Recently, I have been experiencing Binance AI Pro and I would like to try a more practical direction: designing the same trading strategy from scratch and having AI assist in building it. What is the difference between the entire process? I chose a relatively simple scenario: Bitcoin fixed investment strategy. Just look at how much effort AI can save us in organizing ideas, designing rules, and building workflows. Design your own strategy and consider a few questions first: ·Regular investment frequency: buy daily or buy weekly? ·Investment amount: fixed amount each time, or adjusted according to market conditions? ·Trigger condition: Buy regardless of price fluctuations, or buy only when there is a certain degree of price correction? ·Risk control: Is there an investment cap? Should we pause when encountering abnormal market conditions? It may seem simple, but once you start sorting it out, you will find that there are details to consider behind every issue. For example, a fixed weekly investment of 50 USDT makes the logic clearer; But if we want to add a condition that additional buying is only executed when BTC experiences a certain degree of correction, we need to further clarify the reference price, correction magnitude, execution frequency, and how to avoid repeated triggering. The advantage of designing by oneself is that each rule can be determined according to one's own understanding, and the thinking is also relatively easy to control. The disadvantage is equally obvious: one needs to organize scattered ideas into clear conditions and then consider the relationships between these conditions. If you want to add reminders or adjust trigger conditions in the future, the entire workflow will have to be reorganized by yourself. Next, I will hand over the same requirement to Binance AI Pro. Input prompt words: "Help me design a BTC investment strategy, invest 50 USDT per week, and create an editable strategy canvas that displays investment frequency, execution conditions, and risk control related rules. Use it for simulation trading first, do not enter the real market directly. '' One feature of Binance AI Pro is generating editable strategy canvases through conversations. Compared to starting from scratch to organize logic, you can first have a workflow framework and then check each item according to your own needs. For example, I will focus on confirming: ·Is there a correct understanding of the frequency and amount of fixed investment? ·Are the triggering conditions clear and have any boundary conditions been overlooked? ·Are the risk control related rules in line with one's expectations? ·Are there any unnecessary steps or logic in the workflow that you don't want to use at all? If you find that the generated results are inconsistent with your own ideas, continue to request modifications through dialogue. Of course, writing the prompt clearly does not necessarily mean that the generated strategy is correct. AI may misunderstand requirements or generate logic that requires further adjustment. It helps me organize my ideas, but the final rules still need to be checked and confirmed by myself. The real difference between the two methods If we only look at the process of strategy construction, I think the difference between the two is mainly reflected in the following aspects. 1. Different starting methods To design on your own, you need to first break down your ideas into specific rules, and then gradually organize and execute the logic. AI assisted design can first describe the goal in everyday language, allowing AI to help generate the initial workflow, and then continue to modify based on this foundation. For people who are already clear about what they want, both methods can be used; But for people who have ideas but are not very good at organizing them into processes, the value of AI assistance may be more apparent. 2. Different ways of logical organization When designing on your own, you need to actively consider each condition and the relationships between them. When using AI Pro, you can first have it generate a visual workflow, and then compare it with your original requirements to check where it needs to be supplemented, deleted, or adjusted. However, a clear workflow does not necessarily mean that the logic is reasonable. Especially when it comes to triggering conditions, fund management, and abnormal situations, it is still necessary to verify them item by item. 3. Different modification methods After modifying a condition in a strategy designed by oneself, it may be necessary to recheck whether other rules are affected. AI assisted design can propose modification requirements through dialogue and then check the updated canvas. This makes the adjustment process more intuitive, but it cannot be directly assumed that AI has correctly understood every modification. 4. Different levels of energy required AI can help with initial framework and partial workflow organization work, but it doesn't mean it can be completely brainless. In fact, I think that after using AI, people's energy will be more focused on requirement expression, logical review, and risk assessment, rather than simply building each step from scratch. So, rather than saying that AI designs strategies for me, it's more accurate to say that it helps me make the strategy design process easier to start and more convenient to repeatedly adjust. The completion of the strategy canvas construction does not mean the end of the task. Binance AI Pro provides simulated trading functionality, allowing users to observe the execution of workflows using virtual funds. At the same time, the product will also perform automatic code checks to help identify errors that may occur during workflow execution. There are two things that need to be clearly distinguished here: if the code check passes, it can only indicate that no corresponding execution errors were found in the relevant checks, and it cannot prove that the strategy is effective, let alone that the strategy is definitely profitable. Simulated trading does not necessarily equate to actual trading results. The liquidity, transaction situation, and market changes in the real market may all affect actual execution. Therefore, I prefer to first check the rules, then observe the execution process through simulated trading, and continue to modify after discovering problems, rather than generating strategies and directly taking them to the real market. If you decide to enter the real market in the future, you also need to clearly approve the strategy and manually transfer funds to the corresponding AI strategy account. After the strategy logic changes, the new version still needs to be approved again. Users can also pause policies or revoke access permissions. When experiencing such tools, my biggest concern is whether they can make it easier for me to turn an idea into a verifiable and adjustable execution process. The advantage of self-designed is strong autonomy, and all rules can be gradually established according to one's own ideas; The advantage of AI assistance is that it can quickly enter the workflow construction and modification process, especially suitable for those who have trading ideas but are not familiar with the strategy construction process. Of course, the premise is that you know what problem you want to solve. Without even considering the requirements clearly, letting AI generate a set of strategies randomly may only result in a workflow that appears complex but is not actually suitable for oneself. For me, a more reasonable approach is to determine the goals and risk boundaries on my own, let AI assist in building, and then check, simulate, test, and decide whether to adopt them. If you also want to give it a try, you can directly access Binance AI Pro: http://ai. (binance.com) Just find a simple fixed investment or market reminder scenario first. First, write down your own ideas, and then let the AI generate a workflow to compare the differences between the two methods in the construction and modification process. After all, AI can help you organize your thoughts and assist in execution, but the person who truly decides what strategies to adopt and what risks to take should always be yourself. The above is a discussion on the product experience and strategy construction process, and does not constitute investment advice!