Professional Development – 2024 – Week 4

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.NET

“Stop Using null, Use default Instead in C#” | Code Cop #010 (via Nick Chapsas)

The downside is that you have to look in two places to understand what the code is doing: the return statement, and the return type. For enumerable types, don’t return null: Return an empty collection.

The Magic of Breaking Down Your Types in C# (via Nick Chapsas)

  • Object deconstruction is a way of turning types that have multiple components — for example, KeyValuePair has Key and Value — into individual components returned as a tuple.
  • The Deconstruct method uses N out parameters to return a tuple with N elements.
  • Note that record types get this without any additional effort — they are compiler-generated.
  • If you don’t own the type, you can make extension methods that act the same way. Naming the method Deconstruct is important.
  • Many base class libraries already implement this to some degree.

Business

9 Trends That Will Shape Work in 2024 and Beyond (via HBR)

  1. Organizations will offer creative benefits to address the costs of work.
  2. AI will create, not diminish, workforce opportunity.
  3. Four-day workweeks will move from radical to routine.
  4. Employee conflict resolution will be a must-have skill for managers.
  5. GenAI experiments will yield hard lessons and painful costs.
  6. Skills requirements will overtake degree requirements as the “paper ceiling” crumbles.
  7. Climate change protection becomes a new employee benefit.
  8. DEI won’t disappear; it will become more embedded in the way we work.
  9. Traditional stereotypes of career paths will collapse in face of workforce change.

5 Reasons People Get Laid Off (via HBR)

  1. Lack of skills advancement
  2. You’re an overseer, not a doer
  3. Lack of visibility
  4. Lack of performance
  5. Offshoring and automation

Technology

Getting Machine Learning Projects from Idea to Execution (via HBR)

  1. Establish the deployment goal
  2. Establish the prediction goal
  3. Establish the evaluation metrics
  4. Prepare the data
  5. Train the model
  6. Deploy the model