AI & Emerging Technologies

Balancing Quality and Budget: Practical Strategies for Release and Delivery Managers

How often do we, as Software Release, Delivery Managers, and Technical Project Managers, face this challenge of delivering high-quality Software Apps under tight budget constraints? It’s a common struggle, one that requires us to not only use our Dev and Test resources wisely, but also to enforce a disciplined change management process, promote operational efficiency, […]

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Balancing Code Quality with Project Deadlines – Especially When Stakeholders Disagree

How many times has this scenario come up in your career as a TPM? – And you said, I’ve been here before. That your sprint is halfway done, your team is knee-deep in refactoring legacy code, and suddenly, a stakeholder drops a “must-have” feature that wasn’t even in the backlog last week. Another stakeholder insists

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How AI Enhances Azure DevOps Backlog Management

I’ve been working with Azure DevOps since its transition from Visual Studio Team Services (VSTS), witnessing its evolution in both functionality and scope. With this current infusion of Artificial Intelligence (AI) and my own training in this field, my curiosity has reached new heights. I felt compelled to analyze and organize my thoughts by outlining

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How AI Enhances Azure DevOps Dashboards

After a discussion with some of my IT professional friends about my recent (Article) contribution on AI and Azure DevOps Backlogs, I decided to organize my thoughts on how AI enhances Azure DevOps dashboards. These dashboards provide teams with real-time insights into project progress, backlog management, and CI/CD pipeline performance. With an integration of Artificial

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How Explainable AI (XAI) Enhances Transparency in AI Decision-Making – Part 1

Inspired by current, rapid advancements in AI, I’ve planned a series of articles covering different emerging technologies, and this one on Explainable AI (XAI) being the first of many to come. As artificial intelligence (AI) becomes increasingly embedded in business, healthcare, finance, and everyday decision-making, so is lack of transparency in AI models which has

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The Rise of AI-Generated Impostors: Email, LinkedIn, and Beyond

Readers, beware of an alarming new trend: scammers are using AI to create highly convincing “fake identities.” These impersonators might pose as a “CEO” or “recruiter,” often using phrases like “Act now,” “This is confidential,” or “Your account will be closed.” – Artificial Intelligence (AI) is transforming industries, however, it’s also arming cybercriminals with powerful

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How AI is Transforming QA Testing & Reducing Effort

Recently, I wrote about business impact of downplaying QA (Testing), highlighting many risks of neglecting comprehensive quality assurance (QA) efforts. I also promised to follow up with an article on how to reduce development time and effort by adopting an AI-powered QA testing strategy. To be clear, my intent wasn’t to simply point out a

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How AI Can Optimize SAFe & LeSS Implementations

“LeSS” (Large Scale Scrum) “SAFe” (Scaled Agile Framework) Introduction In a discussion with my colleagues about SAFe & LeSS, some of them asked if I could write a concise, easy-to-digest version on “How AI can optimize SAFe and LeSS implementations”. It took me some time to dive into the topic, but after researching, I’ve gathered

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How To Train Reliable Dataset for an AI Model

There is a growing concern within the IT community about reliability of AI. Some schools of thought question the accuracy and trustworthiness of AI-generated results, particularly due to quality and biases of datasets used to train these models. I dedicated some time to research methods to counter these concerns and explored ways to verify data

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AI with Human Decision Making – Strikes a Right Balance in Agile Methodology

There has been an extensive discussion about AI and human interaction in Agile Methodology. In reality, AI and human decision-making are not opposing forces, they are complementary allies. AI enhances efficiency, predictability, and risk management, while human intuition, creativity, and emotional intelligence remain crucial for Agile success. By finding a right balance, organizations can leverage

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