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    Home»Markets»GitHub Copilot and AI Brokers Remodel Legacy Techniques
    GitHub Copilot and AI Brokers Remodel Legacy Techniques
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    GitHub Copilot and AI Brokers Remodel Legacy Techniques

    By Crypto EditorOctober 14, 2025No Comments3 Mins Read
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    Ted Hisokawa
    Oct 14, 2025 17:06

    GitHub Copilot and AI brokers are revolutionizing the modernization of legacy programs, making out of date COBOL programs accessible to as we speak’s builders, in keeping with GitHub’s insights.

    GitHub Copilot and AI Brokers Remodel Legacy Techniques

    In an period the place legacy programs nonetheless underpin important international infrastructures, GitHub Copilot and AI brokers are stepping as much as modernize these outdated frameworks. Based on a report by GitHub, these applied sciences are significantly efficient in making COBOL programs, which have been in use for over six a long time, accessible to up to date builders.

    The Problem of COBOL

    COBOL, a programming language that predates the web, stays integral to many banking, insurance coverage, and authorities programs. Regardless of its significance, discovering builders expert in COBOL is more and more tough as the unique consultants retire. This has left a good portion of the world’s 200 billion strains of COBOL code in want of modernization.

    AI-Powered Options

    Julia Kordick, a Microsoft International Black Belt, has been on the forefront of utilizing AI to modernize COBOL programs with no need to study the language. By leveraging AI for reverse engineering, her staff can extract and doc enterprise logic, establish dependencies, and supply a complete understanding of legacy codebases.

    A Systematic Strategy to Modernization

    Kordick’s staff employs a three-step framework for modernization: code preparation, enrichment, and automation aids. GitHub Copilot assists in reverse engineering code to know its performance, whereas AI brokers enrich this understanding by translating and analyzing the code’s construction.

    Automation aids additional scale this course of, permitting for the technology of name chain maps and test-driven modernization plans. These steps not solely streamline the modernization course of but additionally be sure that human consultants stay integral to validation and oversight.

    Actual-World Utility and Limitations

    Whereas AI gives important efficiencies, Kordick warns that it’s not a panacea. Human experience is important for validating AI-generated evaluation, and the distinctive complexities of every COBOL codebase imply that full automation just isn’t but possible. Nonetheless, AI has already reworked legacy modernization from a frightening process right into a manageable undertaking.

    Open-Supply Framework for COBOL Modernization

    GitHub and Microsoft have open-sourced a framework constructed with Microsoft Semantic Kernel, providing a sensible start line for organizations seeking to modernize their legacy programs. This framework contains a number of specialised brokers that deal with varied elements of the modernization course of, from dependency mapping to value monitoring.

    The framework is designed to maintain organizations answerable for their mental property whereas permitting inner groups to study and adapt to new enterprise logic as modernization progresses.

    For extra detailed insights, go to the total article on [GitHub](https://github.weblog/ai-and-ml/github-copilot/how-github-copilot-and-ai-agents-are-saving-legacy-systems/).

    Picture supply: Shutterstock




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