Every major technological shift follows the same pattern. A new tool emerges that automates the technical work, freeing professionals to focus on higher-level strategy and creative problem-solving.
When CAD first showed up in the 1980s, plenty of engineers resisted. They trusted their drafting skills. They didn't want to learn a new tool. They thought computers would make engineering less creative, less human.
The engineers who adopted CAD had significant advantages:
- • Explore more ideas in the same time. No more starting from scratch for every variation.
- • Catch flaws early. Run simulations before building prototypes.
- • Handle more complexity. Manage systems that were impossible with hand drawings.
- • Work together seamlessly. Share files instantly, collaborate from anywhere.
CAD enabled faster iteration. Engineering moved faster. Designs got more sophisticated. Development cycles shortened. Better products reached market quicker.
Strategy Matters, Not Technical Minutiae
CAD never invented an airplane on its own. It let people design better ones, faster. The engineer still decided what to build, how it should work, and whether it was worth building at all.
LLMs work the same way. They don't know what matters. They don't have taste or judgment. They hallucinate. They miss nuance. They're bad at deciding what's worth saying—that's your job.
For Software Engineers: APIs Are Memory, Architecture Is Expertise
If you're a software engineer, you've probably noticed you don't need to memorize API documentation anymore. LLMs handle the syntax, boilerplate, and implementation details. That's genuinely useful.
But "vibe coding" your way through complex systems won't get you there. Building scalable, reliable software still requires deep understanding of system design, performance trade-offs, and architectural decisions. The difference is where you spend your mental energy.
You're not debugging syntax errors or looking up function signatures. You're focused on system design and data flow, performance bottlenecks and scaling challenges, security implications and edge cases, code maintainability and team collaboration.
This Is How It Looks in the Wild
A founder outlines a pitch deck in ten minutes instead of three hours. Not because the AI wrote the deck, but because it helped her test different structures, find the right narrative, and polish the language.
A marketer whips up five landing page headlines to test this week. Instead of agonizing over one "perfect" option, she's running experiments with variations she never would have thought of.
A PM turns raw user feedback into clear action items overnight. The AI helps organize themes, identify patterns, and draft recommendations that would have taken days to synthesize manually.
CAD Made Engineering Better. LLMs Will Do the Same for Ideas.
Most people struggle with LLMs because they don't know what they're actually good at. They either dismiss them entirely or get frustrated when the results don't match their expectations.
The people who get real value from LLMs understand they need direction. They learn what works, what doesn't, and how to guide the process effectively.
Working with LLMs effectively means being methodical: rough sketch your ideas before you commit to a direction, stress-test different versions to see what resonates, see how they land with different audiences, keep tweaking until it works instead of settling for "good enough."
When CAD showed up, it didn't just make drafting faster. It unlocked a level of complexity engineers couldn't handle on paper. LLMs handle the implementation details. They help you iterate faster and explore more variations. They'll let you explore ideas you wouldn't have had time to develop.