Artificial Intelligence is everywhere these days. From coding assistants to writing helpers, more and more professionals are leaning on AI to make their work easier. I’ve been experimenting with it myself, and I want to share my personal opinion about how we, as professionals, should approach using AI.
AI Is Okay, But With Conditions
I believe using AI is fine, but only under certain conditions. For developers like me, the biggest rule is: don’t put your company’s closed-source code into a public AI tool. Company code is intellectual property, and unless your company hosts its own private AI, you shouldn’t risk exposing it. The same goes for business strategies, client data, or anything confidential.
That doesn’t mean AI is off-limits at work. It just means we need to be careful. For closed projects, AI can still be useful for discussions, brainstorming new features, or exploring generic solutions—just don’t feed it sensitive details.
It’s Not About Trusting AI Outputs
For me, the issue isn’t about whether AI makes mistakes. The real concern is data handling. Every interaction with AI is data, and depending on the provider, there’s a risk that your inputs could be used to improve the model. That means your carefully written or improved code might show up later for someone else.
So, I always think about what data I’m giving away before pasting it into an AI.
Know What You’re Doing
This part is really important: AI is a tool, not a replacement for judgment.
Some people—often juniors, but not always—take AI’s answer as-is and copy it directly. That’s dangerous. Bugs, security flaws, and misunderstandings can slip right in.
It’s not really about being a senior or junior developer, though. It’s about understanding what you’re doing. Even a junior who takes time to read, adjust, and test AI output is being responsible. On the other hand, a senior blindly copy-pasting is not.
So the key is: always validate, always think.
AI as an Accelerator, Mentor, and Mirror
Here’s how I see AI in my workflow:
Accelerator → AI helps me skip boilerplate, explore patterns, or speed up repetitive tasks.
Mentor → AI teaches me real-world terminology and examples. For instance, I once wanted to learn how to create a Twibbon or photo frame template where you could insert your own picture. I didn’t even know what to call it. AI explained it was an overlay, and gave me a step-by-step example. That’s real, practical learning.
Mirror → AI is also a great tool for bouncing ideas. You can see multiple approaches, weigh them, and decide what works best.
Beyond Developers
While I’m writing this from a developer’s point of view, the same rules apply elsewhere:
A lawyer shouldn’t paste confidential contracts into AI.
A designer shouldn’t upload unreleased client assets.
A marketer shouldn’t share campaign strategies.
It’s the same principle: use AI responsibly, know what you’re doing, and protect sensitive information.
Final Thoughts
AI is here to stay, and it really can make us more productive and creative. But like any tool, it requires judgment. For me, the rules are simple:
Don’t share sensitive data.
Use AI responsibly.
Always understand and validate what you’re doing.
If we follow those principles, AI becomes not a threat, but a powerful partner in our work.