How to become an AI toolsmith

Stop writing long prompts. Learn to build your own custom language and have an AI act as its compiler.

#1about 1 minute

The inefficiency of natural language for code generation

AI code generators are useful for prototypes but become cumbersome when specifying complex implementation details using natural language.

#2about 6 minutes

Understanding React fundamentals for the examples

A brief introduction to React covers core concepts like components, JSX syntax, passing data with props, and managing interactivity with the useState hook.

#3about 3 minutes

Creating a domain-specific language for React components

The "Act" language is introduced as a domain-specific language (DSL) with specific rules for defining components, IDs, classes, and styles more concisely than standard JSX.

#4about 1 minute

Using an AI to compile the custom language

The rules for the "Act" language are fed into an AI model, which successfully compiles the custom syntax into a functional React component.

#5about 4 minutes

Extending the language with props and state management

The "Act" language is enhanced with new rules for handling component props and managing state, demonstrating how the AI can combine multiple rules to generate complex code.

#6about 5 minutes

Understanding the benefits of domain-specific languages

Domain-specific languages (DSLs) like SQL offer advantages over general-purpose languages in expressiveness, maintainability, productivity, and efficiency for specific tasks.

#7about 3 minutes

A four-step recipe for building your own DSL

Follow a four-step process to create your own DSL with AI by identifying a repetitive task, designing a simple language, defining rules, and iterating on the results.

#8about 4 minutes

Q&A on AI limitations and practical application

The discussion covers the limitations of using AI for complex compiler generation and compares the DSL approach to using an IDE with tools like GitHub Copilot.