How Prepared Should You Be When Learning AI?
- Patrick Law
- Aug 13
- 2 min read
Learning AI can feel intimidating—especially if you think you need to be a programmer before you even start. The truth? You don’t need to be a coding genius… but you also can’t walk in unprepared. The right mindset and a few essential skills can make all the difference.
Key Strengths: Why You Can Start Now
Clear thinking beats coding – If you can break a problem into steps, you can start using AI today.
Immediate workflow benefits – AI can take over repetitive, data-heavy tasks, giving you more time for real engineering work.
Accessible tools – With platforms like ChatGPT, Make.com, and industry-specific AI software, you can start experimenting without expensive hardware or advanced degrees.
Limitations & Risks to Watch Out For
Garbage in, garbage out – Without clear, accurate inputs, AI will produce poor results.
Verification is critical – Especially in engineering, every AI output must be validated for safety, compliance, and accuracy.
Not a replacement for domain knowledge – AI amplifies your expertise; it can’t replace it.
Real-World Application
Consider pump sizing in process engineering. Traditionally, it’s a time-consuming task involving data collection, calculations, and verification. With AI, you can:
Generate a pump sizing calculation template in seconds.
Auto-pull constants and reference data from standards.
Check unit conversions instantly. The catch? You still need to feed the AI with correct specifications and validate the results before they go anywhere near a live project.
Conclusion / Call to Action
AI isn’t about replacing engineers—it’s about amplifying them. If you can clearly define a problem and validate outputs, you’re ready to start learning AI today. The sooner you begin, the faster you’ll uncover ways to automate tedious work and focus on high-value tasks.
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