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Tool Stack

AI Employee Stack

Everything a role-owning agent needs: knowledge, tools, memory and reporting.

1 min readupdated 2026-08-01

/ quick answer

Run a persistent agent that owns a business function and reports on outcomes. Everything a role-owning agent needs: knowledge, tools, memory and reporting.

Everything a role-owning agent needs: knowledge, tools, memory and reporting. Run a persistent agent that owns a business function and reports on outcomes. The stack combines Claude or GPT-5 (reasoning), Make (system-to-system execution), Notion or Google Drive (SOPs and knowledge base), Supabase (memory and activity log), Slack (daily reporting and escalations). This tool stack node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.
Purpose
Run a persistent agent that owns a business function and reports on outcomes.
Tools Included
  • Claude or GPT-5 (reasoning)
  • Make (system-to-system execution)
  • Notion or Google Drive (SOPs and knowledge base)
  • Supabase (memory and activity log)
  • Slack (daily reporting and escalations)
Workflow Supported
Alternatives
  • n8n instead of Make
  • Airtable instead of Supabase
/ frequently asked

What is the AI Employee Stack stack for?

Run a persistent agent that owns a business function and reports on outcomes.

Which tools are in this stack?

Claude or GPT-5 (reasoning), Make (system-to-system execution), Notion or Google Drive (SOPs and knowledge base), Supabase (memory and activity log), Slack (daily reporting and escalations).

Are there alternatives to this stack?

Yes — n8n instead of Make, Airtable instead of Supabase.

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Related concepts

The vocabulary this page depends on.

  • AI Employee

    An AI employee is a persistent agent that owns a defined role — with a job description, tools, memory, KPIs and a manager — instead of running as a one-off task.

  • Agent Architecture

    Agent architecture is the structural blueprint of an AI agent: the model, the planning loop, the tools, the memory layer and the guardrails that decide how it acts.

  • Multi-Agent System

    A multi-agent system splits a job across several specialised AI agents that coordinate through a shared plan, message bus or orchestrator.

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Related workflows

Turn this into a repeatable process.

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Related tool stacks

The tools that run it in production.

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Related prompts

Reusable prompts for this job.

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Related use cases

How people apply it, and what came out.

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