This portfolio of documents illustrate how artificial intelligence. Web 2.0 technologies, open-source software, and agile development are changing the way that products and services are documented.
Learning Python and Generative AI: A Self-Study Guide
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I created an article to learn Python for Generative AI development with the creation of a "Human Voice Preserving" AI agent as the capstone project.
Researched, planned, and created the conceptual, task, and reference topics for open-source user interface components ( https://github.com/predixdesignsystem ) that enable developers or designers to quickly and easily create industrial web applications that run on dedicated Predix services and data. View Publication
The impact on documentation is huge when project teams adopt agile practices to plan and deliver products and services. Key Takeaways: Agile Principles and Technical Documentation: Agile development prioritizes working software, collaboration, and adaptability, which significantly impacts technical documentation. Shift from Formal Specifications: In agile, writers must rely on working software, not formal specifications, to create documentation. Dynamic Documentation: Agile emphasizes creating documentation that is relevant, stable, and continuously updated based on feedback. Audience Analysis: Understanding the target audience is crucial for creating effective documentation. User Stories and Tasks: User stories and tasks provide a structured approach to breaking down documentation requirements. Continuous Delivery and Kanban: Agile's focus on continuous delivery and the use of kanban boards help ensure that documentation aligns with the evolving product. The article also inc...
The article highlights a shift in the approach in product documentation (particularly in smaller startups) from commercial software like Microsoft Word and Adobe FrameMaker that are industry standards. The trend is now towards open-source alternatives like Apache OpenOffice and LibreOffice. View Publication
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