How to Use AI Right

Challenges

  • Difficulty identifying how AI can help in current software development, not just future scenarios
  • Development teams struggle to boost speed and productivity without increasing technical debt
  • Developers face pressure to deliver clean, scalable code quickly without sacrificing quality

Solutions

  • Focus on practical, current AI tools like GitHub Copilot and JetBrains AI Assistant
  • Integrate AI capabilities such as LLMs and RAG into backend systems and workflows
  • Use AI assistants to support code writing, debugging, documentation, and design tasks

Benefits

  • Immediate productivity gains by applying AI tools that are available and usable today
  • Enhanced application functionality and faster feature delivery through AI integration
  • Improved code quality, scalability, and engineering efficiency with AI-powered assistance

AI-Driven Development: How to Use AI Now to Boost Productivity

From the Memphis Global AI Community Boot Camp Speaker Interview Series: Watch on YouTube

Table of Contents

  • Focus on the NOW in AI
  • Two Types of AI in Software
    • AI Features in Applications
    • AI-Driven Development
  • Conclusion

Focus on the NOW in AI

Most of the conversation around AI is about future possibilities, but software leaders, architects, and developers need to focus on what AI in software development can do right now and what will change in the next year.

 

By focusing on current AI capabilities, tech teams can stay ahead of the curve and implement solutions that impact productivity and efficiency today.

Two Types of AI-Driven Development

AI Features in Applications

These are building smarter, more interactive applications with transformative technologies like:

  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Local GPTs and open-source AI models

 

These tools are revolutionizing AI software development by boosting the productivity and speed of developers’ daily work.

 

By integrating AI into backend systems, software teams can enhance application functionality using traditional development tools and processes. This seamless integration supports scalable, AI-powered innovation.

AI-Driven Development

With AI-Driven Development, artificial intelligence becomes a true partner in the software engineering process.

 

Software engineers and architects can use intelligent tools like:

  • GitHub Copilot
  • JetBrains AI Assistant

 

These AI coding assistants help developers write cleaner code, maintain scalable architecture, and develop features faster.

 

Importantly, these tools aren’t replacing developers. They’re empowering teams to improve code quality, speed, and technical knowledge, all while keeping control in the hands of human engineers.

Conclusion

AI is a tool that software architects and developers can use today by focusing on practical use cases and available technologies.

 

No matter the task—writing code, debugging, documentation, or design—there’s a place for AI in your development strategy. Use AI now to boost productivity and drive digital transformation.