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I understand the need for restrictions in industries like defense, space, or healthcare, where compliance is crucial. However, I’m curious because this requirement seems to appear even for more general roles, like front-end positions at SaaS startups. What’s the logic behind applying such a restriction in those cases?


Regulations follow the money and it's infective. So even in what could seem to be unrelated things depending on the funding or the partnerships or the relationships of those companies they may be under the same compliance burdens. The embargo lists are insanely bizarre.


Making the company US-based makes perfect sense, especially given the regulatory landscape. I had a similar experience when one of the top accelerators required us to register the company in the US in order to secure investment. My question is about hiring:)


My partner and I are working on Supabird.io (https://supabird.io), a tool to help people grow on X in a more consistent and structured way. It analyzes viral posts within specific communities so users can learn what works and apply those insights to their own content.

My partner shares our journey on X (@hustle_fred), while I’ve been focused on building the product (yep, the techie here :). We’re excited to have onboarded 43 users in our first month, and we're looking forward to getting feedback from the HN community!


Here's what nobody talks about: the author was RIGHT about the structural problems.

But completely wrong about the solution.

The PhD glut? Real. The postdoc treadmill? Absolutely real. The funding crisis? Still here.

But here's what changed:

The same skills that make you survive a PhD—deep research, systems thinking, hypothesis testing, data analysis—became the EXACT skills the market desperately needs.

2025 reality: - AI companies hiring PhDs at $300K+ base - Biotech startups led by former academics - Data science roles requiring scientific rigor - Deep tech ventures solving real problems

The trap wasn't the PhD. The trap was assuming the ONLY path was tenure-track academia.

The researchers who thrived? They took their training and built different careers: → Industry R&D leadership → Technical founding teams → Quantitative roles in finance → Policy and strategy positions → Scientific consulting

The irony: that essay discouraged a generation from science right before scientific thinking became the most valuable skill set in the economy.

The lesson isn't "don't get a PhD."

It's "don't limit yourself to one narrow definition of what a scientist does."

The best training for solving hard problems is still solving hard problems.

You just get to choose which ones.


I've been on LinkedIn a bunch lately while I'm looking for work. The cadence and "But here's what changed:" are extremely LinkedIn coded. I hope this is just an LLM and people aren't actually starting to talk this way.


Yeah, the only difference between that post and a full linkedIn post is the AI generated illustration.


It's the LinkedIn version of the challenge to tell people they can prove P=NP without te ...

As far as Jane Jacobs (not a professional) is concerned, this is the hardest problem for any tribe of humans: how to survive as a culture?

On values (some say fumes) or on money. Values vs value. Academia back in the days of Athena was a "solution" on the values end of the spectrum. Religion, too, until they figured out they could appeal to the "charity" of the spiritually hungry rich (& later, everyone)

(I appreciate the Benedictine orders for limiting their offer of spiritual goods to some devilish brews )


Most academic topics have near-zero applicability to industry. A classmate just got her PhD on some paleoclimate records of biomarkers in permafrost. It's not a job. If you love the topic and do research in it.. then awesome. Otherwise, hope you enjoyed the ride. You're gunna have to retrain for the next gig.

The training otherwise is a bit of a joke.. you can write some janky Python to shit out crappy plots. You learn to skim papers.. and some bare-minimum stats. It's not worth doing for some nebulous "scientist training"


If you only understood how White Hot and Stone Cold a research field can be! Five years ago crypto was white hot and today it's almost Stone Cold! People get intoxicated with the money beams that get blasted at people in the white hot subfields but realize that only 5-10% of phds are majoring in the white hot subfields and they simply got lucky 5 years ago to pick that subfield and all that attention hopefully lasts for 10 years which is enough time for them to get tenure or succeed with a startup! if the field isn't white hot for 10 consecutive years they will get fired at tenure time!


The problem with your take is that you neglect the nuanced difference between demand and need.

Demand is where people are willing to pay you at the right price, and you aren't struggling to find work. Need is where they aren't, and you are struggling, and people only get jobs when there is suitable demand.

Jobs where there is great need but distortions that cause zero or extremely low demand, you don't get people. These jobs have great need, but there is no economic benefit that justifies the people development cost for that crop. These resources are wasted resources after demand is met.

A lot of this is basic economics, and the tragedy is that just like in science, structure dictates function. Distortions beget more distortions, and when they are not based in the core principles that determine wealth of a nation, then they may become chaotic at which point structure fails.

The lesson the OP author is trying to make is, make sure the juice is worth the squeeze, and be extremely discerning because there are a lot of people that will lie for imaginary personal benefits. Enough that he says don't do it, and that's coming from an insider who has known and seen how it goes bad in detail, but was still successful.


I did my PhD while working, so it's not even that either or. And just to add to your point, it is really so rare to get that kind of mentoring, feedback than in a PhD program. It might depend on the program, but you finally have access to the brightest minds in your field and get to socialize with them.


Is this LLM written?


This is absolutely true. And the mistake I see from PhDs who want to switch into industry, is looking for work around the exact subject they did their research on. Rather they need to identify a useful industry area and demonstrate how their research skills give them an edge in that new area

It’s not hard to do but you have to let go.


Quantity matters, how many scientifics work for an AI company versus how many are unemployed?


Building SupaBird.io - reverse-engineering viral X content so you don't have to guess what works.

Here's the catch: most creators study top accounts but can't replicate their success. They miss the patterns.

Analyzed 1M+ tweets from top performers and built AI that doesn't just copy - it adapts their winning frameworks to your voice and niche.

One user went from inconsistent posting to systematic growth. The content quality jumped. The engagement followed.

Not promising follower counts. Promising you'll finally understand what actually converts on this platform.


The tip about replying quickly to early comments is key—having conversations early on seems like the best way to get your post seen imo.


yes, seems like engagement is one of the highest priorities for the algorithm.


Wow! Such a detailed response. That makes everything much clear. Thanks for sharing and the references!


Thank you all for the insightful comments. I appreciate how this community shares its thoughts with such care and knowledge. I agree that while GPTs handle simpler tasks effectively, complex questions have never been Stack Overflow's strong suit.

A project I’ve been working on started as a web annotation tool and has evolved into a visual task manager called JustBeepIt (https://justbeepit.com). Considering many of our users are developers, we observed that Stack Overflow wasn’t among the sites where users create tasks. This led me to question why it seems to be losing its prominence.


https://www.justbeepit.com/ started as a web annotation tool that I hacked together with a friend. Now, it’s a full-fledged visual task management platform with over 2,000 users.

In 2022, I wondered what it would be like if my manager could leave comments directly on the live website for all the edits, rather than sending a bunch of screenshots and videos. That’s how I came up with the idea for a "simple" browser extension that lets you leave comments on any site, anywhere on the screen.

There were several challenges along the way:

Attaching Comments to the Correct HTML Element: I initially struggled with ensuring comments were attached to the right element, as relying on X/Y coordinates would not be responsive. Now, I use a combination of element IDs, classes, outer HTML, and attributes. This approach works correctly 95% of the time. Do you know of any other methods to find the correct element in the DOM?

No Third-Party Libraries: Extension development only allows pure HTML, CSS, and JS, with no external scripts from CDNs. Building a text editor from scratch was one of the most challenging parts.

Real-Time Functionality: Keeping the extension's background page active was tough because it deactivates when not in use, making it almost impossible to maintain a socket connection. I wrote code to wake up the background page and reconnect the socket whenever it goes to sleep.

I stopped all my freelance projects, and now three other people and I work on this tool full-time. We recently became #1 on Product Hunt: JustBeepIt.com

There are still many issues we're working on, such as using it with iFrames or inside scrollable objects, but we're tackling these challenges one by one.



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