agile software development
PulseAugur coverage of agile software development — every cluster mentioning agile software development across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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AI agents spark debate on agile methods, communism, and coercion
This article explores the potential societal implications of advanced AI agents, drawing parallels between their development and historical concepts like agile methodologies and communism. It questions whether the pursu…
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New frameworks reconstruct 3D objects from hand interaction videos
Two new research papers introduce novel frameworks for reconstructing 3D objects from egocentric videos, focusing on hand interactions. The first, ROHIT, uses a Constrained Optimisation and Propagation (COP) framework t…
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AI and PM Leader Generated Over $2.5B in Business Value
Scott Graffius, an AI, Agile, and Project Management leader, author, and speaker, has generated over $2.51 billion in business value. He has led initiatives across various industries including advanced technology, enter…
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Dew Drop Newsletter covers AI, .NET, and web dev topics for May 1, 2026
The Dew Drop Weekly Newsletter, issue 481, covers developments up to May 1, 2026. It includes a wide range of technical topics such as ASP.NET Core, CSS, Azure, JavaScript, C++, .NET, and AI. The newsletter also touches…
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AI modernizes Rails apps, but user needs remain a communication challenge
A session will explore strategies for modernizing Ruby on Rails applications using AI to address technical debt and scalability issues. The session will cover how AI can reverse-engineer undocumented knowledge, automate…
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Eugene Yan finds value in Scrum for data science projects
Eugene Yan shares his evolving perspective on using Scrum methodologies within data science projects. Initially resistant to its structured approach, particularly regarding estimation and the potential for iterative rew…
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Eugene Yan explores Agile and Scrum frameworks for data science effectiveness
Eugene Yan's articles explore the application of Agile and Scrum frameworks within data science teams, highlighting both their benefits and challenges. While Agile's iterative approach, clear task definition, and feedba…