
🇨🇦/acc, technoalchemist @chaosgremlinlab
Lethbridge, Alberta
Joined August 2008
- Tweets2.3K
- Following2.5K
- Followers440
- Likes2K
Chris Rabl retweeted
instead of giving your agents / llm whatever a soul.md, tell it to never use first person, that it is an llm, not an "i"
its amazing, never going back
is this how mathematicians felt last week
BREAKING: OpenAI says it found a critical flaw in Brotli, a widely used compression library built into software like Node.js, Bun and Envoy.
The bug could let an attacker take over a system just by sending it malicious compressed data, with no login needed. That works both ways: a hacker could hijack an unpatched server, or a malicious server could hijack an unpatched user’s device.
Chris Rabl retweeted
Craziest news of the week: Andon Labs has a product
the CrossX app built by @jtaverasv is phenomenal and "just works". if you have an Xteink X3 or X4 it's definitely worth a download. i'm super impressed by the OSS community around this hardware!
incoming @modal appreciation post: i freaking love this product. ridiculously easy to run experiments with serverless GPUs!
grok 4.5 is decent (not on the same level as opus) but limited by 500k context, where it wins is SPEED omg this thing is fast
Chris Rabl retweeted
I might be one of the few people who is most bearish on human research taste and bullish on automated research:
- "AIs can only do hyperparameter search" is mainly a skill issue with bad automated research setups.
- human taste is overrated, e.g. frontier labs / neolabs are doing pretty simlar things.
- human taste might win in a low-compute world, but not a high-compute world we're entering.
opus 4.7 is extraordinarily good at following precise instructions, unfortunately it is also extraordinarily good at following instructions precisely
thank you @modal for existing! serverless H200 instances with snapshots are so nice for quick experiments
been data mining my claude code transcripts to figure out why conversations "feel worse" lately. pulled out 264 "tilt" incidents across 127 sessions, ~9k tool calls and this is what i found...
in contrast to others i don't think the fix is more thinking tokens. tool selection and "thrash" detection are two places to start: make the model verify against actual source material before it starts claiming things, and detect when the model starts swirling and second-guessing









