# Daily Hermes + AI Research Brief — 2026-05-24

## Important updates

- **Hermes Agent v0.14.0 shipped May 16 as the “Foundation Release.”** Highlights: PyPI install path, ~19s faster cold start, 180x faster Browser CDP calls, native Windows beta, OpenAI-compatible local proxy for OAuth-authed providers, xAI/SuperGrok OAuth with 1M-context Grok, LINE/SimpleX/Teams platform work, `/handoff`, LSP diagnostics on writes, and new optional skills. This matters for Atlas because it reduces install friction and opens a useful “Hermes as local provider proxy” pattern for Codex/Aider/Cline/Continue experiments. Source: [GitHub releases](https://github.com/NousResearch/hermes-agent/releases).

- **Hermes v0.13.0’s durable Kanban/multi-agent board remains the most relevant recent Hermes architecture change.** The release notes describe durable heartbeats, reclaim/zombie detection, auto-blocking, task lifecycle, and worker/orchestrator patterns. This is directly applicable to Will’s Atlas/local-swarm work: use the board as the durable coordination boundary instead of ad-hoc background sessions. Source: [Hermes releases](https://github.com/NousResearch/hermes-agent/releases).

- **LiteLLM opened an alpha Managed Agents Platform on May 8.** It is a self-hosted platform for running multiple agents in production, focused on per-team/context sandboxes and session persistence across pod restarts/upgrades. Worth watching as a comparison point for Hermes Kanban + profiles + gateway on Kubernetes. Source: [LiteLLM blog](https://docs.litellm.ai/blog/agent-platform-alpha).

- **vLLM’s latest developer docs now document experimental disaggregated prefilling.** The page describes splitting prefill and decode across separate vLLM instances and transferring KV cache via connectors such as NIXL, OffloadingConnector, and FlexKV; it was updated May 6. This is practical for CoreWeave-style GPU/k8s serving experiments where prefill/decode bottlenecks need separate scaling. Source: [vLLM disaggregated prefilling docs](https://docs.vllm.ai/en/latest/features/disagg_prefill/).

- **MCP governance/security capacity is expanding.** The MCP project added Clare Liguori as Core Maintainer and Den Delimarsky as Lead Maintainer; the post emphasizes production agent runtimes, triggers/events, authorization, RFC 8707 resource indicators, and security work. This matters because MCP is becoming long-lived infra, not just a tool-call fad; Hermes MCP integration should track auth/security spec changes closely. Source: [MCP blog](https://blog.modelcontextprotocol.io/posts/2026-04-08-expanding-maintainer-team/).

## Actionable ideas for us

- **[quick]** Test `pip install hermes-agent` in a clean disposable venv/container and note any Atlas bootstrap simplifications vs the current install path.
- **[experiment]** Prototype the new Hermes OpenAI-compatible local proxy with one external coding client (Aider/Cline/Codex) and one OAuth provider; record latency, auth refresh behavior, and whether prompt caching survives the proxy path.
- **[experiment]** Map Hermes Kanban concepts to the Pi/Atlas swarm: task table = durable queue, profile = worker role, heartbeat/reclaim = supervisor; avoid inventing a parallel scheduler until this is evaluated.
- **[watch]** Track vLLM disaggregated prefill + LiteLLM componentized/agent platform work for a future GPU/k8s inference control plane design.

## Worth ignoring

- Generic “agent framework star race” and listicle posts unless they include reproducible architecture details or benchmarks.
- Consumer-only “AI assistant” announcements without tool protocol, deployment, privacy, or local-first implications.

Saved to Obsidian: Atlas/Daily Research/2026-05-24 - Hermes AI Brief.md
