This episode of Techsplainers explores COBOL modernization strategies for organizations managing critical legacy systems written in this 60-year-old programming language. We examine why COBOL remains vital today—processing 95% of ATM transactions and 90% of global financial transactions—while highlighting the pressing challenges of maintaining these systems amid a growing skills gap, integration difficulties, and scalability concerns. The discussion covers various modernization approaches, from less disruptive strategies like rehosting and refactoring to more transformative methods like rearchitecting and replacement. We share key best practices for successful modernization, including thorough application documentation, business-value prioritization, preservation of essential business logic, and incremental implementation. The episode emphasizes that effective COBOL modernization isn't about wholesale replacement but thoughtful evolution that preserves decades of refined business logic while enabling future innovation. Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

This episode of Techsplainers examines COBOL modernization approaches—from rehosting and refactoring to complete replacement—helping organizations evolve critical legacy systems while preserving valuable business logic. 

What is COBOL modernization?

Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.

Techsplainers by IBM

This episode of Techsplainers explores legacy code—software that continues to deliver value despite being inherited, outdated, or difficult to modify. We examine how these systems, though challenging, often represent significant business value and intellectual property, running critical operations across industries from banking to government. The discussion covers the main challenges legacy code presents: knowledge gaps from departed developers, accumulated technical debt, outdated technologies, poor documentation, and integration difficulties. We explore practical approaches to managing legacy systems, including incremental modernization through refactoring, the service wrapper approach, complete rewrites when necessary, and hybrid strategies. The episode concludes with best practices for working effectively with legacy code, emphasizing the importance of documentation, testing, incremental changes, and maintaining respect for systems that have successfully powered business operations for years. Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

This episode of Techsplainers examines legacy code challenges and strategies, from incremental modernization to service wrappers, helping organizations maintain vital systems while evolving their tech landscape. 

What is legacy code?

This episode of Techsplainers explores how artificial intelligence is transforming one of developers' most dreaded tasks: code documentation. We examine how AI-powered tools can automatically generate human-readable explanations of code, bringing consistency, efficiency, and improved maintenance to software development teams. The discussion covers key benefits of AI documentation, including time savings, comprehensive coverage, and knowledge preservation, while providing practical tips for effectively implementing these tools. We highlight the importance of using AI as a starting point rather than a complete solution, establishing clear documentation standards, and integrating tools directly into development workflows. The episode also addresses current limitations of AI documentation and the evolving landscape of tools that are making documentation more interactive and contextually relevant. Whether you're a seasoned developer or new to programming, this episode offers valuable insights into how AI is solving one of software development's persistent challenges.&nbsp; Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

This episode of Techsplainers examines how AI tools are revolutionizing code documentation, saving developer time while creating more consistent, comprehensive, and maintainable software documentation. 

AI code documentation: Benefits and top tips

This episode of Techsplainers explores Code LLMs, specialized AI models that are transforming software development by understanding, generating, and explaining code. We examine how these models differ from general-purpose LLMs through their extensive training on programming languages, documentation, and code repositories, giving them a deeper understanding of software development concepts and patterns. The discussion covers how Code LLMs work through transformer architecture and reinforcement learning from human feedback, as well as their substantial benefits for developers, including increased productivity, enhanced learning opportunities, improved documentation, and democratized access to coding. We highlight practical applications such as code generation, bug fixing, refactoring, and test creation, while also addressing important limitations including potential security vulnerabilities, challenges with complex code, intellectual property concerns, and the risk of over-reliance. The episode concludes with insights into how these tools are reshaping the development landscape, with developers increasingly shifting toward a supervisory role focused on architecture and design decisions. Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

This episode of Techsplainers explores code refactoring—how developers restructure code to improve quality while maintaining functionality, using techniques like Extract Method and removing duplication. 

What is code refactoring?

This episode of Techsplainers explores Integration Platform as a Service (iPaaS), a cloud-native solution that connects disparate business systems and applications. We examine how iPaaS differs from traditional middleware approaches and note key use cases including data synchronization, streamlined automations, AI-powered optimization, governance, and B2B integration. &nbsp;&nbsp;The episode highlights industry-specific applications in healthcare, banking, and manufacturing, along with significant benefits like operational efficiency, improved accessibility through no-code tools, and enhanced security. We also discuss future trends, including how iPaaS helps combat SaaS sprawl and leverage unstructured data for AI training and autonomous agent development. With organizations achieving up to 345% ROI after implementation, iPaaS is becoming an essential component of modern digital transformation strategies.&nbsp; Find more information at https://www.ibm.biz/techsplainers-podcast&nbsp;Narrated by Dan Segal&nbsp;

This episode of Techsplainers explores iPaaS use cases across industries, from automating workflows to connecting applications, with real-world examples of how this integration technology drives digital transformation. 

iPaaS examples and use cases

This episode of Techsplainers explores Integration Platform as a Service (iPaaS), a cloud-based solution that connects applications, systems, and data sources across diverse IT environments. We explain how iPaaS emerged to address the challenge of SaaS sprawl—where organizations use hundreds of different applications—and how it offers pre-built connectors, low-code interfaces, and centralized monitoring. The episode walks through how iPaaS works, how it compares to traditional approaches like Enterprise Service Buses and API management, and its various use cases from app-to-app integration to AI-powered workflows. Listeners will learn about the benefits of iPaaS, including reduced complexity, lower costs, improved data accessibility, and increased scalability, all of which help organizations streamline operations and break down data silos in increasingly complex IT ecosystems.&nbsp; Find more information at https://www.ibm.biz/techsplainers-podcast&nbsp;Narrated by Dan Segal&nbsp;

This episode of Techsplainers demystifies iPaaS—cloud-based integration platforms that connect diverse apps and data sources, helping organizations break down silos and automate workflows without complex coding. 

What is iPaaS (integration platform as a service)?

This episode of Techsplainers explores enterprise application integration (EAI), the crucial technology that connects disparate business systems and software applications across organizations. We explain how EAI works through both synchronous and asynchronous processing methods, and breaks down five key architectural patterns including point-to-point, hub and spoke, service-oriented architecture, microservices, and event-driven approaches.&nbsp;&nbsp;&nbsp;The discussion covers how EAI compares to related technologies like iPaaS, EDI, and ERP systems, while highlighting major benefits including legacy system integration, elimination of data silos, and increased business agility. The episode also addresses challenges like security vulnerabilities, migration issues, and performance limitations, before concluding with a look at how modern innovations like AI-powered integration and low-code tools are transforming EAI for today's enterprise environments.&nbsp; Find more information at <a href="https://www.ibm.com/think/podcasts/techsplainers" rel="noopener noreferrer" target="_blank">https://www.ibm.com/think/podcasts/techsplainers</a>&nbsp;&nbsp;Narrated by Dan Segal&nbsp;

This episode of Techsplainers explores enterprise application integration (EAI), showing how businesses connect disparate systems using various architectures from point-to-point to microservices. 

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