
Making the Switch: The Reality of Moving from Windows to Mac for Your Software Engineering Team
If you have a team of software engineers and want to move them to Mac, you will need to consider a number of things before you do so.
If you have a team of software engineers and want to move them to Mac, you will need to consider a number of things before you do so.
Here’s what’s new in our January 2023 Release Notes:
* Tables Columns Sorting Improved
* Reconcile Commits Count Between KPI Card and the Table
* Efficiency Tab Improvements and Efficiency KPI Cards Align
Soon, software companies will be actively using AI for Agile software development projects. Well, that’s at least what we hope, as we continue upgrading our performance analytics into an AI for Agile project management and DevOps. Some have expressed an interest in how AI fits to Agile values and principles. There’s not a whole lot out there on this matter. So, let’s explore!
The focus here is on using AI in conjunction with Agile software development. There may be some overlap, but this shouldn’t be confused with using Agile for AI development projects or creating AI systems. For that, you might check out the following articles:
You can find the full Agile Manifesto and other Agile essentials over at the Agile Alliance.
AI serves to make it easier and faster for real people to carry out their work more accurately. This is especially true when it comes to working with large amounts of complex data, as is definitely the case when managing software development teams. Software development is expensive. The larger the company and/or project, the more complex it is and the more inclined it is to be challenged or fail outright.
AI heavily reinforces Agile’s first value, that, people come first. Everything about software development boils down to individual developers and team dynamics. Using AI for Agile project management involves a focus on continuously improving each developer’s skill and aptitude for teamwork. Everything else is a natural and logical extension of helping all software development stakeholders achieve their full potential and work better as a team.
Remember – successful software, at a minimum, is delivered on time, on budget, and according to specifications – all of which depend on team skill and teamwork. AI helps managers, and actually all stakeholders, better channel the resources, training, and mentoring, as well as improve work processes and team interaction to help everyone do their best.
Agile’s 4 Values | How AI Fits |
1) Individuals and Interactions Over Processes and Tools |
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2) Working Software Over Comprehensive Documentation |
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3) Customer Collaboration Over Contract Negotiation |
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4) Responding to Change Over Following a Plan |
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One of the biggest concerns some engineering managers and developers have about AI is its potential as a tool to eclipse the value of people. It is a tool, yes. But it can make people’s jobs a lot easier. If you had to dig a mile-long, five-foot deep trench, a shovel would suffice – but it would be oh, so much easier with an excavator! Let AI do the heavy lifting.
Agile’s 12 principles are an extension of the four values above, so there’s some redundancy.
Agile Principles | How AI Fits |
1. Customer satisfaction by early and continuous delivery of valuable software. |
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2. Welcome changing requirements, even in late development. |
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3. Deliver working software frequently (weeks rather than months) |
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4. Close, daily cooperation between business people and developers |
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5. Projects are built around motivated individuals, who should be trusted |
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6. Face-to-face conversation is the best form of communication |
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7. Working software is the primary measure of progress |
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8. Sustainable development, able to maintain a constant pace |
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9. Continuous attention to technical excellence and good design |
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10. Simplicity—the art of maximizing the amount of work not done—is essential |
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11. Best architectures, requirements, and designs emerge from self-organizing teams |
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12. Regularly, the team reflects on how to become more effective, and adjusts accordingly |
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The boldface element dealing with metrics critical to organizational objectives is especially interesting from an org-wide perspective. It’s not just for engineers or getting down to the nitty-gritty of excellent code and coding practices. The CEO, HR and BI Teams, and others, probably aren’t coding, but what they do directly and indirectly impacts code. And too often, different teams work at cross-purposes. Shocking!
Similar situations can play out by swapping the BI Analyst with Sales Teams not signing enough new clients or perhaps signing too many, too fast. For fast-growing companies, HR teams can be very hard-pressed to find enough developers with the right skills (and salary expectations). More or less the same net effect. Similarly, a number of companies are pushing out releases for early access games with excessive defects – some so bad that they kill sales.
Leastwise, there exists any number of situations where teams within the same company can be pursuing results that come at the expense of other teams. It’s not just a technical issue.
So, let’s play the same game wherein everyone is working together toward improving critical metrics.
Okay, so that’s a little cheesy, and maybe an oversimplification, but organizationally, there’s a big difference between working together – or at cross-purposes. When it comes to developing Technical Excellence, the last thing anyone wants is Chaos.
Article posted: May 04, 2022
If you have a team of software engineers and want to move them to Mac, you will need to consider a number of things before you do so.
Here’s what’s new in our January 2023 Release Notes:
* Tables Columns Sorting Improved
* Reconcile Commits Count Between KPI Card and the Table
* Efficiency Tab Improvements and Efficiency KPI Cards Align
Here’s what’s new in our December 2022 Release Notes:
* Developing Improvements for On-Prem Data Processing;
* Improving Jira Data Connection;
* Aligning Metrics throughout the Application.