
Uhh. Wasn't it Anthropic that pushed for third party "independent" auditors across the whole industry?
Replying to @METR_Evals
We submitted a ~100-page full report on our assessment to Anthropic. For the public version, Anthropic redacted a majority of the evidence we found most informative. As a consequence, the public must rely on our judgment more than we consider ideal.
“hey, saw your post on xyz…”
No, no you didn’t, no one talks or writes like this you cold outreaching clanker
Congrats @_catwu 🫡
Is anyone else getting VERY worried about the next major release lobotomizing our boy? 😰 I can't go back to Opus 5 days... I can't! I refuse!
Friday was my last day at Anthropic.
Two years ago, when Claude Code was a small internal tool, I asked it to build an RL env. I steered it for tens of hours but never manually wrote a line of code. It worked, I was hooked, and I joined the team.
When we first launched, most people approved every permission prompt by hand and mostly used Claude to answer questions and write tests.
Today, the default is trusting Claude's judgment to auto-approve. Claude does large migrations and builds new products.
Helping build Claude Code into an industry-defining product has been the journey of a lifetime.
Thank you to the incredible team behind Claude Code, Cowork, and Tag. These products are the sum of thousands of great ideas from you. I'll miss working with you all.
Thank you to our users for embracing a new way of working. Your constant feedback shaped so much of what we shipped and your stories made the work so meaningful.
Excited to see what you all make next!
This ugly regex is an INSANE AEO CHEAT CODE. Paste it into Google Search Console and pull out the EXACT questions your customers are asking ChatGPT and Claude!
Say someone searches “can I export my data on the free plan” and Google shows them your pricing page. Does your page say yes or no?
1. Open Performance → Search results.
2. Click + Add filter → Query → Custom (regex) → Matches regex.
3. Paste this and hit Apply.
^(?:who|what|where|when|why|how|which|whose|whom|is|are|was|were|do|does|did|can|could|will|would|should|may|might|must|have|has|had|am|best|top|difference|compare|vs|versus|alternative|alternatives|review|reviews|worth|which is|how much|how many|how long|how to|what is|what are|what does|is it|are there|should i|can i|do i|does it|why is|why does|pricing|cost|price|cheap|vs|better)\b(?:\s+\S+){2,}
4. Sort Queries by impressions. Click a question → Pages.
5. Answer it on that page. Name the plan. Show where to click.
Roads? Where we're going, we don't need roads. 😎
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…




