IT OPS

Agent-Orchestrated Offboarding Deprovision Plan

A CEO-led offboarding agent reads the leaver's role and access footprint, drafts a tool-by-tool deprovision plan with risk ordering, executes the revocations.

CategoryIT Ops
Enginepaperclip
Difficultyadvanced
Triggerchat
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerManager opens offboarding request in CEO chat
  • ActionQuery Postgres for role, grants, and owned resourcesPostgreSQLPostgres
  • LogicDraft risk-ordered plan; gate shared/billing seats for approval
  • ActionExecute GitHub admin and org access revocationsGitHubGitHub
  • OutputReport completed and pending-signoff items to SlackSlack

What it does

Hands offboarding to an agent that reasons about the specific person rather than running a fixed checklist. It assembles the leaver's full access footprint, decides the safest revocation order (high-risk admin access first), carries out the deprovisioning, and escalates anything ambiguous to a human.

When to use it

Use it for senior or admin-heavy departures where blanket revocation is risky and you want judgment about sequencing, shared-account handling, and what genuinely needs a manager's approval before being cut.

How it works

  1. 1A manager opens an offboarding request in chat naming the departing employee.
  2. 2The agent queries Postgres for the person's role, access grants, and owned resources.
  3. 3It drafts a risk-ordered deprovision plan, revoking GitHub admin and org access first.
  4. 4A logic gate holds any shared-account or billing-owner seat for explicit approval.
  5. 5The agent executes the approved revocations tool by tool.
  6. 6It returns a completion report to Slack listing what was deprovisioned and what awaits sign-off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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