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Vini Ganancio is a Senior Cloud Software Architect at Caylent, specializing in DevOps and AI/ML with a focus on cloud-native application development. Based in São Paulo, he is a builder who constantly experiments with new ideas to create innovative solutions. Passionate about coaching and knowledge sharing, Vini helps organizations leverage modern cloud technologies and stay competitive in today's rapidly evolving market.
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Luiz Soares is a Senior Cloud Software Engineer at Caylent, based in São Paulo, with a strong track record of modernizing enterprise applications and driving cloud transformation initiatives. With experience at Itaú Unibanco, he specializes in building scalable, cloud-native solutions using .NET, Node.js, Kubernetes, and AWS. His expertise includes serverless architectures, AI-powered applications, CI/CD pipelines, and infrastructure as code. Driven by a passion for modernization, clean architecture, and performance optimization, Luiz brings a consultative and solution-oriented mindset to every engagement.
View Luiz's articlesAs application demands grow and timelines shrink, organizations are seeking new ways to modernize faster. The race is on to upgrade outdated applications, accelerate feature releases, and maintain code quality while managing increasingly complex software systems. As the pressure to do more with less intensifies, developer productivity has become essential to success.
This is where AI-powered development tools are transforming the industry. Instead of replacing developers, these tools enhance human abilities, automate repetitive tasks, and offer intelligent support throughout the software development process, allowing development teams to focus on innovation while AI manages the routine work.
This blog examines how AI is changing developer productivity, with a detailed look at Amazon Q Developer. We'll guide you through a practical example of migrating a .NET Framework application to .NET 8, demonstrating how AI can turn what used to take weeks of manual work into hours of guided automation.
Before exploring solutions, let's recognize the real challenges that development teams face today.
These challenges are not just technical – they directly affect business outcomes. Slow development cycles lead to delays in launching features, raise maintenance costs, and limit the ability to respond swiftly to market shifts.
AI is solving these productivity challenges in surprisingly practical ways. Instead of the sci-fi idea of AI creating entire applications from scratch, the real change is happening through intelligent assistance that enhances human abilities.
The key insight is that AI doesn't replace the creative, problem-solving parts of development. Instead, it takes care of routine, predictable tasks that eat up developer time without providing any creative value.
Amazon Q Developer represents the next step in AI-powered development tools. Unlike basic code completion tools, it's built as a full assistant that comprehends and supports the entire software development lifecycle.
Here's what makes Amazon Q Developer especially powerful:
Multi-Step Task Automation: Instead of only suggesting code snippets, Amazon Q Developer can plan and carry out complex, multi-step tasks. For example, it can analyze a legacy application, develop a modernization plan, and then systematically apply the changes across multiple files and configurations.
Enterprise-Grade Security and Compliance: Amazon Q Developer is designed to meet enterprise standards. It supports VPC endpoints, works with AWS IAM for access control, and features audit logging via AWS CloudTrail. This ensures it is suitable for organizations with strict security and compliance needs.
Contextual Understanding: The AI doesn't just see individual code files – it comprehends your entire project structure, dependencies, and coding patterns. This awareness allows for smarter suggestions and helps prevent inconsistencies.
Real-World Impact: The results are clear. Organizations using Amazon Q Developer have experienced significant gains in developer productivity, according to data presented at AWS re:Invent 2024.
These aren't theoretical improvements, they're based on real deployments across over 30 developers at organizations like DTCC, covering 71% of their programming languages and 50% of their development environments.
What distinguishes Amazon Q Developer is its agent-based approach to complex development tasks. Instead of simply generating code snippets, it can function as an autonomous agent that plans and carries out multi-step workflows.
The agent approach marks a major shift from reactive code support to proactive development automation. Instead of waiting for developers to request help, these agents can independently handle complex, time-consuming tasks.
To illustrate the practical impact of AI-powered development tools, let's go through a real-world scenario: migrating a legacy .NET Framework application to .NET 8.
You can follow this example using our complete demo repository.
Note: While AWS also offers AWS Transform specifically for .NET Framework to .NET modernization at enterprise scale, this example demonstrates Amazon Q Developer's broader capabilities across multiple programming languages and frameworks. For organizations with extensive .NET portfolios, AWS Transform may be worth evaluating alongside Q Developer's multi-language approach.
Typically, this type of migration requires weeks of manual effort, including analyzing dependencies, updating project files, refactoring code for new APIs, and resolving compatibility issues. With Amazon Q Developer, much of this process can be automated.
Our example features a demo banking application built on .NET Framework 4.8. It's a typical legacy application with the following characteristics:
This application includes two main controllers:
Using the Amazon Q extension in Visual Studio Code, you can start the migration process with a simple prompt.
"I need to migrate my LegacyBankAppDemo .NET Framework API to .NET 8."
Amazon Q Developer automatically analyzes your entire codebase and creates a comprehensive migration plan:
The AI identifies that this is a .NET Framework 4.8 Web API application with MVC components and creates a detailed migration roadmap.
Amazon Q Developer doesn't stop at the planning stage; it also begins making the actual changes for you. It updates everything that needs to change, from .NET Framework to .NET 8, such as:
Next, Amazon Q detects raw SQL queries in your controllers and converts them into proper data model classes, making your code easier to maintain. It also updates your controllers by adding the appropriate decorators and modifies your raw SQL code to use Entity Framework, following best practices.
Amazon Q automatically updates the controllers, adding all the necessary decorators to ensure proper functionality and converting all raw SQL statements into Entity Framework queries.
When you enable Agent Mode in Amazon Q Developer, it automatically creates and organizes all the new files. The system prompts for permission before performing actions that require elevated privileges, such as creating directories or modifying the project structure.
The migration process creates a complete .NET 8 project structure:
After Amazon Q Developer completes the migration, you can immediately test the results:
The migrated application runs on .NET 8 with modern features:
What usually takes weeks of manual work, such as analyzing dependencies, updating project files, refactoring controllers, implementing Entity Framework, and testing compatibility, now takes only hours with Amazon Q Developer. The AI handles the tedious, error-prone parts of migration so developers can focus on business logic and testing.
Successfully integrating AI tools like Amazon Q Developer requires more than just installation. Here are essential strategies for maximizing the benefits:
AI-powered development tools like Amazon Q Developer represent a fundamental shift in how we approach software development. Rather than incremental improvements to existing processes, we're seeing the emergence of entirely new workflows where AI handles routine tasks while humans focus on creative problem-solving.
The evidence is clear: organizations that strategically adopt these tools are seeing measurable improvements in developer productivity, code quality, and time-to-market. More importantly, developers report higher job satisfaction when they can concentrate on engaging technical challenges rather than repetitive tasks.
As we've observed from the DTCC case study and our .NET migration example, the technology is prepared for enterprise adoption now. The question isn't whether AI will transform software development, but how quickly your organization will adapt to this new reality.
The competitive edge will go to organizations that effectively incorporate AI into their development processes while preserving human insight and creativity that promote true innovation. The future of software development is human-AI partnership, and that future is happening now.
At Caylent, we help organizations modernize legacy applications and accelerate their transformation journeys with our Application Modernization solution. By leveraging modern, managed AWS services, we eliminate the undifferentiated heavy lifting, such as scaling, patching, and infrastructure management, so your engineering teams can focus on building great products and delivering business outcomes. Whether you're moving off monolithic systems or optimizing existing applications, we help you unlock improved performance, reduced costs, faster time to market, and more. Contact us today to get started.
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Vinicius Ganancio
Luiz Soares