AgentsAutonomy & tool use
Julian Goldie demos paid 'Agent OS' dashboard combining Claude, Hermes, Antigravity and Codex
Creator Julian Goldie showed an 'Agent OS' that puts Claude, Hermes, Antigravity and Codex on one dashboard with video, SEO and call-scoring tools. It is sold as a zip in his paid community. No code, architecture or evaluation is published.
From the r/AISEOInsider (via last30days) article of October 15, 2026 and cited sources: The setup looks like a front end that runs existing agent command-line tools and adds saved workflows. [2] [7]
SOURCES[2] Linked video: 7 Lessons From Building My AI Multi Agent… youtube.com[7] OpenMontage GitHub github.com
AT Pulse research deskPublished · Updated · 4 min read · AI-assisted analysisAI-assisted, not human-edited. Methodology Corrections Who owns this site
- What happened
- The setup looks like a front end that runs existing agent command-line tools and adds saved workflows. [2] [7]
- Original source
- r/AISEOInsider (via last30days) article, independent perspective
- Brief by
- AT Pulse research desk AI-assisted; publisher and contact on the desk page
- When
- October 15, 2026 article published
- Covered
- Oct 16 edition
- Evidence
- 10 sources across 9 sites
- 17 Lessons From Building My AI Multi Agent Systemreddit.com
- 2Linked video: 7 Lessons From Building My AI Multi Agent…youtube.com
- 3Why Do Multi-Agent LLM Systems Fail? (arXiv)arxiv.org
- 4SD Times: Google Antigravitysdtimes.com
- 5Visual Studio Magazine: Google joins AI IDE racevisualstudiomagazine.com
- 6Hermes Agent (Nous Research) docsagentic-ai.readthedocs.io
RisingHow it’s measured
YouTube video · 2.7K views · 20 likes
Reach blends public engagement (views, likes, comments, shares, stars) from the platforms where the story or its original source lives: YouTube, Hacker News, GitHub, Substack and similar. A video and the article written from its transcript share one score, taken from the video. Platforms with no data are left out rather than counted as zero, and the age of a story never lowers its score.
The setup looks like a front end that runs existing agent command-line tools and adds saved workflows. It bundles off-the-shelf parts, such as Higgsfield and the open-source OpenMontage, and adds no new model capability. [2] [7]
The lessons worth copying are design habits: store generated output in one workspace, turn repeated prompts into one-click workflows (for example, a content-idea generator or a competitor scan), and hide tools that go unused. [2]
a demo with no metrics, code or user counts. Implication: the dashboard-plus-saved-workflow pattern matches the direction of tools like Google's Antigravity.
Read the full assessment
Teams should still measure multi-agent review and confirm call-recording consent before adopting similar setups.
Executive brief
The "Agent OS" in this post is a paid product funnel. The setup is sold as a zip file inside a paid Skool community, the "AI Profit Boardroom" (video 02:58). The author, Julian Goldie, says it puts Claude, Hermes, Antigravity and Codex on one screen and adds tools for video, SEO and scoring sales calls. No code, architecture, benchmark or user count is published, and no independent coverage was found. The useful part is the design pattern: one workspace that keeps output, saved one-click workflows instead of chat boxes, and agents that check each other's work. Published research shows that last pattern often fails.
What changed and event timeline
Research maps multi-agent failures
The MAST study looked at seven multi-agent frameworks and found 14 failure modes. Most came from how the system was designed and from agents working at cross purposes, not from the models themselves ().
Google launches Antigravity
An agent-first IDE launched alongside Gemini 3, free in public preview, that produces checkable "Artifacts" such as plans and screenshots (;).
OpenMontage gains traction
An open-source (AGPL-3.0) video production system that runs through coding agents like Claude Code and Codex (;).
Nous Research releases Hermes Agent
An MIT-licensed agent with memory that persists between sessions and skills it builds itself. A third-party docs page reports over 180,000 GitHub stars within four months ().
Goldie posts "7 lessons."
The Reddit post and the linked video show the Agent OS and promote the paid download (;).
Capabilities and access
The demo shows these components: No model versions are named. Access is through the paid community.
Read the full section
The demo shows these components:
- One dashboard holding Claude, Hermes, Antigravity and Codex, with "any CLI" pluggable (00:14, 05:09).
- Higgsfield video and ads, a "Search OS" that publishes SEO articles, and OpenMontage video (00:46, 01:17, 04:40).
- A sales tool that scores call recordings against the team's SOP (04:09).
- A Codex and Blender 3D tool, a voice agent, and a pixel-art "office" view of the agents (03:26, 04:50).
No model versions are named. Access is through the paid community.
Technical analysis for researchers and developers
- Architecture: no documentation.
- Pixel office: the name appears as "Starnet" in the auto captions and "Staret" in the post. Which one, if any, is used is unknown.
- The call-scoring tool's accuracy is not reported.
Read the full section
- Architecture: no documentation. From the demo, it looks like a front end that runs existing agent command-line tools, plus saved workflows: "Hermes Muse" suggests content ideas and "Hermes Astros" analyses competitors, each launched with one click (05:44).
- Pixel office: the name appears as "Starnet" in the auto captions and "Staret" in the post. Open-source tools with the same idea exist, such as Pixel Agents and Star-Office-UI (Pixel Agents; Tenten roundup). Which one, if any, is used is unknown.
- Evaluation: none. The call-scoring tool's accuracy is not reported.
- Reproducibility: none outside the paid zip.
Claims and evidence
No independent corroboration of the Agent OS itself was found.
Read the full section
- Saves time daily by replacing about 10 tabs (00:21): anecdotal, not measured.
- Agents in a group "catch each other's mistakes" (02:36): MAST lists inter-agent misalignment and weak checking of results as major failure categories (arXiv). Read the claim as a hope, not a measured result.
- Built over three to four hours a day (02:49): self-reported.
- Component facts: these come from vendor or project pages, not independent tests. OpenMontage's own counts differ by source: 52 tools and 500+ skills on one aggregator versus 100+ tools and 700+ skill files in the current README (Pinggy; GitHub).
No independent corroboration of the Agent OS itself was found.
Context and prior work
- Same direction as the IDEs: dashboards that coordinate agents and show their work are where the big vendors are heading too.
- Memory built in: Hermes already advertises memory that lasts across sessions and connections to messaging apps (Hermes docs).
- Off-the-shelf parts: the Agent OS mostly wires together existing open-source and commercial tools rather than adding new capability.
Read the full section
- Same direction as the IDEs: dashboards that coordinate agents and show their work are where the big vendors are heading too. Antigravity's "Artifacts" exist to make agent work checkable (SD Times).
- Memory built in: Hermes already advertises memory that lasts across sessions and connections to messaging apps (Hermes docs).
- Off-the-shelf parts: the Agent OS mostly wires together existing open-source and commercial tools rather than adding new capability.
Limitations, safety and contested findings
- Promotional source: the video repeatedly pushes the paid community and uses urgency, saying those who wait a year will be behind (07:20).
- Call recordings: the sales tool processes recorded calls. Consent and data handling are not discussed.
- Auto-publishing: articles go straight to the website, with no human review step shown.
Read the full section
- Promotional source: the video repeatedly pushes the paid community and uses urgency, saying those who wait a year will be behind (07:20).
- Call recordings: the sales tool processes recorded calls. Names were hidden in the demo but can be switched back on (04:26). Consent and data handling are not discussed.
- Auto-publishing: articles go straight to the website, with no human review step shown.
- Licensing: OpenMontage is AGPL-3.0, which matters if it is bundled into a redistributed zip (GitHub).
- Transcript quality: the transcript is auto-generated and may contain errors, including in names.
Business and practitioner implications
- Worth copying: keep generated output stored in one place, turn repeated prompts into saved workflows, and hide tools nobody uses (06:29).
- Treat multi-agent "review" as untested until you measure it. Use MAST's categories to audit failures (arXiv).
- Check before you buy: before installing a third-party agent bundle, review its license terms, API cost limits, credential handling and the permissions its command-line tools get.
Read the full section
- Worth copying: keep generated output stored in one place, turn repeated prompts into saved workflows, and hide tools nobody uses (06:29).
- Treat multi-agent "review" as untested until you measure it. Use MAST's categories to audit failures (arXiv).
- Check before you buy: before installing a third-party agent bundle, review its license terms, API cost limits, credential handling and the permissions its command-line tools get.
- Sales scoring needs checks: calibrate it against human reviewers and get legal sign-off on recording calls.
The source trail.
Sources (10)
7 Lessons From Building My AI Multi Agent System
Feed excerpt only. A transcript of the video linked from this page is supplied (linked video auto captions; https://www.youtube.com/watch?v=FvJKt59Kd9s); automatic text may contain errors.
reddit.comLinked video: 7 Lessons From Building My AI Multi Agent System
linked video auto captions
www.youtube.com