Comment by rubicon33

To be meta about it, I would argue that thinking "generatively" is a craft in and of itself. You are setting the conditions for work to grow rather than having top-down control over the entire problem space.

Where it gets interesting is being pushed into directions that you wouldn't have considered anyway rather than expediting the work you would have already done.

I can't speak for engineers, but that's how we've been positioning it in our org. It's worth noting that we're finding GenAI less practical in design-land for pushing code or prototyping, but insanely helpful helping with research and discovery work.

We've been experimenting with more esoteric prompts to really challenge the models and ourselves.

Here's a tangible example: Imagine you have an enormous dataset of user-research, both qual and quant, and you have a few ideas of how to synthesize the overall narrative, but are still hitting a wall.

You can use a prompt like this to really get the team thinking:

"What empty spaces or absences are crucial here? Amplify these voids until they become the primary focus, not the surrounding substance. Describe how centering nothingness might transform your understanding of everything else. What does the emptiness tell you?"

or

"Buildings reveal their true nature when sliced open. That perfect line that exposes all layers at once - from foundation to roof, from public to private, from structure to skin.

What stories hide between your floors? Cut through your challenge vertically, ruthlessly. Watch how each layer speaks to the others. Notice the hidden chambers, the unexpected connections, the places where different systems touch.

What would a clean slice through your problem expose?"

LLM's have completely changed our approach to research and, I would argue, reinvigorated an alternate craftsmanship to the ways in which we study our products and learn from our users.

Of course the onus is on us to pick apart the responses for any interesting directions that are contextually relevant to the problem we're attempting to solve, but we are still in control of the work.

Happy to write more about this if folks are interested.

Personally I still love the craft of software. But there are times where boilerplate really kills the fun of setting something up, to take one example.

Or like this week I was sick and didn't have the energy to work in my normal way and it was fun to just tell ChatGPT to build a prototype I had in mind.

We live in a world of IKEA furniture - yet people still desire handmade furniture, and people still enjoy and take deep satisfaction in making them.

All this to say I don't blame you for being dismayed. These are fairly earth shattering developments we're living through and if it doesn't cause people to occasionally feel uneasy or even nostalgia for simpler times, then they're not paying attention.

I share your frustration. But for better or worse, computer language will eventually be replaced by human language. It's inevitable :(

This sounds like a boomer trying to resist using Google in favor of encyclopedias.

Vibe coding can be whatever you want to make of it. If you want to be prescriptive about your instructions and use it as a glorified autocomplete, then do it. You can also go at it from a high-level point of view. Either way, you still need to code review the AI code as if it was a PR.