Author: Basava Raju Dontamsetti

Systems that once powered businesses reliably have now become barriers. They are costly to maintain, risky to replace, and not equipped for an AI driven world. Leaders often face a difficult choice: continue supporting aging platforms or commit scarce engineering capacity to move everything onto modern technology stacks. Modernization today is not just about doing more efficiently. It is about resilience, competitiveness, and the ability to innovate continuously.

The Hidden Cost of Delay
Technology teams are under constant pressure to deliver new features and meet customer expectations, leaving little time to focus on modernization. But postponing the re-architecture of legacy systems comes with more than just high maintenance costs. It erodes competitiveness and leaves organizations vulnerable to more agile rivals. Leaders recognize that modernization is inevitable, yet immediate demands often dominate the roadmap. The longer the delay, the greater the drag of legacy systems, slowing innovation and making future transformation even harder.

Innovation as the Turning Point
The key challenge is how to modernize without stalling the delivery of ongoing initiatives. The answer is to view modernization not as a distraction but as an opportunity. Traditional modernization approaches often force enterprises into difficult trade-offs. Lift-and-shift migrations move systems quickly but carry forward existing technical debt. Big bang rewrites aim for a fresh start but are slow, risky, and prone to failure. Incremental refactoring is safer but depends heavily on manual effort, often taking years and leaving businesses behind the pace of change. Each method addresses part of the problem, yet none fully balances speed, safety, and adaptability. What organizations need is a way to modernize while still delivering features, protecting business logic, and scaling at enterprise pace. Enter Agentic Modernization—the bridge between yesterday’s systems and tomorrow’s intelligent enterprises.

Agentic Modernization Explained
Modernization once meant heavy manual efforts, from auditing codebases to planning migrations and slowly replacing systems. Today, agentic coding tools change the game by acting like embedded teammates that analyze code end to end, make targeted changes, and work directly within development environments. These solutions integrate seamlessly into development workflows, offering capabilities such as deep analysis of entire codebases with visibility into architecture, dependencies, and hidden complexities; preservation of business logic to ensure critical rules remain intact during transformation; and automated documentation that creates clarity while addressing long-standing knowledge gaps. They provide secure integration with development environments, allowing edits, file changes, and command execution without disruption.

Built-in compliance and policy alignment ensure modernization respects regulatory standards, data privacy requirements, and internal governance rules. Additionally, these solutions continuously learn across projects, improving tools as they interact with systems, and enable acceleration at scale, allowing modernization efforts to advance more quickly than traditional approaches. For technology leaders this means modernization no longer requires a trade-off between supporting today and preparing for tomorrow. Both can advance together. 

A New Generation of AI Tools
The arrival of platforms such as Copilot, Cursor, and Windsurf, powered by advanced coding models like GPT 5 and Claude Sonnet 4, represents a turning point in how enterprises approach transformation. These tools are not limited to generating snippets of code. They can interpret entire codebases, retain business critical logic during migration, and generate documentation where none previously existed. This new class of assistants is helping organizations modernize with speed and precision, reducing risk while preserving institutional knowledge.

Choosing the Right Models and Tools for Modernization
Over the last several months I have experimented with a wide range of large language models, but two consistently stand out: GPT 4/5 and Claude Sonnet 3.5/4. Both have now become my preferred choices and I find myself standardizing on them across most modernization projects. Each model brings unique strengths across different phases of the software lifecycle. During development, GPT-5 excels at writing new features or restructuring code, following instructions precisely and confidently handling complex refactoring. For maintenance, Claude Sonnet 4 is particularly strong, offering conservative, careful updates that reduce the risk of introducing errors while preserving existing business logic. When it comes to migration from legacy frameworks or languages, I actually prefer Sonnet 4 over GPT-5, as preserving business rules and logic is critical; Sonnet’s detail-oriented and cautious approach minimizes risk while still accelerating the process. In short, GPT-5 drives rapid progress, while Sonnet 4 safeguards the foundation.

Protecting Your Code
When adopting AI assisted development, ensuring security and privacy is just as important as accelerating delivery. With Cursor, the Teams license is the safer option. It guarantees that your code is not used for training and is not stored on external servers. Code is passed only as tokens to the model API, which means the system never receives your complete repository. For organizations handling sensitive or client specific work, the Teams plan is far more appropriate than the Pro plan because it provides stronger contractual assurances.

With GitHub Copilot, the situation is similar. The Pro plan for individuals does not offer the same level of safeguards, and code may be used for training unless you opt out. By contrast, the Business and Enterprise plans promise that code will not be used for training and include compliance features such as audit logs and policy controls. These higher tiers are the better choice for enterprises that need to align with security and regulatory requirements. The bottom line is simple: Cursor Teams is the safer choice for project wide modernization where context and privacy matter, while Copilot Business or Enterprise is ideal for fast inline editing with enterprise grade safeguards.

Looking Ahead: AI Infused Architectures
True modernization goes beyond simply moving off legacy platforms; the real opportunity lies in designing architectures built for AI from the ground up. By embedding modular AI agents into applications, organizations can create systems that adapt instantly to changing user needs, execute tasks with precision through seamless API integrations, and provide interactions that feel natural and expert-like. Additionally, these AI-driven systems enhance development efficiency by automating repetitive work, reducing errors, and freeing engineers to focus on higher-value innovation.

Conclusion
Legacy no longer needs to mean limitation. AI-powered modernization allows enterprises to preserve what matters, re-architect with confidence, and deliver new capabilities without slowing down. The real advantage comes from a blend of AI tools and human expertise. Agentic coding platforms accelerate analysis, refactoring, and migration — while the judgment and experience of engineering teams ensure that delivery is consistent, high quality, and aligned with business needs.

Basava Raju Dontamsetti, Practice Director, Software Engineering at OSI Digital 
Basava has over 25 years of experience in the IT industry, specializing in global consulting, product management, process re-engineering, and technical advisory for startups. He is currently the Practice Director at OSI Digital, a leading global consulting and IT services company, where he oversees enterprise applications, software engineering, cloud enablement, and analytics services. Prior to OSI Digital, he co-founded MobiGesture, driving business strategy, global sales, and operations while building a portfolio of semiconductor and technology clients and achieving significant revenue growth. He began his career with Philips and Motorola, contributing to pioneering mobile innovations, and holds a B.S. in Electronics Engineering from Nagarjuna University and an M.S. in Electronics from Mysore University.