Hermes
An AI coding agent used as part of Multica's multi-agent development workflow. It is mentioned as one of several agents assigned tasks from a shared board.
Key Highlights
- Hermes is cited as both a coding agent in Multica's workflow and a personal agent in the GBrain/OpenClaw ecosystem.
- Its mentions highlight key PM themes: agent orchestration, memory-augmented workflows, deployment channels, and benchmarking.
- Hermes has been connected to shared traces, WebRTC and Twilio deployment, X-native search, and Kanban-based task assignment.
- For AI PMs, Hermes is most useful as a real-world example of agents moving from demos into operational product workflows.
Hermes
Overview
Hermes is an AI coding and personal agent tool that appears in two closely related contexts: as part of Multica's multi-agent software development workflow, and as an agent used alongside Garry Tan's GBrain/OpenClaw ecosystem. Across newsletter mentions, Hermes is described as a task-executing agent that can be assigned work from a shared board, connected to personal knowledge systems, and deployed through interfaces like WebRTC or Twilio. It has also been referenced in benchmarking alongside other coding agents such as Claude Code, Codex, and Gemini.For AI Product Managers, Hermes matters less as a single feature product and more as a signal of where agent tooling is heading: operationally embedded, multi-agent, knowledge-aware, and increasingly connected to real workflows rather than isolated demos. Hermes shows up in examples involving task routing, personal knowledge augmentation, native search, trace sharing, and lightweight deployment, making it useful as a case study for how AI agents can move from experimentation into daily execution.
Key Developments
- 2026-04-07: Hermes is mentioned in connection with open-sourced agent traces shared via Traces.com, alongside OpenCode and Claude, to help create a crowdsourced dataset for open-source agent models.
- 2026-04-13: Garry Tan highlights that OpenClaw or Hermes can be installed from the gbrain repo and run on WebRTC or through a Twilio number in under 30 minutes.
- 2026-05-02: Garry Tan uses an OpenClaw/Hermes setup with 17 years of Foursquare check-in data to auto-generate personalized travel guides, illustrating Hermes as a personalized agent layer on top of memory-rich data.
- 2026-05-06: Peter Yang benchmarks Hermes against OpenClaw, Claude Code, Codex, and Gemini, with no clear overall winner among the agents.
- 2026-05-17: xAI integrates X Premium subscriptions into Hermes Agent and adds native search across X posts, expanding Hermes' access to platform data and discovery workflows.
- 2026-06-01: Garry Tan open-sources GBrain under MIT license and describes a 30-minute setup using his large markdown wiki plus an OpenClaw/Hermes agent that automates many tasks.
- 2026-06-06: Multica uses a local “Multica Demon” bridge between its Kanban board and local AI coding agents including Cloud Code, CodeX, and Hermes, enabling direct task assignment and rapid daily shipping by a four-person team.
Relevance to AI PMs
1. Designing multi-agent delivery workflows: Hermes is a concrete example of an agent being assigned work from a shared task system rather than only operating in chat. AI PMs can use this pattern to think about orchestration, task decomposition, handoffs, and throughput metrics across multiple agents.2. Evaluating knowledge-aware agents: Mentions tying Hermes to GBrain, imported personal data, and native search suggest that agent performance depends heavily on context sources. PMs can use Hermes as a reference point when deciding whether product value comes from the base model, proprietary memory layers, workflow integrations, or retrieval/search access.
3. Planning deployment and observability: Hermes appears in settings involving local deployment, WebRTC, Twilio, and shared traces. For PMs, this highlights practical implementation questions: where the agent runs, what channels it supports, how traces are captured, and how to compare quality across competing agents like Claude Code, Codex, and Gemini.
Related
- Multica / Multica Demon: Hermes is one of the local coding agents connected to Multica's board-driven development workflow through the Multica Demon bridge.
- GBrain / gbrain-repo: Hermes is repeatedly associated with Garry Tan's GBrain knowledge system and installation flow from the gbrain repo.
- OpenClaw: Frequently paired with Hermes as a comparable or companion agent in the GBrain ecosystem.
- Claude, Claude Code, Codex, Gemini, Cloud Code, OpenCode: These are adjacent coding or agent tools used for comparison, benchmarking, or trace-sharing alongside Hermes.
- Traces.com: Used to share Hermes agent traces as part of an open dataset effort.
- WebRTC / Twilio: Referenced as deployment or communication surfaces for running Hermes.
- xAI / X Premium: Connected through an update that added X Premium subscription support and native X post search to Hermes Agent.
- Garry Tan / Peter Yang: Two notable figures associated with Hermes through setup guides, ecosystem framing, and benchmark commentary.
Newsletter Mentions (7)
“Multica uses a local “Multica Demon” script to bridge its Kanban board with local AI coding agents (Cloud Code, CodeX, Hermes), enabling direct assignment of tasks to agents and daily shipping by a four-person team.”
#11 ▶️ Your AI Agents Block on You - Here's the Fix 🧵 SyntaxGTM Multica uses a local “Multica Demon” script to bridge its Kanban board with local AI coding agents (Cloud Code, CodeX, Hermes), enabling direct assignment of tasks to agents and daily shipping by a four-person team.
“Garry Tan open-sourced GBrain (MIT-licensed) on GitHub and outlines a 30-minute setup using his 350k-page markdown LLM wiki plus an OpenClaw/Hermes agent that automates most tasks.”
#6 𝕏 Garry Tan open-sourced GBrain (MIT-licensed) on GitHub and outlines a 30-minute setup using his 350k-page markdown LLM wiki plus an OpenClaw/Hermes agent that automates most tasks.
“#2 𝕏 xAI integrates X Premium subscriptions into Hermes Agent and equips it with native search across X posts.”
Today's top 13 insights for PM Builders, ranked by relevance from X, Blogs, and LinkedIn. Why LLM features need end-to-end observability metrics #1 𝕏 Boris Cherny upgraded /usage to show personalized token usage by plugin, skill, and parallel agent, so you can pinpoint high-consumption drivers and maximize your doubled rate limits. #2 𝕏 xAI integrates X Premium subscriptions into Hermes Agent and equips it with native search across X posts. #3 📝 PromptLayer Blog A deep dive into LLM observability tools - Discusses the need for observability when shipping LLM-powered features, since models can return confidently wrong answers while logs show successful API responses. Argues observability must connect inputs, outputs, latency, cost, and quality to diagnose real production issues. #4 𝕏 Sebastian Raschka presents a visual overview of recent LLM architectures—from Gemma 4 to DeepSeek V4—showcasing long-context efficiency tweaks. He dives into innovations like KV sharing, per-layer embeddings, layer-wise attention budgets, compressed attention, and mHC. #5 𝕏 Garry Tan launched GBrain, an open-source knowledge system (not RAG in a box) with eight memory-enhancing layers that make agents like OpenClaw and Hermes feel clairvoyant about you, paving the way for personal AI.
“in Peter Yang benchmarks five personal AI agents—OpenClaw, Hermes, Claude Code, Codex, and Gemini—and finds no clear winner.”
#9 in Peter Yang benchmarks five personal AI agents—OpenClaw, Hermes, Claude Code, Codex, and Gemini—and finds no clear winner.
“Garry Tan imported 17 years of Foursquare check-in data (5,000+ entries) into his OpenClaw/Hermes platform to auto-generate personalized travel guides, starting with his top spots in San Francisco.”
Garry Tan imported 17 years of Foursquare check-in data (5,000+ entries) into his OpenClaw/Hermes platform to auto-generate personalized travel guides, starting with his top spots in San Francisco. Garry Tan released GBrain v0.25 to let contributors benchmark AI evaluations against their own real-world brain queries.
“#2 𝕏 Garry Tan shows how to install OpenClaw or Hermes from his gbrain repo and have it running on WebRTC or your Twilio number in under 30 minutes.”
GenAI PM Daily April 13, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 14 insights for PM Builders, ranked by relevance from X, Blogs, and YouTube. #2 𝕏 Garry Tan shows how to install OpenClaw or Hermes from his gbrain repo and have it running on WebRTC or your Twilio number in under 30 minutes. He likens it to a Homebrew computer club for personal AI.
“#8 𝕏 clem 🤗 is open-sourcing their agent traces from Hermes, OpenCode, and Claude via Traces.com to kickstart a crowdsourced dataset for open-source agent models, and urges other builders to share theirs too.”
#8 𝕏 clem 🤗 is open-sourcing their agent traces from Hermes, OpenCode, and Claude via Traces.com to kickstart a crowdsourced dataset for open-source agent models, and urges other builders to share theirs too.
Related
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AI/PM commentator and curator who appears in the newsletter as a credited source and amplifier of AI workflow examples.
An AI coding tool used in agentic workflows. Here it appears as one of the platforms Omnigent plugs into.
A modified or forked Claude-related interface/tool used to expose reasoning traces. It matters for PMs as an example of surface-level observability for model reasoning.
Gemini is Google’s AI model family used here for generating workout video imagery and content prompts. The newsletter references a specific Nano Banana model within Gemini.
Tech executive and investor who is cited here introducing GBrain. The newsletter presents him as sharing an open-source retrieval layer for agents.
xAI is an AI company building models and consumer AI experiences. Here it is referenced for subscription access inside Warp.
An MIT-licensed open-source retrieval layer for AI agents that dynamically selects relevant context. It is described as a Postgres-like librarian for agent memory.
A local AI coding agent mentioned as part of Multica's workflow stack. It is used with issue boards and team playbooks for task execution.
A coding agent or development tool mentioned as an integration target for Omnigent. It is part of the agent workflow stack discussed in the newsletter.
A communications platform used here as a runtime/connection endpoint for personal AI demos. It is mentioned alongside WebRTC in a quick setup workflow.
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