TLDR;
This video explores how artificial intelligence (AI), specifically large language models (LLMs), can be used to enhance blockchain development in 2025. It covers various applications, including code generation, error handling, front-end development, and smart contract auditing. The video emphasizes the importance of AI as a tool for both new and experienced blockchain developers to streamline their workflows and improve the security and functionality of their applications.
- LLMs are the core AI technology for blockchain developers.
- AI can be integrated through chatbots, text editor plugins, and full-on AI code editors.
- Key applications include code generation, error handling, front-end development, and smart contract auditing.
Introduction: AI and Blockchain Development [0:00]
The convergence of AI and blockchain technologies presents unlimited potential for creating game-changing applications. For developers aiming to excel in blockchain by 2025, AI is becoming an essential skill. The video aims to demonstrate how to leverage AI to code blockchain applications, providing insights from a blockchain developer's perspective. The speaker also promotes the Blockchain Boot Camp V3, launching on May 15th, which will extensively use AI in developing blockchain applications.
Understanding Large Language Models (LLMs) [1:23]
The core AI technology for blockchain developers is large language models (LLMs), which power tools like Chat GPT. LLMs understand and respond in human-like text, including human-readable source code such as Solidity, JavaScript, and Python. While the chatbot doesn't run the code, it provides answers that can be integrated into your code.
Ways to Interface with AI [2:40]
There are several ways to integrate AI into your workflow. One way is to use a language model directly through platforms like chatgpt.com. Another approach is to use text editor plugins like Copilot, which allows you to chat with an LLM directly inside your text editor. For a more integrated experience, you can use a full-on AI code editor like Cursor, which has AI built-in, allowing it to look at your code, make modifications, and compose things for you.
Writing Code from Scratch [4:18]
AI can be used to write code from scratch, especially for tasks with predictable outputs, such as creating an ERC20 token. By providing a prompt like "create a Solidity ERC20 token with 18 decimal places called DAP token with a symbol DAP with no external libraries," the AI can generate the source code. This code can then be deployed using tools like Remix or integrated into a Hardhat project. AI can also assist in building more complex applications, such as savings and lending platforms, by providing step-by-step guidance and code suggestions.
Error Handling [5:48]
AI can significantly aid in error handling, a common frustration for new developers. Instead of struggling with cryptic error messages, developers can explain the problem to the AI, provide the error message, and ask for a simplified explanation and troubleshooting plan. The AI can help understand the underlying cause of the error and provide a step-by-step fix, which is more effective than simply Googling the error message and trying to interpret solutions from Stack Overflow or GitHub issues.
Front-End Development [7:37]
AI is particularly useful in front-end development, which involves creating user interfaces for blockchain applications. While back-end development (smart contracts, etc.) is essential, front-end development allows users to interact with these applications. AI can create entire front-end applications from scratch by providing the AI with the smart contract's source code and specifying the desired programming frameworks (e.g., ReactJS, Next.js) and functionalities. Additionally, AI can be used to quickly skin an existing front-end application by generating CSS code based on specified themes and settings.
Smart Contract Auditing [9:51]
AI can be used for smart contract auditing, which is crucial for ensuring code security and preventing vulnerabilities that could lead to hacks or loss of funds. Developers can use AI to identify potential security flaws in their code before handing it off to a professional auditor. By piping the source code into a language model and asking it to identify vulnerabilities, developers can address basic issues and demonstrate due diligence. AI can also be used to learn smart contract auditing skills, identify vulnerabilities, and serve as an essential auditing tool.
Conclusion [12:38]
AI offers numerous ways to enhance blockchain development, and the possibilities are vast. The video encourages viewers to like and subscribe for more content and to consider joining the Blockchain Boot Camp V3 for extensive training in AI-driven blockchain development.