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Comment by mardef | Hacker News Reader

Not every engineering effort is a product in search of market fit or a community.

Some things are already very useful as just a one shot. I just made a quick app to help me pack for a trip, it updated forecasts every day, let me know when rain entered the forecast at one of my stops and gave me a checklist that helped me quell my travel anxiety.

The greatest thing that LLMs have done is allow many to achieve things that they couldn't have before. I'm incredibly disinterested in "I can do the same thing I was already doing x% faster"

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> gave me a checklist that helped me quell my travel anxiety.

it's truly fascinating how many positive descriptions of AI gesture at emotional management. I think that's the killer feature of this technology -- it makes people feel good, capable, reassured -- without the risk and vulnerability of interacting with another human.

I use Google Weather for my forecasts btw, no need to vibecode an app for that

Gathering forecasts for each leg of a trip only on the particular days for the particular location is tedious. Anyone can do it with google weather but why spend the time when you don't have to.

I can keep track of my expenses on a napkin but i'd much rather use a spreadsheet or dedicated app especially when that app is effectively free.

I asked Google Gemini to generate me a basic expense estimator to paste in ... Google Sheets. Every single formula needed editing. At least it generated the basic layout for me.

did you know that Google Weather has saved locations?

> Not every engineering effort is a product in search of market fit or a community

I think you misunderstood my point: by "legitimate stand-out products", I meant exactly that, with no connotation of commercialization. Maybe you can agree that having a high signal-to-noise ratio for (open source) projects is a desirable goal?

> Some things are already very useful as just a one shot.

I agree. I too have made or forked about a dozen apps and tools in the past few months. It would be dishonest not to consider the flipside, that this software is overfitted to the needs of a single person. Further, this hyper-bespoke software typically feature-complete within moments of the final prompt, and I have,on occasion, completely forgot about the tool/app I spent a weekend created, it clearly wasn't worth the effort I put in.

> The greatest thing that LLMs have done is allow many to achieve things that they couldn't have before.

Let's not pretend there isn't a cost to this.

> by "legitimate stand-out products", I meant exactly that, with no connotation of commercialization

The word "product" implies commercial.

> The word "product" implies commercial.

I disagree; but see where you're coming from. I'm chuckling at the irony of my word-choice: I initially had used "project" but nixed it because of its frequent association with Open Source. I instead opted for "product" as a broader term. For the sake of clarity, my original comment is referring to commercial and non-commercial software projects/products.

Spending 1 day vibecoding or modding an existing app to fit you better and not using it is much better than spending, 2 weeks and then using it from sunk cost falacy.

Also it teaches you that what you think you need and want is not what you need and want. This is why you are not using it

> having a high signal-to-noise ratio for (open source) projects is a desirable goal?

It’s not obviously true. A higher number of attempts, a larger talent pool, typically doesn’t change the average much (or it might even make the average go down), but tends to produce higher peak outcomes.

We see this everywhere (science, startups, sports, chess, etc).

If you want the best spreadsheet, game, or whatever app you want, you’re only interested in the few highest peaks.

So you do actually get better signal to noise with a larger wasteland of discarded attempts. The higher peaks make it easier to filter out the noise.

The goal you’re intrinsically motivated by seems different than this. That seems to be the whole disagreement.

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