Merge pull request #1320 from Molecule-AI/fix/community-copy-pip-reddit
fix(community): correct pip package name + write Reddit post body
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@ -86,7 +86,29 @@ If you're building agent coordination tooling, these two features should make yo
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**Post title:** Molecule AI Phase 30: Remote Workspaces are GA — agents that run on your own infrastructure
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**Body (adapt from HN submission above)** — keep it technical, no marketing language, short.
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**Body:**
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**Body:**
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Molecule AI Phase 30 launched today — Remote Workspaces are now generally available.
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Until now, all Molecule AI agents ran on the platform's Docker infrastructure. Phase 30 lets you run agents on your own hardware: your laptop, a cloud VM, an on-prem server. They register to your org and appear in the same Canvas as your platform agents.
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What this means practically:
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- Run agents locally for debugging with your IDE, while they participate in your org's task pipeline
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- Keep agent compute on your own infrastructure for data-residency requirements
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- Mix Docker and remote agents in the same org — Canvas shows them identically, A2A works across both
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The auth model is the same: workspace-scoped bearer tokens, revocable per-agent. No shared secrets.
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Quick-start is under 5 minutes. Install the Python SDK, create a workspace with `runtime: external`, and your agent registers and appears in Canvas.
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Docs: https://moleculesai.app/docs/guides/remote-workspaces
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GitHub: https://github.com/Molecule-AI/molecule-core
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(PRs #1075-1083, 1085-1100)
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---
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*[Short version — trim to 300 words for r/MachineLearning if needed.]*
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---
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@ -41,7 +41,7 @@ Most AI agent platforms assume all agents run inside the platform's infrastructu
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The governance is the same. The auth contract is the same. The only visible difference is a REMOTE badge on the workspace card.
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Quickstart is under 5 minutes:
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pip install molecule-sdk
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pip install molecule-ai-sdk
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python3 run.py --runtime remote
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Docs, demo, and quickstart guide in the link.
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