jackyli02

The landing page feels quite Claude design-y. Is that what you used? If so it's one of the better Claude design landing pages I've seen. Nice work!

The framing of tests-as-source-code resonates, but I think it extends further than testing specifically. From my experience building with AI coding tools, I spend increasingly more time reviewing and validating code than writing it. You end up acting like an engineering manager running a team of junior devs: scoping tasks tightly, reviewing output critically, deciding whether what came back meets the requirement. Tests are one expression of that, but so is code review - they're both forms of validation. The broader shift is that the developer's primary output is becoming judgment about correctness rather than the code itself.

Essentially the same thing Elon has been saying for years. Physical AI plays to a real Chinese advantage: manufacturing density. China doesn't just have cheap labor, it has the iteration speed that comes from having chip fabs, robotics assemblers, and end-user factories within the same industrial corridor. Compared to foundation models, the gap in embodied AI narrows fast when the bottleneck shifts from compute to real-world manufacturing.

https://lynnandtonic.com/ is really well-built and has a distinctive style. Recommend checking it out!

This is explicitly framing hand-written code as the wrong workflow. That's a significant shift from even six months ago. My sense is this will become more common at companies building on top of APIs and integrations (Zapier's core domain), where the code is more glue than architecture. Whether it scales to systems-level work is a different question. The failure modes of agent-written code are still poorly understood, and "built mitigations" is doing a lot of heavy lifting in that job listing.

It's impossible for private companies to decide what state actors (especially the US military) want to do with AI.

OAI made a business decision to cooperate with the DoW. And they had to make the "we can't control how customers use it" excuse due to pressure from its employees, peer competitors and the general public.

The "optimization" framing is where self-help tends to go wrong. Tyler Cowen has made a similar point that reading self-help books is often a form of procrastination disguised as productivity, because you're consuming meta-strategies rather than doing the actual work in whatever domain you care about.

PMs in Meta-scale companies vs. startups has always been different, and they are diverging even more as AI gets better.

In startups anything goes. PMs and engs do whatever it takes to ship and scale the business. No one cares who's using AI in what way, as long as they're getting shit done.

In a place like Meta or Amazon, people also get more shit done with AI, but because these teams are huge, well-oiled machines, sudden productivity bumps or norm changes can drop overall productivity.

Totally agree with this post as long as it's limited to large, mature teams

Totally agree that students should learn to actually write code.

To use a tool well, you have to understand how the tool works rather than outsourcing everything.

Good athletes know how their muscles work, good racers know about the springs and tires, and same goes for coders.

on track for another 10x this year

To avoid "AI barging into human conversations unsolicited", you can either stop the AI from barging in, or remove the premise that this is a "human conversation". The latter might be easier.

The role "reporter" deserves very little credence in AI now. The public might be better off if they get their information on AI from ChatGPT.

Wait till the tiktok influencers hear about this and jump on the bandwagon. Anthropic will keep winning

Great timing, especially since Anthropic has been shipping huge improvements in their iOS app. Now they've replaced their Stone Age audio input and added live mode, the iOS experience is a lot closer to ChatGPT's (though still lacking a bit)

And last week's selloff isn't even about Saas, yet ppl just love to tell themselves that AI is going to nuke everything and we are all fucked

Yep, "everyone wants an AI that fundamentally agrees with them" is probably the strongest argument for a multi-AI world.

Overall probably still SV. But depending on the circumstances China, Singapore, Dubai are all good. The physical location matters so little from a business perspective now though. So I think it's actually more of a lifestyle choice vs a business one.

This shows how many "rights" people in the developed west enjoy are in fact privileges.

SA is a real weasel lol. Acted like he stood behind Anthropic's principles just to announce the deal with DoW a few hours later.

"Stood its ground" to some. Don't forget there are still lots (even in SV) who can't stop glazing companies like Palantir and Anduril.

People can still brush this off by saying Anthropic is doing this to create more buzz for its next round. But they are taking unpopular stances and could be burning bridges. Simply take a look at PLTR and it's obviously more lucrative to lean the other way.

Reasons this piece is unimpressive:

1. It never really seemed to explain WHY poor countries stopped doing better. It just framed it as "sike, they never were getting better!". But the WHY is still missing.

2. The penultimate paragraph present a thesis that China's commodity boom is the main driver behind the "great convergence". This claim is baseless. Just because the commodity boom in China coincide with the great convergence does make one the "product" (verbatim quote) of the other. In fact these two events are structurally connected and there is no simple one-way causation relationship. Other factors like financial deregularization played a vital role in the great convergence but was completely ignored.

3. Some of the evidences (eg. "Dutch disease") are over-generalizations and ignore the differences between nations.

Hi HN!

Conversations with Tyler episodes have a high density of book mentions - guests and Tyler constantly reference what they're reading. I kept pausing episodes to jot down the book mentions, so I figured I'd just extract them all.

Book lists scraped from HN/podcasts aren't new. The difference is that now with LLMs, we no longer need custom ML pipelines (like in https://news.ycombinator.com/item?id=28595967).

Thanks to Claude, each book also gets a quote (from the mentions in the podcast), tags, and a polished description. The quotes ended up being my favorite feature - they convey rich information and capture the characteristics of a book much better than a simple star rating would.

Hope you all enjoy this and please lmk your suggestions & feedbacks!

Love the design! Small nit: the play button for the landing page video seems a bit off (the triangle alignment is off)