clapthewind

> almost entire set of humans that it made the deal with walks away from the deal

You missed mentioning a million new humans will gladly walk into the deal.

This is a list of 1600 people who should be alrady looking out because meta won't be after this signature.

Build trust, collect data from cdrowdsource, if you want to succeed on this.

Build trust by: truly making this a public good, by open sourcing it. Be the maitnainer. Data dump every week as a zipball/tarball. These will ensure you can't rugpull.

With this trust, offer an extension (open source of course) to all, which whever a user goes through crunchbase, traxn, etc, sends any factual data (hence non-copyrightable) to you. If you gained trust, I would also do this.

You get the right to be a maintainer, and figure out if you also want to make a business with it on top.

In India, by law, companies above a certain size are required to spend 2% of profit on social responsibility activities. So in my city, you see lots of things around adopted or funded by companies.

Why is that (framed as) a bad thing? We don't go around life understanding everything that we do because it would be exhausting.

Sometimes all you want to do is use something and it works.

Just because it didn't meet your preferred outcome does not mean it was rubberstamped. The truth is that it is transformative.

I didn't try it. Given jslinux exists, and works, i suspect WASM based linux will be faster and more streamlined.

So we can run this on a browser? a demo on the github page would be great. combine it with an extension to support networking, and you have a winner.

I suspect you're a junior engineer if you think that way. Domains (any) are deep, and require thorough understanding before you can have business or revenue impact.

Is it smart to pick a path that's probably not going to be appreciated anymore? One that's probably going to lead to unemployment?

> It's perfectly possible for an engineer to be both a fantastic engineer, and bad at using AI

In this era, AI native skills are the major factor, alongside system design, which define who's fantastic. As an example, deep programming language or framework knowledge is a commodity now and not meaningful as a skill difference.

I think Hollywood is in for a rough era. The disruption is happening at break neck speeds.

It sounds like you're championing labor using ai. But capital will also use it and leverage it more.

There's no mechanism for only labor to exploit a technology, apart from common ownership at a world level. Achieving this is left as an exercise to the ambitious.

Putting it politely, I think you may have xenophobic tendency. And for all your buster, I suggest you work on having a more sane world view.

Some people are playing the global optimization game; a world where anyone can have any (production grade) software they want.

AI "disciplining" is arguably much simpler, easier and cheaper.

Low pay, to be fair.

BTW the skill to develop to direct your career towards this: build deep understanding of one part of a domain, develop thinking in abstractions and systems, follow TDD in all agentic dev (converts probabilistic to deterministic).

I'm seeing this in some teams I am aware of. It is usually a 3-4 people team working very closely. They're not using gas-town or such, but are typically creating abstraction after abstraction for reviews and assimilating changes (usually with a claude 20x account). They are human in the loop until the system stabilizes and needs no further AI.

It was like science fiction becoming aware of this pattern, but as the OP says, this is indeed happening. Going to change the shape of tech careers for sure. my 2c.

Do not get hung up? Sounds like English ESL rewrote some insights for language. Content > Form.

DSA itself may now not be as indicative, but grinding is absolutely a key trait in good hires. That type of person will put in very effort at work.

No magic pill: you can't work backwards. Pivot away from current idea if it's not getting word of mouth or any other traction, and for the next idea start with finding problems for people in your network that they will pay for.

You've to go into founder mode - solve problems that exist for customers you've already discovered, rather than build something and expect magical "marketing" to find customers. The latter was previously a weak strategy, and is completely gone with the AI era. No alternative to working very closely with customers.