Tenkai Daily — March 21, 2026
Open Source Releases
- claude-code v2.1.81 adds –bare flag for scripted calls and –channels permission relay
— The
--bareflag skips hooks, LSP, plugin sync, and skill walks for faster scripted-pcalls, requiring you to pass an API key explicitly. A new--channelsoption lets you forward permissions to channel servers, handy for automation pipelines. 🤖 - stateweave 0.3.10 — Think git for agent state: snapshots, branches, merges across LangChain, LlamaIndex, and other frameworks. You can roll back a bad prompt or migrate a running agent to a different stack without losing context. 📄
- rwkv-ops 0.8.0 — Provides PyTorch, JAX, and Keras implementations of the core RWKV operators (time‑mix, channel‑mix) with GPU kernels and autograd support. Drop‑in if you want to experiment with RWKV’s linear‑complexity recurrence in your own models.
- velar-sdk 0.4.11 — One‑command CLI that builds a container, sets up autoscaling, and serves your model on GPUs, abstracting away Docker, Kubernetes, and vendor‑specific tweaks. Useful when you just want to ship a model without becoming a DevOps guru. 🛠️
- claude-code v2.1.80 adds rate limit display and inline plugin configuration
— The status line now shows a
rate_limitsfield for 5‑hour and 7‑day Claude.ai usage, helping you spot throttling before it bites. You can also declare plugins directly insettings.jsonviasource: 'settings', skipping the marketplace UI. 🤖 - cdn-ai 0.4.1 — Implements Condensa, a language that compresses AI‑to‑AI chatter by ~70% while keeping zero‑shot interpretability high. Comes with encoder/decoder utilities and ready‑to‑plug adapters for popular LLM APIs.
Research Worth Reading
- FaithSteer-BENCH: A Deployment-Aligned Stress-Testing Benchmark for Inference-Time Steering — A benchmark that pushes activation‑based steering methods under realistic deployment noise, revealing where today’s techniques break. Good for checking if your steering trick will survive real‑world traffic.
MCP Servers & Integrations
- GitHub — An MCP server that lets AI agents run Git commands, manage PRs, and hook into CI pipelines straight from prompts. Enables fully automated code collaboration without leaving the agent loop. 🔧
Today’s Synthesis
Start by checkpointing your agent’s current configuration with stateweave
so you can roll back any failed tweak. Then launch a sweep of prompt variations using claude‑code v2.1.81
with the --bare flag; this strips hooks, LSP, and plugin sync for rapid scripted -p calls, letting you fire hundreds of iterations in a CI job without waiting for the full toolchain. While the sweep runs, you can enable cdn‑ai 0.4.1
to compress inter‑agent traffic by ~70%, cutting network overhead and letting you fit more trials into the same bandwidth. Collect the best‑performing prompt‑state pair, commit the new state snapshot via stateweave’s branch‑merge workflow, and push the change through the GitHub MCP server
to open a PR directly from the agent loop. Reviewers can diff the state like any code change, approve, and merge, triggering an automatic rebuild with velar‑sdk 0.4.11
to containerize and serve the updated model on GPUs in a single command. The whole loop—snapshot, bare‑metal prompting, Git‑based review, and one‑click serving—keeps experimentation fast, reversible, and production‑ready.