# AI Trader

## Design Philosophy

AI Trader was built with a strong design philosophy built on five main pillars: Simplicity, Pragmatism, Sustainability and Intelligent AI Trading.

Please check out the developer[ Docs](https://ais-organization-2.gitbook.io/ai-trader/docs) if you are a developer

### #Simplicity <a href="#simplicity" id="simplicity"></a>

AI Trader aims to keep the feature set it offers as simple as possible. Ideally, AI Trader should contain the minimum number of moving parts required for a secure, scalable and flexible system. This simplicity gives AI Trader's design a number of significant advantages over other, more complex structures.&#x20;

AI Trader prefers to use existing battle-tested Ethereum code and BSC code wherever possible. The clearest example of this philosophy in practice is the choice to use AITRADER as the client software for AI Trader. When dealing with critical infrastructure, simplicity is also security. Every line of code we write is an opportunity to introduce unintentional bugs. A clean and minimal code base is also easier for external contributors and auditors to access. All of these help to maximize the security and correctness of the AI Trader protocol.&#x20;

This will only become more apparent as the AI Trader protocol solidifies and existing resources can be redirected to core Ethereum infrastructure.

### #Pragmatism <a href="#pragmatism" id="pragmatism"></a>

AI Trader's design philosophy puts the needs of users and [developers](https://ais-organization-2.gitbook.io/ai-trader/docs) above theoretical perfection. AI Trader was also founded on the understanding that any core team would have limited areas of expertise.&#x20;

AI Trader is developed iteratively and strives to continuously gain user feedback. Many of today's core AI Trader features, such as [EVM](https://ais-organization-2.gitbook.io/ai-trader/docs/avm) equivalence (opens new window), were only possible through this iterative approach to protocol development.

### #Sustainability <a href="#sustainability" id="sustainability"></a>

AI Trader has been involved for a long time. Application developers need to ensure that the platforms they are building can not only keep running, but remain competitive in the long run.

AI Trader's design process was built around the idea of long-term sustainability, rather than taking shortcuts for scalability. At the end of the day, a scalable system is meaningless without the ecosystem that supports it.

The more complex the codebase, the harder it is for people outside the core development team to actively contribute to it. By keeping our codebase simple, we are able to build a larger community of contributors who can help maintain the protocol over the long term.

### #AI Trader has more advantages. <a href="#optimism" id="optimism"></a>

Although AI Trader appears to be an independent blockchain, it is ultimately designed as an artificial intelligence transaction, and all transaction scenarios will be applicable to AI Trader.

**Automation:** AI Trader can automate workflows and processes, or work independently of human teams. For example, artificial intelligence can help automate various aspects of information security by continuously monitoring and analyzing network traffic; quickly avoid risks through data analysis and market trend data, and make automatic decisions thousands of times faster than humans.

**Reduce human error:** AI Trader can eliminate human error in data processing, analysis, making decision recommendations, and other tasks through optimal automation of functions and algorithms.

**Fast and accurate:** Compared with humans, AI Trader can process more information faster, so as to find patterns and discover data relationships that humans may miss. For example, when trading opportunities arise, AI Trader can buy and sell 10,000 times faster than humans. Data will be easily captured and used in AI Trader.

**Unlimited availability:** AI Trader is not limited by time of day, rest needs, or other human burdens. When running in the cloud, AI Trader and machine learning can be "always on", so that the assigned tasks can be continuously processed, and the benefits of decision-making can be obtained at any time, AI Trader is the first.
