Kategorie: Developer Productivity

May the LLM be with You – On Planes and German Trains

This article explores the use of local Large Language Models (LLMs) as coding companions during travel, offering insights into the practicality and performance of offline LLMs for software development tasks. I share my recent experience of using these tools while flying, addressing the challenges of coding without internet access and evaluating the effectiveness of LLMs in providing coding assistance and overcoming connectivity and privacy limitations.

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How Testing and Quality Assurance Change Through AI (AI for DevEx, Part 3)

This article, part of the „AI for DevEx“ series, explores the role of AI in software testing and quality assurance. It examines AI’s potential in automating test case generation and UI/end-to-end tests, and reviews tools like ZeroStep and auto-playwright. The piece highlights the integration of testing in the development process and the current best use of AI in supporting test creation and testability. It concludes by anticipating future AI advancements in testing and code reviews.

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Writing and Improving Code with AI (AI for DevEx, Part 1)

In ‚Writing and Improving Code with AI‘, part of the AI for DevEx series, we examine the impact of AI tools like ChatGPT, GitHub Copilot, and AWS CodeWhisperer on software development. The article highlights real-world applications of these tools in code writing, improvement, and testing, underscoring the balance between AI assistance and human expertise in coding.

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Why We Need to Stop Measuring (Developer) Productivity — Part 2

Measuring developer productivity is a flawed endeavor; it often replaces uncertain realities with misleading certainties. While metrics can offer insights, they cannot directly quantify productivity. Instead of seeking elusive measures, focus on understanding and eliminating barriers to engineers‘ best work. After all, nurturing an environment for outstanding work is a more valid approach to enhancing productivity.

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