nathanfig

I have been using Sites a few months now, really underrated feature IMO. Any time I get a quick app idea I just hand it off to Sites and usually get a working prototype within the hour.

For example, here's a game where you are a mouse hunting for cheese in higher dimensional mazes: https://manifold-six-axis-escape.nathan338932.chatgpt.site/

Idea came to me while at a concert, was ready to play that same night.

I hope open weights continue to gain traction for this reason too.

But injecting information into outputs is a little different than Claude keeping tabs internally. The point is that we do not know what information is being shipped with the fingerprint itself.

Yeah it's entirely possible the answer is: "You don't." But I haven't even seen people attempting to imagine life well-lived. Like with so much technology it's basically an afterthought.

I've been pondering the question: "What does it mean to live well with AI?"

We are certainly scrambling for productivity with "token maxxing" and scrambling for entertainment with AI companions, but I haven't seen many thoughtful takes on how AI might look in a life well-lived.

I think that's a big part of what makes this era so much fun - the interactivity tailored to my capability. I feel like I'm 13 again discovering I can write HTML and feeling that giddy delight when I try something and it just works.

>> I haven’t had great luck with winding it up and setting it loose on a task

Yeah there is real labor involved with trying to set up the right context and explain your goals and ensure it has the right tools, etc. etc. Sometimes the payoff is massive, other times it's like "I could have done this myself faster". It takes time to build an intuition for which is which, and I'm constantly having to tune that heuristic as new models and tools come out.

Yeah, the social problem of "how do we use technology well" persists.

Can you elaborate? I might agree, I'm just curious what you mean.

Yeah in fact I think we are going through some major upheaval in development practices because we haven't yet figured out what constraints to put in our use of AI, and so plastering it everywhere we trip ourselves up. It took a while to figure out that private members were useful and GOTO is harmful despite how tempting it might be.

I think similarly we will find that using AI to take shortcuts around design is mostly harmful, but using it to fulfill interfaces is brilliant. Eventually a set of best practices will evolve.

Because they are already useful for programming and unlikely to get worse!

Sounds a lot like "nothing ever happens"?

Reduced costs does not necessarily equal reduced wages, but I see what you're saying. As others have pointed out, making cameras more accessible made photography more competitive.

It may be in the end that software developers make less money even as more jobs become available.

And worrying. LLMs don't fed themselves, we need people to continue sharing solutions. I've contributed some popular answers on SO myself and am happy that an LLM can use that in its training, but rarely go to SO myself anymore.

I'm finding 2.4% unemployment rate for software developers: https://money.usnews.com/careers/best-jobs/software-develope...

Regardless of the true number, you're right that no amount of reasoning on paper "why" we should be employed matters if the reality is different; which it clearly is for a lot of people. Reality decides in the end.

A more accurate title might have been "Why AI is a reason to become a software developer" - since the topic I discuss is entirely AI and its effects on the field, and there might be entirely non-AI reasons for not going into software.

Yeah, with current-state AI I foresee more such opportunities.

Yes, if you built your career on FrontPage you have probably had a bad time. Many such cases.

That said, even if the specific products like Cursor or ChatGPT are not here in 5 years, I am confident we are not going to collectively dismiss the utility of LLMs.

Really! That could make for some really interesting stories. Fascinating to think of LLMs as a customer acquisition pipeline for developers.

Claude made this point while reviewing my blog for me: the mechanization of farms created a whole lot more specialization of roles. The person editing CAD diagrams of next year's combine harvester may not be a farmer strictly speaking, but farming is still where their livelihood comes from.

Yeah I think the combine-harvester analogy is tempting because it's so easy to visualize how wheat can scale over a big square field and project that visual onto lines of code generated on a big square screen... forgetting that lines-of-code-generated is not inherently useful.

An interesting parallel because there were undoubtedly some people who worried we would lose something important in the craft of instruction-level programming, and almost certainly we have in relative terms. But in absolute numbers I am confident we have more low-level programmers than we did before Fortran.

And if I were to jump into instruction-level programming today I would start by asking an LLM where to begin...

I also remember this! Maybe a subconscious influence

Thanks!

Oh I should have known - yeah I was just being facetious

Hi all - I write a lot for myself but typically don't share, hence the stream-of-consciousness style.

But I thought this might be worth blogifying just for the sake of adding some counter-narrative to the doomerism I see a lot regarding the value of software developers. Feel free to tear it apart :)

At WHOI we frequently run into some of these issues. Ocean-going projects often have long periods of disconnect, or have just a tiny bandwidth-capped connections that are meant for sending home critical data and not for automated software updates...

So much software also just takes for granted that it should be allowed on the Internet.

Multi input? Infilling? First generative audio model I've seen that starts to close the gap with image models.

Not quite; turn any GUI application into a Python command line program.

I would love something that could do the reverse.

Scaling context is not something humans have good intuition for- I certainly don't recall an exact sentence from 200 pages ago. This is an area where we actually want the models to not mimic us.

Definitely edited, pretty clear in some of the transitions. Makes me wonder how many takes were needed.