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✦AI & tech design · Atomic Projects 2025–2026

An AI agent operating system

Teaching an AI agent to run the parts of the business a founder didn’t have time for.

10×project volume
0new hires
1framework, not 5 ad-hoc efforts
Slack messageNew CRM leadScheduled checkInbound emailtriggersMemory: task + businessClaudeplan → act →observe → reflectTools: CRM, Slack, DocsguardrailWrite to CRMSend Slack updateUpdate docsAsk a humanactionsevery run logged1Discoveryagent calls tools via API25% agent-run2Document & planClaude maps the process55% agent-run3Scalemonitored automation85% agent-runeach step hands more of the work to the agent
triggers → Claude’s loop, with memory, tools and a guardrail → actions
!The problem

Clear docs, but nothing to scale on.

Ben needed to scale fast and had already bet on AI. I’d helped clean up his Notion: clear divisions, SOPs and documentation. What was missing wasn’t information. It was a system to scale on, across every function at once.

✦What I did

An agent with memory, tools and limits.

n8n handles tool access and orchestration, and Claude does the reasoning. But an agent that calls tools isn’t an operating system, so I gave it:

Memory→short-term for the task, long-term for the business
Tool registry→only the tools it’s allowed to touch
Guardrail→a human approves payments, external messages and deletions
Logs→every run feeds back into what it knows

On top, we ran a discovery → documentation → scale framework, handing more of the work to the agent at each step.

✓What happened

Ben directs. Claude executes.

Discovery, documentation and monitored automation now run on one framework instead of five separate efforts. The business handles 10× the projects with zero new hires.

A short screen-recorded walkthrough of the system in action.
Built with
n8nClaudeNotionAPI design