A lot of social posts focus on grand ways to optimise life and work with AI.
This is not one of those posts.
Knowing what not to do often steers us better than searching for countless ‘best practices’. Let’s discuss the common mistakes you can dodge with AI collaboration.
Unfortunately, too many people want amazing results now without the thought process behind it.
You try to outsource your thinking to AI
Don’t do this. It won’t end well.
Neither does:
- Delegating everything to AI
- Not reviewing and editing AI outputs
- Forgetting about your human skills
Fret not, friend. All hope is not lost.
You can dodge these mistakes by:
Step 1: Getting clear on AI limitations and opportunities
AI is not a silver bullet that does it all.
It can enhance your work if used intelligently, but it can also lead you astray. Take time to research and experiment with your work. Apply your context for use cases.
Step 2: Thinking independently about tasks
So many people take the wrong turn by outsourcing their thinking to AI.
This happens because we’re looking for shortcuts and ways to optimise without the necessary effort. To avoid this, always spend time to set your intentions with AI.
Think critically about what you want to accomplish with x AI tool.
Step 3: Treating AI outputs as ugly first drafts
Probably the simplest thing you can do to not look like a fool.
Read, review and edit everything AI outputs before you share it with anyone. A smart operator combines AI and human thinking. Don’t de-skill yourself and look like a fool at the same time by relying on AI.
It’s just another tool.
Before you go… 👋
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