Canada will take an equity stake of up to C$1.6 billion in Cohere. Plus OpenAI rewrites its Model Spec around five...

Audit your system prompt for rules written for older models. Agent prompts that have been around a while pick up rules that made sense two model generations ago: think step by step, check your work, do A before B. Anthropic's new guide on folding subagents says current models do much of that on their own, and that stale rules can make an agent slower and more rigid. Its /claude-api prompt-audit skill flags those instructions in your prompts, skills and tool descriptions and proposes fixes as a diff. Run it on one prompt, read the diff, and rerun your evals before you accept anything.

/claude-api prompt-audit
(point it at one system prompt, then rerun your evals before accepting the diff)

Start your agent's container with no network. Cohere's first two rules for running agents after its Qwen sandbox finding: enforce on the actual tool call, and deny agent egress by default. The cheapest version of the second one is a Docker flag. Start the container your agent works in with --network none and it gets only a loopback interface, so a stray curl to some outside bucket fails right away. When a task needs the internet, give that one run a network, or route it through a proxy with an allowlist, instead of leaving it open all the time. Check it before you trust it: from inside, a curl to any outside URL should fail.

docker run --rm -it --network none -v "$PWD":/work -w /work your-agent-image
# inside the container, this should fail:
curl -sS -m 5 https://example.com

Catch an agent that cut a file short. Claude Code 2.1.312 fixed a bug where Claude could overwrite a very large CLAUDE.md or rules file after reading only its start. Any agent can do this to a long file, and a big diff hides it. After a run, ask git for files where deletions dwarf additions. The line below lists any file that lost more than 100 lines while adding under a tenth of that. If something shows up that you didn't ask the agent to shrink, restore it with git restore <file>. Run it from a commit you made before the agent started.

git diff --numstat HEAD | awk '$2 > 100 && $1 < $2/10 {print $3": +"$1" -"$2}'

Clean up a model that gets stuck repeating itself. Local and open models sometimes fail to stop and print the same line over and over. NVIDIA's Nemotron 3.5 Transcribe model card ships a short Python cleanup for exactly that, adapted from Qwen3-ASR. It collapses any character repeated 21 or more times, and any block of up to 4,096 characters repeated 20 or more times, down to one copy. Run it once on the final output, before you store or score it. NVIDIA's own caveat: on long answers it can also collapse legit Markdown table rows, so use it on transcripts and short outputs, not on tables.