Cloud Computing

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 to Balance Quality and Tight Deadlines in a Web3 Project

As a Software Release Manager or a TPM, how often have you faced the pressure of delivering a Web3 project, built on blockchain technology, under a tight deadline? You aim to release a stable, bug-free product; However, the clock is ticking. Balancing quality with time constraints is tough, yet achievable with your right approach. By

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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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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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Important Safeguards Against a Microsoft Office 365 Outage

Recently (Last month), a major Microsoft outage primarily affected Office 365 and Teams, disrupting business operations, collaboration, and communication. As with any global software outage, users faced difficulties accessing emails, documents, and essential business tools. To help businesses stay operational during such disruptions, I wrote an article outlining key strategies. While Microsoft outages can be

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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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Azure DevOps vs. Jira: Which Agile Tool Fits Your Workflow?

Over the years, I’ve noticed that ‘tech community’ frequently debates about their choice between JIRA Confluence and Azure DevOps – Kanban for project management. Cost has always been a focal point & a deciding factor. While I have extensive experience with Azure DevOps – Kanban, these ongoing discussions prompted me to take a deeper dive

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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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