Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

> why are the examples given of futuristic capabilities always so visionless - it's always booking a flight or scheduling a meeting.

This AI wave is filled with "ideas guys/gals" who thought they had an amazing awesome idea and if only they knew how to program they could make a best-selling billion dollar idea, being confronted with the reality that their ideas are really uninteresting as well.

They're still happy to write blog posts about how their bleeding-edge Claw setup sends them a push notification whenever someone comments on one of their LinkedIn posts, though.



I have "new genius" ideas very often. After doing quick search I discover that any idea worth thinking of implementation is either implemented already or what seems to be low barrier to entry clashes with some legal obstacles.


I have the opposite problem. I have a genius idea, and I start to research it.

I find a company that actually built a solid product, dangit this is really good. They appear to have executed well, but they failed, or went nowhere, heck the app is still out there. Maybe they are even chugging along but its a smaller business even with a better product than I would have been able to build. Had I been a founder of the product, I would be questioning staying.

Then I also find sometimes I was doing it all wrong and the world has moved past my notions of products. I think there's a market opportunity because I don't realize that the rest of the world is already cool using a $15 plant hygrometer bluetooth device which can also keep track of your medicine or food in your cooler, my notion of the value of something is skewed by western costs


Interestingly that sort of research is actually what I've used Claude/Chatgpt deep research and openclaw for. If I have an idea, I get an agent to go and do some product research for me and see if there is a market, if anyone has tried it, and if there is anyone doing it.

It has unironically saved me a lot of time I would have otherwise spent going down rabbit holes.

Of the models I've found that claude doesn't gas you up as much as GPT, so for stuff like this where the answer can be "no, that's not a good idea" I usually use claude.


Yup. I do have a 4-step process for this (just for prompts and some bash scripts that call CC). 1. Breadth first 2. Compress 3. Per player deep research 4. Per player compression. Then I just merge all the markdown files, fit it into 250k tokens, load any model that supports that much and you can pretty much "tall to market".

The biggest limitation here is data access though. A lot of market data is gated behind registration or anti-bot captchas, so the project that my CC is working on now is a playwright clone that is not easily detectable + can be used with CLI same as playwright itself.


Sure I do use AI to to do research on my ideas as well


I find ChatGPT so infuriating the way it always agrees with everything you say. The product is optimised for engagement so it wants its users to be delighted


Jim Rohn said one time “just pick a direction and go, you will find out sooner”, if its good or bad.

That was adjusted for 80s. In todays world you can know whether something is worth pursuing in minutes. Tip - in 99.9% of cases its not, but you will still learn along the way. Maybe you find something new.


Hmm I often have ideas that I don't see anywhere else but I'm just in it for rent curiosity and learning. I absolutely hate the business side and usually I do stuff for free just so I don't have to complicate my taxes.

So being an entrepreneur would never work for me.


Story of my life.


the whole obsequious nature of how LLMs also amp them up thinking they're onto something incredible is throwing gas on this dumpster fire.

"What a great idea! This will revolutionize linkedin commenting. Let's implement it together."


Anthropic tried to fix this I think. Because it's the only model that will push back, but it's even funnier.

Ask a question, it will say yes, ask "are you sure?", it will reverse direction full throttle, then ask are you sure again and it'll go back to initial response saying "yeah I confused myself there". You can do this until context window exhaustion and this will never stop.

On the other side of this, Gemini will stand by whatever it generated the first time, no matter how much you push back and no matter how stupid the idea is.


Oh for sure. When I present something to the LLM it always tells me how great it is until I make it "question" it, then it says it was overestimating this or that. Eh. Quite annoying.



You have to remember that LLM's don't have any persistent capacity to hold a "judgement". You ask for something, it provides an attempt at a completion for it. No fact checking, no reasoning, just a plausible looking output, tuned to hopefully get you to repeat the interaction.

Half the reason the dominant UX is a "Chat" is that's the only way to provide a facsimile of memory or persistence across requests. Append the last few turns, press go. Over time you can develop an eye for the model's tics/attractor topics.

Remember that they bill by token use, and suddenly, the entire UX/architecture starts making sense.


Yeah it seems like we're still in the "XYZ ... but on a computer!" stage of AI.


Wait til you see my todo app though…


Can it suggest me to do the things I should do ? Can it talk to me into overcoming what's blocking me from completing tasks at an emotional level ? :)



nope.

It won't even help you understand that the 20 second task you've been putting off for 6 months causing anxiety will only take 20 seconds (nor will we learn from this)


Or the fact that in the time it took me to read this thread I could have finished that task. Sometimes I really want to punch my brain in its stupid face lol.




Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: