That was my immediate impression too! It feels like it's all AI maximalists who seem to have a need to filter their every interaction through an LLM. And the result looks and reads just like Moltbook.
Yeah and the employee who generated an AI response to the AI-generated bug report, is Jared Sumner who is the founder of Bun which was acquired by Anthropic. Pretty sad state of affairs all around.
It feels (nobody can prove it) that all user-facing applications are fully vibe-coded and no internal developers have any idea how they work, so they just keep redirecting user questions to Claude to answer on behalf of them. That's why they are dealing with regressions and downtimes every few releases as it's the usual pattern with vibe coding that bug keep resurfacing.
If all LLM advancements stopped today, but compute + energy got to the price where the $30 million zettaflop was possible, I wonder what outcomes would be possible? Would 1000 claudes be able to coordinate in meaningful ways? How much human intervention would be needed?
Headline/article is extremely misleading. They still have subscription plans with included usage, but those usage limits are now based on tokens instead of messages.
I like this, and think it's true for how humans learn. What's interesting to me is that it seems LLMs are significantly smarter than they were two years ago, but it doesn't feel like they have better "taste". Their failure modes are still bizarre and inhuman. I wonder what it is about their architecture/training that scales their experience without corresponding improvements in taste.
In theory, RLVR should encourage less error-prone code, similar to a human getting burned by production outages like the article mentioned. Maybe the scale in training just isn't big enough for that to matter? Perhaps we need better benchmarks that capture long-term issues that arise from bad models and unnecessary complexity.
I’ve tried having one “big” task that I’m focusing on with active back and forth while letting other Claude instances handle easier back-burner type tasks that it can effectively one-shot. But I’ve noticed that often turns into me spending more time/focus than I’d want on tasks that aren’t actually that impactful. I still think I get more done than I would otherwise, but I still haven’t found the best management strategy.
Yeah that confused me, but the compression paper also doesn’t make a ton of sense since I doubt Google would have released it if it was actually such a competitive advantage compared to what other labs are doing. So I wonder what’s actually causing the price decrease.
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