overlooked risk points;
Enhancing the data foundation when you make decisions;
Ultimately executing orders based on your judgment.
Of course, it will not directly and accurately predict tops and bottoms; you still need to make judgments and decisions yourself and take responsibility for risks. My attitude toward it is similar to that toward autonomous driving: AI cannot and should not replace the subjective judgment of traders.
5. What decision behaviors has it changed?
Before using GetAgent, I usually relied on three dimensions of data cross-confirmation: technical indicator charts, on-chain trends, community sentiment; this meant I had to switch between at least three platforms, manually marking and summarizing. Since incorporating GetAgent into my daily use, I found that the process of information integration and quick judgment has become more efficient.
Compressing the decision-making process, improving decision-making efficiency
From my input of a vague question 'Is BGB suitable for short-term entry', to receiving suggested ranges, stop-loss reference points, and support resistance ranges in less than 20 seconds. More importantly, this information does not require me to cut charts or verify MACD/EMA values, and directly provides a credible thinking path.
This has transformed my daily decision-making rhythm from 'collecting → summarizing → judging → acting' to 'filtering → judging → acting'.
Change in decision-making perspective
Previously, I relied heavily on the shape logic of graphical patterns or technical indicators, such as 'triangle breakouts', 'golden crosses', etc.; now I focus more on 'cross-validation provided by the system', for example, whether sentiment indicators and capital inflows are diverging? Has the narrative heat of a currency declined?
This is actually a transition from 'indicator thinking' to 'system perspective', GetAgent can help me clarify logic rather than just tell me values.
Expanding the dimensions of perceived information
GetAgent also has a subtle effect: it makes you aware of certain data points you have never paid attention to but are crucial, such as changes in active addresses on-chain, social mention frequencies of meme sector rotations, and trends of whale wallets moving to exchanges.
The structural organization of this type of information, which was previously exclusive to institutions, can now be clearly understood through dialogue. Over time, the dimensions of focus during my trading have become more diverse, naturally increasing the probability of avoiding pitfalls.
6. Usage suggestions for different types of traders
AI tools are not suitable for everyone and do not exhibit optimal performance at all stages. In my testing, I tried to analyze GetAgent's adaptability from several typical user perspectives.
New users: provide friendly onboarding guidance
For users who know nothing about charts and are unfamiliar with on-chain logic, GetAgent's core value lies in being 'newbie-friendly'. For example, it can help users plan regular investment plans, explain basic concepts, and use specific cases to explain sources of volatility and risk points.
This is much more reliable than blindly researching TA or chasing KOL opinions for beginners. For new users entering the market, this is a good 'AI coach' type of tool.
Heavy Trader
For users who frequently operate and have their own strategy frameworks, GetAgent provides decision support + blind spot reminders. It cannot replace the system you have built but can help you verify whether certain trends match your cognition or issue warnings when you overlook details.
Especially during periods of frequent rotation of hot coins, using GetAgent can speed up judgment and reduce noise interference caused by massive information.
Radical Investor
For high-frequency operators, trend chasers, and alpha hunters, GetAgent's potential value lies in two directions:
Hotspot prediction mechanism: By analyzing narrative heat, community indexes, and whale buying rhythms, it may provide signals before a surge;
Risk checklist function: It will point out the risks of certain tokens with poor liquidity, low market value, and frequent institutional sell-offs, issuing warnings for potential risks.
The rationality of AI acts like a sheath for the sword, providing caution and restraint for radical investors.
7. What is the value of GetAgent?
As a product still in the testing phase, GetAgent has not yet reached the level of perfectly replacing manual trading. However, I believe it has already made a very clear breakthrough in the user experience of cryptocurrency trading.
Current Stage: Learning Tool + Decision Support
In terms of functional completeness, GetAgent is sufficient to become a comfortable tool to use, especially suitable for:
Navigation during the learning process for beginners;
Intermediate users with strategy frameworks but limited energy;
Veterans who want to quickly focus on key information and reduce judgment blind spots.
Mid-term potential: an important marker of tool equity
GetAgent's greatest potential lies in breaking the information gap between individuals and institutions. Its integrated data dimensions are broad and its information model is relatively stable. Although it cannot construct a true Alpha strategy, it can quickly help users skip ineffective noise and focus attention on effective information points.
In a sense, it has brought 'quantitative-level data services' into the hands of ordinary users in the form of a dialogue box.
Long-term development: may become the standard entry point for trading platforms
If GetAgent continues to optimize input parsing, strategy models, execution linkage, and other modules, I believe it is very likely to become the default interaction entry point for trading platforms in the future. Just as today, you use Google to search for information and Siri to control devices, in the future, opening a trading app will start with 'asking AI'.
8. Summary and Conclusion
After testing over the past few days, I believe GetAgent can indeed serve as an excellent 'AI personal investment advisor' in the cryptocurrency market. It helps you focus on information, reminds you of risks, provides directional suggestions, allows you to make decisions, and then places orders for you with one click.
For traders who are keen on self-learning and enhancing their cognitive systems, this is a tool worth continuous attention. I will continue to use it for trading preparation, portfolio adjustment assistance, and hotspot verification. I also look forward to more optimizations in data depth, feedback speed, and execution interfaces.
