2025-04-12

# AI for Developers: Strategies to Boost Productivity

Artificial intelligence (AI) is already transforming the way developers work. From code generation and optimization to continuous learning, now is the time to make the most of AI's capabilities to save development time, improve the quality of our work, and accelerate our professional growth. Below, I will outline a series of key strategies to optimize how we use AI.

# Prompt Engineering Techniques: The Art of Talking to AI

Success when working with generative AI models like Copilot, Grok, ChatGPT, or Gemini largely depends on how we formulate our prompts. A good prompt can make the difference between an incomplete response and a precise solution. Here are some strategies for crafting prompts that can help us get the results we expect:

# 1. Relational Interrogation Prompt Strategy

This involves asking a set of specific questions that force the AI to respond directly and in a structured way, with answers interrelated. For example:

"How can I optimize this function? Should I rethink how it receives parameters? Should the same approach be applied to the rest of the class?"

This will yield detailed and connected responses.

# 2. Guided Interrogation Prompt Strategy

This strategy is useful when we are unsure about the information the AI needs to provide the best response. In this case, we ask the AI to request the information it needs to give us the best recommendation. For example:

"Propose a new architecture for my project, focused on making it more maintainable. Ask me a series of yes/no questions to help you provide the best recommendation."

This ensures the AI asks questions to improve the quality of its response based on our expectations.

# 3. Pros and Cons Prompt Strategy

We ask the AI to analyze a decision from multiple perspectives. For example:

"Give me the pros and cons of continuing to use the Factory Method pattern in my classes A and B versus refactoring them to use the Builder pattern, if I need to centralize the creation of these classes in class C."

This is useful for making decisions and evaluating consequences.

# 4. Stepwise Chain of Thought Prompt Strategy

We ask the AI to solve a problem by breaking it down into logical steps. For example:

"Explain step by step how to implement JWT authentication in a REST API with .NET."

This will provide clear, structured, and easy-to-follow responses, even for complex technical tasks.

# 5. Role Prompt Strategy

We assign a specific role to the AI so it adapts its tone and approach during the conversation. For example:

"Act as a senior full-stack developer expert in Angular and .NET and design a scalable architecture for an e-commerce application."

This is perfect for obtaining responses from an expert or creative perspective.

# 6. Iterative Prompt Strategy

We shouldn't limit ourselves to a single prompt. If the response isn't what we expect, we refine the request with more context and details. For example:

"I don't understand your explanation about closures in JavaScript. Can you give me a practical example with code?"

This helps clear up all doubts.

# How to Leverage Generative AI in Software Development

There’s more to AI than just prompts. Generative AI offers practical tools that we can integrate into our workflow as developers. Here are some ways to make the most of it:

# 1. Code Generation

AI accelerates coding by providing autocompletion, suggestions, and even generating entire snippets and classes. Tools like GitHub Copilot, integrated into Visual Studio and VS Code, work this way. They not only suggest solutions as we type but can also interact with our classes through their integrated chat, allowing us to request more complex tasks. For example:

"Write a C# function to validate an email using regular expressions."

"Generate an Angular component for a contact form."

Always remember to review the generated code to ensure it meets good standards and your requirements.

# 2. Improving Code Quality

AI not only generates code but can also improve it. For example:

Request reviews: "Analyze this 5-year-old C# code and update it to the latest version, optimizing performance and fixing potential errors."

Find vulnerabilities: "Review this PHP script and point out potential security issues like SQL injections."

Optimize: "Suggest performance improvements for this SQL query."

This helps keep our code cleaner, more secure, and up-to-date with less effort.

# 3. Testing and Documentation

Writing tests and generating documentation for our projects is often tedious, so why not use AI for this too? For example:

Generate tests: "Create unit test cases in Jest for this JavaScript function that calculates the factorial of a number."

Document: "Add detailed comments to this Python code and generate external documentation in Markdown format."

This saves time and optimizes project maintenance.

# 4. Accelerated Learning

AI can act as an expert and personalized teacher, recommending resources based on our needs. For example:

"I'm learning Rust. What tutorials or documentation do you recommend for understanding memory management?"

"Give me a 4-week study plan to master the basics of Docker."

We can complement this by asking it to prepare exercises, resolve doubts, or even simulate technical interviews.

# Other Strategies

Exploring Alternatives

Use AI to compare technologies or approaches, helping us choose the best tools for our projects. For example:

"Compare Flask and FastAPI for building a Python API: performance, ease of use, and community adoption."

Task Automation

Delegate tasks like data format conversion or configuration generation. Example:

"Convert this JSON to a SQL database schema."

Prototyping

Create functional prototypes in minutes. For example:

"Design a basic Python script for a real-time chat application using WebSockets."

# Conclusion

Despite the initial uncertainty, AI is a powerful ally for us developers, but its true potential is unlocked only when we know how to interact with it. Mastering prompt techniques to get precise and useful responses is essential. Leveraging its capabilities to generate code, improve quality, automate tasks, document, and accelerate learning is equally important. With a good strategy, AI will not only make us more productive but also enhance the quality of our projects and keep us at the forefront of a constantly evolving profession.

Are you ready to integrate AI into your workflow? Try these strategies and transform your daily life as a developer.