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Hang on. You've published hundreds of apps? As in the same thing slightly modified several times?

Indeed their product is an app that is little more than a webview that only shows one website, with optional value-add features. They handle publishing for the client, hence the hundreds.

https://webtoapp.design/


I feel like this take is for a more passive form of stoicism. No you don't have to care about what is going on around you, but you do need to somewhat engage with your life to solve problems, pay bills and take care of loved ones.


(Disclosure: I'm getting a PhD in CS now)

> The hard part of startups is product: knowing what to build, and being able to build it

Funny enough, this is why I think a PhD is undervalued by many. You spend years focused on a single area, sometimes pivoting topics, and getting hands on experience with operating solo on the outskirts of a particular field.

The overall point of the degree is you learn how to learn. The nice part is you have the padded walls of university equipment, funding, and time; So failure isn't terminal, just an opportunity to figure out what didn't work.

There's a few reasons how and why this message got distorted and lost in modern academia (honestly it would be a great subject for a book). It's no mistake that better known programs and programs with ties to a stream of successful startups are also the ones where there's a culture of builders and makers.


In hindsight it was quite early in my career, but a bit over 20 years ago I felt burnt out in tech and wanted to try something new. I was share trading quite a bit so thought maybe I'd become a stock broker (online trading was only just starting to become a thing, so being a broker was still a real job at the time!). I finished the degree and got qualified, and while I loved the learning I discovered I hated the industry and that it wasn't for me.

But all of that discovery work, the financial planning, what their actual objectives were, having to dig into why someone wanted to buy a house, etc. proved to be some of the most invaluable and transferable skills I've learned (that, and SQL ;). A lot of that part of the course was learning how to ask questions, and learning how to follow-up to get past the superficial and often incorrect initial answers.

To your point I feel like there's these kind of meta skills that are transferable to many domains, but are sadly lacking these days from a lot of education that is hyper-focused on very role-specific qualifications. The ones that immediately come to mind:

- Learning how to learn (i.e., how to understand yourself, and improve)

- How to ask good questions (similar to above, but about others)

- And something I need a better label for because I just clumsily call it "sales", but in the Daniel Pink "To Sell is Human" style. Something like being able to structure a coherent and compelling narrative to other people. Clearly I fall short on this one.


To sell is human; to scam, divine.


would've been a great tagline for Better Call Saul


I wouldn't sell yourself short on the last one... the comment itself is a decent example of it :)


Maybe the failure mode isn't the PhD itself, but environments where publishing becomes the objective rather than a byproduct of getting unusually good at understanding and building things


> (...) a byproduct of getting unusually good at understanding and building things

A PhD is not about getting good at understanding something, let alone "unusually good". It's about being able to explore an uncharted area with little to no help, and write down your learnings so that those that come after you can build upon your work.


In an ideal world, sure. In reality, a PhD[1] is about publishing papers in the hope that you learn something along the way.

[1] My experience in ML in 2026.


> In an ideal world, sure. In reality, a PhD[1] is about publishing papers in the hope that you learn something along the way.

You're being needlessly dismissive of what "publishing papers" mean. Writing down what you learn is what papers are for, and the only papers that count for a PhD are those which are accepted by reference journals, which impose a relatively high bar on what content they accept.

So you still need to explore uncharted areas, and your main output is still writing down what you found for others to build upon. Those are the deliverables. For the person doing the PhD, the primary benefit is developing research skills, such as independente and self-reliance.


> which impose a relatively high bar on what content they accept.

Nope. In fact they accept utter garbage most of the time. I can't count the numbers of times I've caught pure errors (literal logic errors, code errors, mathematical errors) even in highly respected journals. Journals have a high bar of entry because they've gated their communities, only allowing insiders to publish (ie tenured professors, people associated/employed with university labs or their colleagues). If you don't have an industry connection the odds of you self publishing in these journals is zero. And if you _do_ find a connection, say a professor whose willing to help you out, they'll demand to place their name on your paper (without actually contributing anything). This is how you get papers with 50 authors, because every politicker wanted a piece of the pie.

This is also why you see frontier AI labs self-publishing on their websites rather than in journals.


> This is also why you see frontier AI labs self-publishing on their websites rather than in journals.

What they self-publish on their own websites should be regarded as marketing.


> Nope. In fact they accept utter garbage most of the time.

Unless you enrolled in a fraudulent, make-believe University of Phoenix style program, no. Any real PhD program only counts publications in a closed allowlist of reputable journals. Those journals are peer reviewed and enforce quality and relevance standards.

> I can't count the numbers of times I've caught pure errors (literal logic errors, code errors, mathematical errors) even in highly respected journals.

That's fine and all, specially if what you actually want to do is take a shot at humble bragging, but back in the subject papers are supposed to be snapshots of your understanding of a topic that can be used by others to inspire or advance their exploration. This means they are not infallible or free from criticism. In fact, it is rather ok brand to publish papers improving upon prior publications by correcting errors, improving methodologies, and even presenting contradictory evidence. That is what it means to be at the bleeding edge.


The commenter is stating that respectable journals accept a lot of bad papers. This is actually very true.


Which is ironic, because self-publishing then should automatically qualify you for a PhD. In fact, I believe more people should take this approach. As far as I'm aware, there's no law or regulation from declaring yourself a "PhD" backed by autoresearch.


I've got a PhD in Physics and I have to say that the quality of most "self published" physics is very low, which probably explains why people would not accept a self-declared PhD.


> Which is ironic, because self-publishing then should automatically qualify you for a PhD.

No. What qualifies you as a researcher is being able to output work that is accepted by your peers. Hence the peer review process is critical. You fail to meet this bar if you publish something in blogspot or even arxiv for that matter.


A key problem is upper-level academia is rife with the same sorts of human-scale power dynamics. Petty squabbles, ideological (and ideological-flavoured) views can and do hold entire fields from time to time. It is only a particular type of tenacity that breaks up the status quo from time to time. (consider the Marvin Minsky era of AI research. A big personality can stifle an entire field). Peers aren't usually the appropriate measuring stick of merit.


> A key problem is upper-level academia is rife with the same sorts of human-scale power dynamics.

You are trying too hard to come up with excuses. The paper review process is double-blind, and nothing prevents you from publishing the same work in multiple journals. If your goal is to do meaningful contributions to science then "power dynamics" are irrelevant.

You do need to develop a meaningful network in the field if your goal is to collaborate with other researchers, but that's basically what everyone needs to do in any professional field.


Entrenched ideas have momentum. Your lone-warrior attitude is admirable if not lacking in substance. Most fields have had occasional hangups on dead ends, such as the aforementioned Minsky "symbolic > connectivist" debacle. Behaviourism in psychology. String theory. The list goes on.


Eh, in theoretical fields we now have good formal verification tools so that someone publishing a code repo on their personal website is more meaningful in pretty much every way than a peer reviewed journal article. The article becomes an archaic formality.

Like I get that the current social norms around "research" might not be there yet, but if they refuse to adapt, I just see that as a reason to defund "research" and start from scratch.


You can't generalize from your personal experience to the rest of academia. There is far too much variation between fields, institutions, and countries as well as over time. ML in particular is an extreme outlier due to amount of money and business interests involved. Your experience would already have been quite different in a less fashionable subfield of CS.


Your role is to publish papers so your PI is able to get grants, and to network, so the lab profile gets better known in the research community, and then as a more senior grad student you can help write grant applications, and you can build a track record of mentoring (e.g. master students). At the end of the day, you want to demonstrate that you can come up with projects and pursue the research up until publication in a top-tier venue, and the ultimate goal (from the point of view of hiring committees) is obtaining prestige and funding for the university.

If you plan to go to industry, your incentives are somewhat misaligned with your PI. In that case you want to pursue multiple internships and getting networked with top companies in your field, and demonstrating practical output, well-released code, demonstrated downstream value for followup projects etc.


Yes, take away all the pretense and a Ph.D. is just an apprenticeship to be a researcher.


There's no pretense. That's always been the whole point.


That's not my experience -- there's a whole pretense about being experts in a field, which is exactly what the poster above bought into. Having a PhD doesn't make or prove you're an expert about anything. It just proves you know how to do research in a thing, but that doesn't stop us from presenting PhDs in front of juries as if they're the only ones who know what they're talking about.


I don't see how these are incompatible. The PhD prepares you to be an independent researcher. The way you prove this is by studying the same topics for a few years, and by the time you reach your viva, you'd be expected to know a lot about the topic you chose.


It's not incompatible, many people in order to do research have to gain a great expertise in a thing. Others can get a Ph.D. having really no expertise at all, but just the ability to get through a research program. Others still can be experts and unable to navigate a research program due to how capricious and political they are. So the pretense is that the Ph.D. is a marker of expertise. It's correlated with expertise, but the actual thing it signals is you've gotten through a research program.


Self made experts with no PhD or formal degrees are testifying in front of juries. They dont even need any science to back them.


I once asked asked my professor for advice. I said, I am drawn to both doing a startup and doing a PhD. How do I do both? He advised me to choose one. “Either one will take the whole of your youth and all its energy”, he said.


> Funny enough, this is why I think a PhD is undervalued by many

no, the opportunity cost is too great for this field, for people that saw the light in just undergrad or wound up building software for other people without an undergrad CS degree


the moment you start talking about opportunity cost, I think you've already ducked the intent of the majority of startup-strategizers-for-exponential-gains-only, for which the carrot on the stick is "unbounded" gain


can you repeat that in a different way? opportunity cost is prioritizing gains - or at least a window of opportunity for outsized gains - I don't see how "ducked the intent" fits in

but yes I realize that any conversation with academics is going to be skewed from the market, I think its worth representing nonetheless since academics often interpret their privilege of choice as a nobler cause because they made that choice at all


This got a laugh out of me! Thanks for sharing!


-My spreadsheet is in Google Sheets

-The hosting is in AWS

-The server itself uses the FastMCP library, in python


> Quell doesn’t store your messages — they’re processed and discarded in real time.

Are you using a 3rd party system to generate the numbers and forward them to your number? How can you audit that they 3rd party that creates the Quell numbers isn't saving the messages before they move to your server?


We can't control what the telcos do with text messages, but we exclusively use SOC 2 Type II compliant providers.


> Ivan was born at a very young age, this has made a lot of people very angry and is widely regarded as a bad move.

Lol


I think it originates from The Restarurant at the end of the Universe: https://www.brainyquote.com/quotes/douglas_adams_125092


> 50% of buyers don't even finish the first video.

Just wondering - Is that a guess or a backed up statistic? Would be eye opening if that really was the case


I stand corrected! It's 52% that don't even START the first video![0] Other studies report that number at 35%.[1]

One thing that's more consistent are average completion rates hovering around 5%.

[0] https://www.science.org/doi/10.1126/science.aav7958 as cited by [1]

[1] https://openpraxis.org/articles/606/files/66d16716e6c09.pdf


I think the number is probably a bit skewed by the fact a lot of companies offer unlimited access to udemy and such, so people "start" courses without any commitment or cost, and then predictably drop off fast or don't start at all.

Personally I just found none of them really worth doing. They felt almost not genuine in a way, like they cared more about profiting from courses and gaming the system than actually teaching you something. I switched to learning via Youtube videos and found it much more educational than the paid courses.


I never got past the second or third lecture in a "Learning How to Learn" class, which I suppose at least meant I had identified the correct problem.


I've had a project idea in the back of my mind for a long time: take all of my locations that I've saved in Swarm (https://swarmapp.com) and 3D render all of the buildings that I've been to. The issue was a lack of models of the actual buildings - which is here! Maybe it is possible...


What was the Texas patent case?


Had to look it up (the texas comment is just a jab at texas being an amenable place to file IP infringement cases which is something i remember back then reading):

https://www.reuters.com/legal/google-owes-3387-mln-chromecas...


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