The enterprise world is filled with mission-critical applications built on robust, yet aging, technologies like COBOL and older Java versions. These systems, while reliable, are often a major source of technical debt, slowing down innovation and feature delivery.
As a software engineer my first job in the 1980s already was centered around these challenges. As one of the first Java trainers in the 1990s I know how hard this endeavor is. Now these first Java systems are the legacy systems of today. Lets create the next generation of systems by learning from the past.
A complete, "big-bang" rewrite is a daunting and risky undertaking that many organizations simply can't afford. Companies have gone down the drain by doing this.
But what if there was a different way? A safer, faster, and more effective approach that combines proven architectural patterns with the power of artificial intelligence, all guided by the principles of Agile and Scrum?
The Strangler Fig Pattern: An Evolutionary Way Forward
Instead of a high-risk, all-at-once rewrite, we can embrace an evolutionary approach. I love the idea that was famously described by software architect Martin Fowler as the Strangler Fig Pattern. As he explains in his article Original Strangler Fig Application, the pattern is named after a type of fig tree that grows around a host tree, eventually replacing it.
In software, the same principle applies. You gradually build new, modern applications and services around your legacy system. A facade or a reverse proxy acts as a "switch," redirecting traffic for specific functionalities from the old system to the new one. Over time, the new system takes on more and more responsibilities, effectively "strangling" the legacy system until it can be safely decommissioned. This approach significantly reduces risk, allows for continuous delivery, and provides immediate value to the business.
AI as Your Accelerator: Introducing Autonomous Code Generation
While the Strangler Fig Pattern provides the strategic blueprint, platforms like Blitzy and Cursor can serve as your AI-powered co-pilot. By automating the most tedious and time-consuming parts of the modernization process, these tools allow your human teams to focus on high-level architecture and strategic decisions.
Imagine a tool with "infinite code context" that can:
- Analyze Your Legacy Code at Scale: It can understand the complex logic and dependencies of your old COBOL or Java codebase, identifying the best parts to break out as new services. Manually done, this is a tedious process.
- Generate New Code Autonomously: It can translate legacy logic into a modern language and automatically generate the new services, completing the bulk of the coding work for you. Code review is left to the developers.
- Accelerate the Migration: By handling the "80% built autonomously," Blitzy allows your engineers to focus on the crucial remaining "20%" – ensuring seamless integration and a perfect fit with your new architecture. This drastically speeds up the entire transformation process.
Scrum: The Agile Engine for Success
No matter how powerful your tools are, a successful modernization effort requires a disciplined framework. Scrum provides the perfect structure to manage this complex endeavor:
- Prioritized Backlog: The Product Owner works with stakeholders to prioritize which legacy functionalities to "strangle" first, ensuring the team is always working on the highest-value items. AI will be a valuable support when applied courageously.
- Iterative Sprints: The work is broken down into manageable Sprints. Each Sprint delivers a new, working piece of the modern application, allowing for continuous feedback and adaptation. We do not just want feedback. We want new ideas how to go to the next level. It is a learning process, not a criticism loop.
- Empowered Teams: Your Scrum Team, augmented by AI, is empowered to make decisions and continuously improve their process. Retrospectives become a powerful tool for optimizing how you leverage the AI platform and refine your strategy. We need amplifying feedback. This includes a personal growth in involved people. Learning to hear feedback as input for amplification. I know, from own experience, how hard it is not to hear feedback as criticism. It easily triggers the psychological pattern of “I am a failure”.
By combining the low-risk Strangler Fig Pattern, the raw power of AI code generation, and the agile discipline of Scrum, you can finally overcome the challenge of legacy code. This isn't just about updating your tech stack; it's about unlocking a new level of innovation and agility for your entire organization. Feedback loops are more than reviews. Feedback is easily confused with criticism. Here we want new levels of creativity loops.