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git commit -m "AI: Know when to use it"
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**Explanation of the commit message:**

*   **Concise:** It's short and to the point, adhering to the common 5-word limit.
*   **Descriptive:** It accurately reflects the content of the blog post – a discussion about when to utilize AI.
*   **Action-oriented:**  Implies a need for thoughtful consideration.
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src/content/when_to_use_ai.md

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+# When to use AI
+
+## The Great AI Debate: When to Trust the Machine vs. When to Stick to Your Brain
+
+As a journalist, software developer, and DevOps expert, I’ve spent years navigating the murky waters of AI’s “what if” scenarios. The question that keeps coming up professionally is: *“When to use AI?”* And the answer, like many things in life, is *“It depends.”* But when I’m not using my brain, I’m using my shudders. Let’s dive into the scenarios where AI isn’s the best choice—and where it *is* the best choice.
+
+## When AI is Not the Best Choice
+
+### 1. **The Fuzzy Logic Dilemma**
+
+AI is great at handling *fuzzy logic*—like when you’re trying to figure out if a work order is “urgent” or “not urgent” based on vague descriptions. But when you’re trying to map a work type to a specific work request, AI is *not* the best choice. Imagine this: You have a dataset of work orders, each with a type (e.g., “installation,” “repair,” “maintenance”) and a duration in days. You’re trying to group these into two categories: *“high-priority”* and *“low-priority.”* The problem? The work types and work requests are *tangentially related*.
+
+> *“I was given a list of work types that could be grouped into 1 of 2 categories exclusively.”*
+> *“The problem was… the ‘work types’ and work requests were at best tangentially related.”*
+
+So I had to manually read each work type and map it to a work request. It was a *shudder-inducing* task. AI, on the other hand, would have *automated* that. But it would also have *misunderstood* the relationship between the two.
+
+### 2. **The Math and Logic Job**
+
+AI is great at math and logic. If you need to calculate the total time spent on a process, or create a formula that accounts for variables like labor hours, weather, or equipment downtime, AI can handle it. For example, I once built a spreadsheet that calculated potential savings in a process. The formulas were precise, and the logic was sound.
+
+> *“Traditional programming methods work on maths and logic that is sound and offers no chance for interpretation.”*
+
+So even if AI could suggest the numbers, I’d never trust it to actually run the calculation. It’s like trusting a robot to drive a car when it’s not built for that.
+
+## When AI is the Best Choice
+
+### 1. **Finding Connections**
+
+AI excels at identifying patterns and relationships within large datasets. This is invaluable for tasks like customer segmentation, fraud detection, and predictive maintenance.
+
+### 2. **Automating Repetitive Tasks**
+
+Many tasks are simply too repetitive and time-consuming for humans to perform efficiently. AI-powered automation can free up valuable time and resources.
+
+### 3. **Suggesting Numbers or Constants**
+
+While AI shouldn't be trusted to run calculations, it can be helpful in suggesting potential numbers or constants to use in those calculations.
+
+## The Human vs. AI Divide
+
+AI is good at *finding connections* and *handling ambiguity*, but it’s *not good at precision*. When you need to ensure that a calculation is accurate, or that a mapping is flawless, AI is not the best choice. And that’s where humans shine. We’re good at *seeing* the connection between two things, even if it’s not obvious. We’re good at *precision* and *accuracy*.
+
+> *“I was given a list of work types that could be grouped into 1 of 2 categories exclusively.”*
+> *“The problem was… the ‘work types’ and work requests were at best tangentially related.”*
+
+So I had to manually read each work type and map it to a work request. It was a *shudder-inducing* task.
+
+## The Final Thought
+
+So, in summary:
+
+*   **AI is not the best choice** when you need precision, accuracy, or a human touch.
+*   **AI is the best choice** when you need to handle ambiguity, find connections, or automate repetitive tasks.
+
+And that’s why I’m a journalist, a developer, and a DevOps expert. I know when to trust the machine and when to rely on my brain.
+
+> *“When in doubt, just do it.”*
+
+## Editable Structure for Easy Customization
+
+### 📝 Title When to use AI
+
+### 🧠 Introduction
+
+*   Briefly explain the question and the tone.
+
+### 🧩 Sections
+
+1.  **When AI is Not the Best Choice**
+    *   Subpoints:
+        *   Fuzzy logic dilemmas
+        *   Manual mapping tasks
+        *   Precision vs. AI’s “fuzzy” logic
+2.  **When AI is the Best Choice**
+    *   Subpoints:
+        *   Math and logic tasks
+        *   Automation of repetitive tasks
+        *   Suggesting numbers or constants
+3.  **The Human vs. AI Divide**
+    *   Highlight the importance of human judgment in critical tasks
+4.  **Final Thought**
+    *   Encourage readers to think critically about when to use AI
+
+### 📝 Conclusion
+
+*   Wrap up the key points and reinforce the message.
+
+## Tips for Editing
+
+*   Replace the example about the spreadsheet with your own scenario.
+*   Add a personal anecdote or a relatable example.
+*   Use humor to keep the tone light and engaging.
+*   Add a call to action: “Next time you’re stuck, ask yourself: ‘Is this a task for AI or a task for me?’”