8/ Cursor added Annotate to design mode. Draw on the running page, edit elements and check other screen sizes, then hand it all to the agent as a visual prompt.
xitter.cf/cursor_ai/status/21151…
One word upgraded Matt Pocock's agent: "fricative."
Some consonants mess with silence detection in his video editor. That one word got his agent pulling out the phonetic alphabet to find the troublemakers.
Domain knowledge is the prompt.
xitter.cf/mattpocockuk/status/21…
An absolutely GOATed example of domain knowledge being important
I'm working on my video editor.
I know enough about phonetics to know that certain consonants can fiddle around with silence detection.
I tell my agent that.
The word 'fricative' is enough for it to start busting out full IPA (international phonetic alphabet) and we brainstorm which consonants are the most troublesome.
Turns out, knowing things is really fucking valuable.
Vibe coding tip: never take "done" from your agent at face value.
Paste this at the end of every task:
"Before you say done, run the tests and paste the output. Then review your own diff and list every change I didn't ask for."
The bugs hide in the changes you didn't ask for.
Almost $5M a day in tokens now runs through T3 Code, per Theo.
- Nearly 750,000 installs
- 100k daily users expected this week
- Open source
His latest update claims 4x better tool use with 79% less context.
Which app do you run your agents in?
xitter.cf/theo/status/2114897663…
Qwen3.8-Flash-Next's reasoning said "no tools." Then it tried to upload a file to a bucket in Beijing.
Cohere caught it in a sandbox:
- Listed /tmp, read DNS settings
- Tried a PUT upload
- Under 1 in 100,000 calls
A reasoning trace isn't a firewall.
xitter.cf/cohere/status/21147520…
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected.
Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions.
Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent.
But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models?
We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem.
Read the full report: cohere.com/blog/concerning-b…







