- If you are bootstrapped, you can build dual use technology.
- All of this is predicated on the idea that building software is hard, you need 8 years to build a product that people like. Maybe this is all going away in the AI world in a couple of years.
We have been working on https://talentpulsar.ai for exactly this. Hope to find some good collaborations with the hn community with some little self promotion, hope this is okay.
We had considered Oban when deciding whether to go with Kafka/Debezium or not. We sided with Kafka because it can do high throughput ingestion and it is easier to maintain it with cursor in today's world. Postgres is not meant for heavy writes, but heavy querying. You could fix that with lot of care but then it does not scale multi-master very well either. Kafka scales much better for heavy writes.
This is not an easy inference. For this inference to be true , you have to know how much of the expense goes to salaries . Also, you have to give credit to tsmc to be world class which enables them to control prices, it may not translate across industries
Just so others don’t have to do it. I did not think this post was hn worthy so wanted to save some time for others. Maybe hn needs to do it automatically
Conclusion
The data points cited in the article are mostly accurate, based on available government reports (e.g., USCIS, ICE, NACE). However, the interpretations and causal claims are ideologically framed and often lack nuance:
Sound in identifying employment and wage challenges for new CS graduates.
Oversimplified in attributing these challenges mainly or solely to foreign workers.
Questionable in presenting policy recommendations as the only “truth-based” solution.
If you're looking for a deeper, balanced understanding, consider consulting:
National Science Board’s Science & Engineering Indicators
Brookings Institution or Cato Institute reports (for contrasting views)
NACE and NCES for graduate outcomes and education data
Maybe it is not, you need much more context about the OP to declare this as a straw argument. Confidentiality agreements are generally very boilerplate. If someone is thinking that this is preventing them from working at something, they are possibly just not understanding what stealing means. This guy possibly had similar understanding of laws: https://www.justice.gov/usao-ndca/pr/former-uber-executive-s...
why downvote this? I have gone through this route and can vouch this is for a good cause, this conversation may mislead people into believing stealing is okay.
Brand takes money to build. IF an employee took the secret to their rich uncle when coke was small, we would not be talking about Coke. Whatever small the formula was.
IF you go to an interview, and nothing was divulged to you, this NDA does not mean anything. But if youwork at a competitor, and you get an interviewer tell you things that the company does not want to divulge, company has some protection. Not all laws and processes are bad.
- If you are bootstrapped, you can build dual use technology. - All of this is predicated on the idea that building software is hard, you need 8 years to build a product that people like. Maybe this is all going away in the AI world in a couple of years.