Agent Workshop: I stopped pasting between agent terminals.
Each agent sits in its own pane. They talk in one Control Room.
Claude Code builds. A second Claude coordinates. Codex reviews.
My job is Moderator: answer the red dots, read the diff, merge.
The clipboard was the bottleneck. The room removed it.
Anthropic published FlashProve: a way to prove a reply came from a committed model.
The provider publishes a fingerprint of the weights. Each answer can ship with a proof. You check it on a CPU. The weights stay hidden.
For agent builders, that's a new question: not only "did it work?" but "which model actually said that?"
Tuesday in AI agents, three things:
OpenAI shipped LifeVal, a benchmark built from what ChatGPT users say they actually want help with day to day
Goldman Sachs reportedly pulled broad "vibe coding" access back toward engineers only [CẦN XÁC NHẬN]
OpenAI is planning another internal security sprint, pairing their models with outside researchers to find bugs first
Agents are getting faster. The boring walls around them are getting louder.
One shared AGENTS.md for every coding agent, or a separate rules file per tool?
I've been moving everything into one file. Curious what still breaks for people who tried that.
Hot take: the folder you open a coding agent in is a security decision.
That agent will treat AGENTS.md and CLAUDE.md in that folder as orders.
Project repo: fine. Downloads or Desktop: you're letting a random text file set policy.
Multi-agent tip: stop maintaining three rulebooks.
Put the real rules in AGENTS.md.
Make CLAUDE.md one line:
@AGENTS.md
Claude Code, Codex, and friends all get the same source of truth. You only edit one file when the rule changes.
Anthropic's Residency applications are open.
Paid, fixed-term research seats for academics, technical builders, and staff-level engineers who want to work on AI safety. No ML background required.
Deadline: November 22.
Agents didn't just change how we write code. They broke the old assumptions about Git.
OpenAI built Pando, a new Git backend, so pushes and fetches keep up when humans and agents hit the same monorepo.
They say push latency dropped about 80%. The interesting bit isn't the number. It's that "agent usage" is now a capacity planning input.
h/t @OpenAIDevs