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.
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
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.
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)
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.