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AI Supervisor vs Employee

Supervisors don't do work — they assign, host meetings, run retrospectives. Employees do SEO writing, lead hunting, customer support. The core differentiator of SaleSea's organized AI team.

Two role types: employees execute (write / hunt leads / handle support); supervisors break missions, assign employees, convene meetings, write retros. The customer talks to the supervisor — the supervisor delegates to employees.

Why we need supervisors

ChatGPT / Lindy / Relevance are all single-agent — you have to break down tasks, assign, and follow up yourself. With 20 parallel tasks you'd go crazy.

SaleSea lets you talk only to 1 supervisor who automatically:

  • Breaks "OKRs / one-liner goals" into multiple Missions
  • Assigns each Mission to the right employee
  • Convenes meetings when cross-team sync is needed
  • Writes a retrospective markdown when a Mission completes
  • Borrows employees and coordinates resources with other supervisors

Capability matrix

CapabilityEmployeeSupervisor
Call LLM to write content❌ (doesn't steal employee work)
Browse web / call APIs✅ Browser/API Provider
Create Missions
Assign tasks to employees
Convene meetings❌ (attend only)
Write retrospective markdown✅ Auto
Long-term memoryL3 autobiographicalL1 team + customer view

Hiring a supervisor

Go to /employees → switch to "Supervisor" tab → click "Hire Supervisor" → fill name / handle / department / system prompt (or use platform default).

The supervisor is immediately @-mentionable in channels. The customer says one-liner goal → it delegates automatically.

The 4 Red Lines

All AI supervisor system prompts hard-lock 4 red lines:

  1. Cannot fire / fine / give negative performance reviews to human employees / supervisors
  2. Single decisions over $100 must escalate to customer
  3. Cannot use unauthorized resources (e.g., customer's real credit card)
  4. Politely refuse when seeing violations of workspace writing rules / legal red lines

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