I've been pondering the use of Python for real-world automation, but rather than jumping straight into coding, I'm interested in exploring a more strategic approach. Before I dig into writing any code, I have some key questions in mind: What should be automated versus what should remain manual? In what situations does Python provide a real advantage instead of just adding complexity? At what point does a simple script require more structure, logging, and accountability? Also, how much of the buzz around AI in automation is actually useful versus just hype?
From what I've observed, most automation focuses on linking systems, outlining boundaries, and determining what should not be automated, rather than just clever code. I'd love to know how others in this space think about these topics:
- Do you design your automation as pipelines, services, or quick scripts?
- How do you assess when Python is the most suitable tool compared to alternatives?
- What early mistakes have shaped how you now approach automation?
I'm looking for insights into mental models, trade-offs, and lessons learned rather than code examples. How do you tackle this?
2 Answers
You should definitely frame your questions around automation in broader terms, as they apply to any programming language, not just Python. It might even be worth broadening your discussions to include other automation tools too!
Prepping for automation without code can seriously boost your workflow. It's all about pinpointing the tasks you want to automate and the results you expect. This clarity helps you select the right Python tools or libraries for the job. I find that sketching out flowcharts or writing some pseudocode can be super helpful in mapping out your plan before you start coding.
Thanks for the suggestion! I'll consider that for a more well-rounded perspective.