SkillOS gives organizations what human teams cannot do manually: turn every completed job into a tested, reusable skill that can upgrade every authorized agent across the network.
AUTOMATION
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Packaging thinking into reusable AI Skills is the next moat
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The next AI moat won’t be “I know how to prompt.” That’s already getting commoditized. The real moat is packaging how you think into a Skill people can run. Your edge becomes reusable.
Your process becomes a product.
Your brain starts earning without being in the room. -
Using External AI Agents with MagicPath, Cursor, and Claude Code
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Here are all the instructions on how you can use external agents in MagicPath with Cursor, Codex, Claude Code, etc.
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Cursor Composer 2.5 Swarms Agents to Build Web Pages and Mobile Apps
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Watch Cursor Composer 2.5 swarm 10 agents inside MagicPath, building functional pages, a mobile app, and a bunch of components for the same project.
— Pietro Schirano (@skirano) 26 mai 2026
Then I export whatever I want into Figma.
Pretty crazy.
(video is not sped up) pic.twitter.com/DvdZa57iJiWatch Cursor Composer 2.5 swarm 10 agents inside MagicPath, building functional pages, a mobile app, and a bunch of components for the same project. Then I export whatever I want into Figma. Pretty crazy.
(video is not sped up) -
Higgsfield Supercomputer: AI Agent for Complete Creative Workflows
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🚨Higgsfield Supercomputer is a cloud-native AI agent that turns one chat into a full creative workflow. It helps with planning, scripting, visuals, voice, editing, and publishing in one place.
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 26 mai 2026
▪️40+ built-in tools for content creation.
▪️3 layers of memory to keep context… pic.twitter.com/78Zcsy6K1jHiggsfield Supercomputer is a cloud-native AI agent that turns one chat into a full creative workflow. It helps with planning, scripting, visuals, voice, editing, and publishing in one place. 40+ built-in tools for content creation.
3 layers of memory to keep context -
Using Traces to Build Production Agent Evaluations
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@AdamRLucek on how we use traces to build evals for production agents. -
Multi-Agent Retention Patterns in Graph-Based AI Systems
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Multi-agent retention is a great extension of this. The execution agent needs a tight working set, the audit agent needs full provenance. Context templates in Graphiti help here. Same underlying graph, but each agent gets a different view scoped by edge types, entity types, and
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SkillOS: Agents Learn Once, All Level Up
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AI agents shouldn’t start from zero every time. SkillOS captures what works from each job, turns it into a tested Skill, and shares it with every approved Agent. One Agent learns.
All Agents level up. That’s how AI work becomes compounding intelligence. -
MagicPath Introduces Figma Export with AI Agent Integration
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Introducing Figma export in MagicPath.
— Pietro Schirano (@skirano) 26 mai 2026
Design and build with our native agent, or your favorite external one (Codex, Claude Code, etc.).
Explore tons of different directions, then bring your work into Figma as fully editable designs.
As simple as a copy-paste. pic.twitter.com/ON9h0UCXpuIntroducing Figma export in MagicPath. Design and build with our native agent, or your favorite external one (Codex, Claude Code, etc.). Explore tons of different directions, then bring your work into Figma as fully editable designs. As simple as a copy-paste.
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AI Copilot for Industrial Telemetry Analysis and Documentation
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The system feeds live and historical telemetry into the same copilot connected to ABB's documentation library for analysis.