speakingmoistly

> The ability to cleanroom reverse engineer and reimplement any software with little effort.

LLMs hardly to clean room anything when their training corpus is most likely "all the code you can get online regardless of license".

> Software value in free fall.

I'd challenge that. A lot of what's being produced is slop, that's the low value part. Good software still has plenty of value because it requires a lot of effort to create.

An interesting (read: icky) choice of platform for government outreach given who it's associated with, what it generally stands for and how much of a closed garden it is.

"I was reckless with AI and created a situation that mishandled financial data" isn't the flex this guy think it is.

"The things they'll be able to do for us are going to be awesome. People will want them, and they are really useful."

Feels like someone has AI stock they need to see go up.

> Do employees vastly outnumber founders on Hacker News?

That's just globally true. For all I know, bots may outnumber both of those groups as well.

> And if so, could that explain some of the negativity towards speculative and crazy ideas?

Do you have specific examples in mind? I can't conjure links and am just operating from memory, but I recall reading about lot of ideas that are less speculative/crazy and more nonsense that feels out of touch with what actual humans would want or need.

> Apple urgently needs a way to disable Apple Intelligence

That's only true if consumers are willing to give up the ecosystem and move elsewhere if they don't. The same way that users have (somewhat) accepted Windows's own sins as the cost of doing business, I'd expect the same here.

Assuming you've shifted containers you ran locally over to this, what do the economics of it look like?

I always find the idea that a solo founder + AI being a whole company would be a good thing to be a bit wonky. I'm sure it's very popular in circles that see employees as cost-centers and that would rather not have to deal with taking care of staff (as in, treat them like people), but I just can't see this happening in a serious way.

I 100% believe that it's a formula that may work up to a certain scale as long as the whole operation toes the happy path line, but I wonder what happens when shit hits the fan in any meaningful way. Businesses adopting products is largely about trust, and having a vendor whose bus factor is essentially infinite feels risky unless it's a mundane service that doesn't process any data, that you don't mind being unreliable and that you are comfortable with it becoming unpredictable.

Not only that, but outsourcing so much to LLM providers feels like a recipe for degraded service (of which there is a lot, Anthropic's status page lists about an event every day or two and save for Claude Government, Anthropic is barely hanging on to two nines uptime) to take out the entire business.

Now, as to the two examples that the WSJ cites. Ben Broca's thing is Polsia, which resells agent services so that other entrepreneurs can do their AI-powered solo thing. It came up in news a while back because of how it exposes what the platform is doing to the public in real-time. Every time I look at it, it feels fishy -- right now, it lists ~3000 companies launched today, which may be true but doesn't quite sound right. I'm skeptical of how viable it is as a business, but I'm welcoming being proven wrong there. Until then, it has a strong "buy my sales webinar" vibe.

Troy Johnston's product is also in the same vein, selling consultant services to help entrepreneurs to leverage AI. Again, having an AI-powered business selling the AI-powered business dream isn't exactly that far from the webinar energy of the last one.

I couldn't find much about Samir Ahmad's venture, but seeing how it folded within a few months, it doesn't look like it really took off the ground.

Finally, Claire Vo's product looks like it might be ChatPRD, which looks largely like a wrapper around frontier models writing product documentation - this is what I would expect the whole one-person-startup to be like. Worth noting that they have since hired staff.

In the end, it seems like it's less "AI runs my million-dollar solo venture" and more "AI helps supporting the idea in the early days, but can only go so far and then you hire staff". That last bit is less flashy than WSJ's title work though.

The CD joke aside, there's something weird abouta large, recognizable entity using such a nondescript MS form and collecting names and addresses, only to send something to a very small segment of them. Feels like a data harvesting operation.

At the very least, I would imagine you'd read and think about the error, parse through and clean it up for unneeded bits if the whole thing isn't relevant and write around it to provide context on what happened / possible things to correlate with it in case you have hypotheses to work out.

I'm also not confident this is something that will stick (and survive the acquisition), which further weakens the idea that companies would set up expensive migration projects to it.

Is the goal to build something and learn something from the experience, or try and build something with adoption in mind?

If the former, the answer to your question is always "yes": if there's something to learn and you're interested in that problem space, it's always worthwhile.

If you're looking at the latter, you're essentially building a product. The next question should then be "is there part of what's out there that you're confident you can do differently/better?"

Not too long ago, a recruiter reached out for a confidential client that turned out to be ClickUp with a posting that felt off (600-900k + stock and bonus compensation), I was left wondering what kind of insanity is rolled into the job for this amount. Now I know.

> Maybe this unlimited character count tweets change was a mistake.

The real mistake was CEOs feeling like they need to be visible on social media and opine on things in the public sphere.