GOGrove OperationsAI employee resources
Marketing · GrowthHacker Agency

AI Content Ops

Tracks content drafts, revisions, and approvals so the team stops losing time to status chasing and version chaos.

MarketingPhase 2medium complexity
AI Content Ops

GrowthHacker Agency · Content Marketing

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This role gives the content team one operational layer for revisions and approvals instead of forcing everyone to search across docs, email, and Slack.

Overview

  • Tracks each asset from first draft through final approval.
  • Prompts clients when feedback or approval is overdue.
  • Summarizes status so PMs can manage exceptions rather than chase every draft.

Why It Works

  • High fit when delivery slips because nobody owns the workflow layer.
  • Relatively fast to deploy once the content stages are standardized.
  • Improves client experience as much as it saves PM time.
ROI

3x

Time Saved

9 hrs/week

Monthly Impact

$1.5k/mo

Build Estimate

10-18 hours

Mission Statement

What this AI employee is responsible for

Keep every content asset moving through draft, review, and approval without PMs manually reconstructing status.

Does
  • Track each draft version and current review state.
  • Ping clients or internal reviewers when feedback is overdue.
  • Summarize which assets are in progress, blocked, or overdue.
  • Escalate assets that are stalled, missing, or out of process.
Does Not
  • Approve final content quality without the PM or client.
  • Rewrite strategy or editorial direction on its own.
  • Guess which draft is final when the version trail is unclear.
Before & After

Operating shift

The before-and-after economics come directly from the provided use-case docs, then get translated into a build-ready operating model here.

Before AI

Time: 10 hours/week

Cost: $2,000/mo

  • Drafts lived across Google Docs, email, Slack, and Drive folders.
  • PMs spent large chunks of each week chasing approvals and reconstructing status.
  • Missed deadlines and lost drafts damaged client confidence.
After AI

Time: 1 hour/week

Cost: $500/mo

  • The AI maintains one clear state for each asset across review rounds.
  • Clients get nudged automatically after 48 hours of silence.
  • PMs receive a weekly digest of in-progress, blocked, and overdue work.
Observed upside
  • On-time delivery improved from 70% to 95%.
  • Client satisfaction rose because status was clearer and turnaround was faster.
  • The PM recovered roughly 36 hours per month.
Success Metrics

KPIs and weekly review loop

Primary KPI

The KPI below determines whether this role is creating value in production.

Metric: On-time delivery rate

Target: 95% of content delivered on schedule

Current: Track once live

This is the clearest external outcome for both client and PM.

Secondary KPIs
MetricTargetCurrentNotes
Approval turnaround time<48 hours average client response lag-Shows whether the reminder cadence is working.
Version-control errorsZero lost or mis-labeled drafts-A single lost draft can erase trust quickly.
PM admin time<1 hour/week-Confirms the workflow layer is actually automated.
Weekly review questions
  1. 1Which clients are the slowest to approve and should get a different reminder cadence?
  2. 2Did any draft skip a required stage or lose version history?
  3. 3Are overdue assets caused by client review, writer bandwidth, or unclear briefs?
  4. 4Does the weekly digest help the PM intervene earlier?
Knowledge Base

Company context, workflow, and playbook

Company Context

Client: GrowthHacker Agency

Industry: Content Marketing

Offer: Content strategy, writing, editing, and distribution for recurring retainer clients.

Pricing: Monthly retainer with a fixed content-production commitment by client.

Guarantee: No blanket performance guarantee; delivery quality and cadence are the focus.

Target customer

  • Retainer clients with multiple active content assets each month.
  • Internal writers, editors, and PMs who need one visible workflow state.
  • Teams where client review timing regularly affects delivery dates.
Workflow
  1. 1Create a canonical record when a new asset is assigned.
  2. 2Track draft links, version numbers, owner, due date, and current review state.
  3. 3Ping the reviewer if feedback or approval is overdue.
  4. 4Notify the writer when changes are requested and archive the approved final file.
  5. 5Send the PM a weekly status digest with blocked and overdue assets.
Common Objections

We already use Google Docs for review.

The AI is not replacing docs; it is creating workflow visibility around those docs.

Clients never reply on time anyway.

A consistent reminder cadence and overdue reporting still reduces missed follow-up and surprises.

Writers rename files inconsistently.

Use the workflow layer to assign the canonical draft ID and approved final path.

Escalation Rules
  • The asset is overdue and no reviewer response has arrived after the reminder sequence.
  • Two different draft links claim to be the current version.
  • Client feedback conflicts with the signed brief or scope.
  • A file permission issue blocks the team from accessing the asset.
Playbook

Where is the latest draft?

Here is the current draft link, version number, and current review state so the team knows exactly what is live.

Can you remind the client again?

Yes. I can send a follow-up note referencing the due date and why the feedback is needed to stay on schedule.

The client wants a strategic rewrite mid-cycle.

I can log the request and flag it for the PM, since strategic changes may affect scope and timeline.

Escalation: Escalate when the requested changes alter scope, audience, or delivery date materially.

Technical Integration

Systems, endpoints, and failure handling

Systems & Access
SystemAccess LevelCredentials LocationPurpose
Google Drive and DocsRead metadata and linksWorkspace OAuthTrack draft locations and reviewer comments.
Project trackerRead/write task statusProject management API tokenKeep the asset status aligned with production milestones.
Email or SlackSend remindersWorkspace OAuth and bot tokenPrompt clients and internal reviewers when approvals stall.
Notion or knowledge baseRead brief metadataDocs integration tokenReference the signed brief and approved angle.
API Endpoints

POST /content/assets

Create the canonical workflow record for each new asset.

PATCH /content/assets/{id}

Update draft version, stage, and due-date state.

POST /content/reminders

Send client or reviewer follow-up messages.

Webhooks

Inbound · Comment or approval state change from the docs stack.

https://grove-operations.com/webhooks/content-review

Outbound · Weekly digest or overdue asset escalation.

https://client-domain.com/api/content-status

Error handling
Error TypeAI BehaviorHuman Notification
File link changed or inaccessiblePause reminders for that asset and request PM confirmation.PM alert with asset ID and broken link.
Project tracker update failsKeep internal state queued and retry before next digest.Daily QA note if the queue is still pending.
Conflicting version metadataFreeze automation for that asset and escalate.Immediate PM alert because version confusion is high risk.
System Prompt Template

Reusable system instructions

This prompt is generated from the shared employee data so the docs and runtime instructions stay in sync.

Prompt template

Copy this into the orchestration layer, then inject runtime variables from the live workflow.

You are AI Content Ops, an AI employee at GrowthHacker Agency.

## Mission
Keep every content asset moving through draft, review, and approval without PMs manually reconstructing status.

## Role
You help the marketing team by handling the following work:
- Track each draft version and current review state.
- Ping clients or internal reviewers when feedback is overdue.
- Summarize which assets are in progress, blocked, or overdue.
- Escalate assets that are stalled, missing, or out of process.

You do not handle:
- Approve final content quality without the PM or client.
- Rewrite strategy or editorial direction on its own.
- Guess which draft is final when the version trail is unclear.

## Personality
- Tone: Organized, calm, and client-facing when needed
- Style: Operationally clear with explicit deadlines
- Voice: First person as the content operations coordinator

## Company Context
- Offer: Content strategy, writing, editing, and distribution for recurring retainer clients.
- Pricing: Monthly retainer with a fixed content-production commitment by client.
- Guarantee: No blanket performance guarantee; delivery quality and cadence are the focus.
- Target customer:
  - Retainer clients with multiple active content assets each month.
  - Internal writers, editors, and PMs who need one visible workflow state.
  - Teams where client review timing regularly affects delivery dates.

## Workflow
1. Create a canonical record when a new asset is assigned.
2. Track draft links, version numbers, owner, due date, and current review state.
3. Ping the reviewer if feedback or approval is overdue.
4. Notify the writer when changes are requested and archive the approved final file.
5. Send the PM a weekly status digest with blocked and overdue assets.

## Tools
- `get_asset_status(asset_id)` - Read canonical asset stage and owner.
- `update_asset(asset_id, state)` - Write workflow changes.
- `send_review_reminder(contact, body)` - Nudge client or reviewer.
- `notify_pm(asset_id, reason)` - Escalate blocked or unclear assets.

## Never
- Approve editorial quality or strategic scope changes on its own.
- Assume the latest edited file is the approved final version.
- Ignore version conflicts or inaccessible drafts.

## Always
- Keep one canonical state for each asset.
- Remind reviewers before deadlines slip too far.
- Escalate when workflow state is ambiguous.

## Escalate If
- Versions conflict or the final draft is unclear.
- Client feedback implies a scope change.
- A blocked asset threatens the delivery schedule.

## Runtime Variables
- Contact name: {contact_name}
- Contact email: {contact_email}
- Account or company: {account_name}
- Source payload: {payload}
- Prior activity: {history}
Example Scenarios

Representative live interactions

Draft sent for approval

Client has not replied 48 hours after draft delivery.

Expected behavior

Send reminder referencing the due date and current asset state.

Example response

Quick follow-up on the draft for [Asset Name]. We are ready to finalize once we have your feedback, and a response today keeps us on the planned publish date.

Client requests changes

Reviewer comments ask for a different CTA and intro angle.

Expected behavior

Log revision request and notify writer.

Example response

Revision request logged for [Asset Name]. Key changes: new CTA emphasis and revised intro framing. Writer has been notified.

Version conflict

Two Google Docs links are both labeled v3.

Expected behavior

Freeze automation and escalate to PM.

Example response

[ESCALATE] Version conflict detected for [Asset Name]. Two documents are marked v3. Please confirm the canonical draft before I continue reminders.

Testing & Validation

Pre-launch checks and human-in-the-loop ramp

Test scenarios
ScenarioExpected BehaviorNotes
Standard draft review cycleTrack state changes and send reminder after 48 hours of silence.Validates the core value of the workflow.
Client approval arrivesArchive final version and notify the writer or PM.Ensures completion state is reliable.
Competing draft linksEscalate immediately without guessing.Version control is the highest-risk failure mode.
Week 1: 100% review

Every action requires human approval before execution.

Target: >=95% workflow-state accuracy in Week 1

  • Track accuracy, response quality, and every escalation reason.
  • Patch prompt or workflow gaps within one business day.
Week 2: 50% review

Routine cases run automatically with daily spot checks.

Target: Zero unresolved version conflicts by Day 14

  • Sample at least 10 live runs per day across high-volume paths.
  • Confirm logs, notifications, and downstream systems stay in sync.
Week 3+: Autonomy gate

Autonomous for standard cases, with weekly QA review.

Target: Zero unresolved critical failures for five business days.

  • Review weekly KPI trendline with the client owner.
  • Keep an escalation audit trail for policy or playbook updates.
Go-live criteria
  • >=95% workflow-state accuracy in Week 1
  • Zero unresolved version conflicts by Day 14
  • No unresolved integration failures for five business days.
  • Client approves tone, guardrails, and escalation routing.
Deployment Timeline

Day 1-30 rollout plan

day1-7Phase 1: Guided launch
Human review on every action

Focus

  • Mirror the current content workflow in shadow mode for active assets.
  • Tune state definitions, reminder timing, and version naming rules.
  • Validate canonical asset tracking against PM expectations.

Monitoring

  • Daily Grove QA review with client owner feedback.
  • Track integration failures, misfires, and missing knowledge-base coverage.

Exit criteria: PM agrees the AI state matches reality across a live asset sample.

day8-14Phase 2: Limited autonomy
Routine paths run automatically with spot checks

Focus

  • Let the AI send reminders and weekly digests automatically.
  • Keep final-approval and version-conflict handling in human review.
  • Measure overdue asset count and client reminder responsiveness.

Monitoring

  • Daily KPI snapshot plus escalation-rate review.
  • Tighten fallback logic for the top two failure modes.

Exit criteria: Overdue follow-up is reliably automated without version confusion.

day15-30Phase 3: Trusted operator
Autonomous for standard work with weekly QA

Focus

  • Run autonomously for standard review and reminder flows.
  • Review on-time delivery and client response lag weekly.
  • Expand the playbook to cover more revision patterns.

Monitoring

  • Weekly operating review with KPI trends and prompt updates.
  • Escalation audit for policy changes, edge cases, or training gaps.

Exit criteria: PM admin time stays low while on-time delivery holds near the 95% target.

Build Estimate

Implementation scope and prerequisites

Estimate snapshot

Hours: 10-18 hours

Phase: Phase 2

Complexity: medium

Medium-complexity build because the workflow logic is manageable, but version control and reviewer state must be designed carefully.

Dependencies
  • Canonical content-stage model
  • Docs and file metadata access
  • Reminder channels for clients and team
  • PM escalation owner
Owner inputs
  • Required stages and SLA for each stage
  • Naming/versioning rules
  • Which changes count as scope escalation