Outreach system
AI Operations Outreach Kit
A repeatable LinkedIn and conversation system for turning practical operations content into workflow bottleneck conversations without selling deep technical complexity.
What this enables
Weekly Operating Cadence
The goal is steady conversation creation: publish useful thinking, show up in relevant threads, then qualify workflow pain through questions.
Monday
Publish
Post one practical workflow problem from the current AI Operations Note and end with a diagnostic question.
Tuesday
Comment
Leave five useful comments on posts from operators, founders, recruiters, and service business leaders.
Wednesday
Connect
Send focused connection requests to people who engaged with related operational problems.
Thursday
Conversation
Reply to new connections with a thank-you, a specific observation, and one workflow question.
Friday
Diagnose
Invite qualified conversations to find their workflow bottleneck or book a short workflow consultation.
12-Week Outreach Campaign
Each week uses one AI Operations Note as the source for a post, comments, outreach question, and diagnostic CTA.
Week 1
Workflow selection
AI projects stall when the first decision is the tool. The better first decision is the workflow. Which repeated task costs attention every week, has a clear owner, and can be measured before and after?
Look for posts about workflow selection and add one concrete question about ownership, handoffs, measurement, or data quality.
Where do you see the most manual drag in your current operations: intake, follow-up, reporting, scheduling, or something else?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 2
Operations audit
The best automation candidates are rarely dramatic. They are the repeated operational tasks that quietly steal time every week. Look for copying, chasing, checking, and reformatting.
Look for posts about operations audit and add one concrete question about ownership, handoffs, measurement, or data quality.
What is one workflow your team repeats every week that still depends on copy-paste or manual follow-up?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 3
Pilot selection
A good first automation is not the biggest problem in the company. It is the smallest useful workflow where the team can prove value, learn safely, and expand from evidence.
Look for posts about pilot selection and add one concrete question about ownership, handoffs, measurement, or data quality.
If you had to automate one narrow workflow in the next 30 days, what output would prove it was worth doing?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 4
Handoff mapping
Automation fails when the handoff is fuzzy. Before adding AI, map where work changes hands, what information must travel with it, and who decides when it is complete.
Look for posts about handoff mapping and add one concrete question about ownership, handoffs, measurement, or data quality.
Where does work most often slow down when it moves from one person or team to another?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 5
Customer and candidate intake
Intake automation works when the team already knows what a good intake looks like. Standard fields, routing rules, and follow-up timing matter more than the model choice.
Look for posts about customer and candidate intake and add one concrete question about ownership, handoffs, measurement, or data quality.
How does your team currently know whether a new request is complete, qualified, and ready for the next step?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 6
Recruiting operations
In recruiting operations, AI should not replace judgment first. It should reduce the admin drag around matching, summarizing, routing, and follow-up so recruiters spend more time on real conversations.
Look for posts about recruiting operations and add one concrete question about ownership, handoffs, measurement, or data quality.
Where does your recruiting workflow lose the most time: matching, notes, follow-up, scheduling, or status visibility?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 7
Reporting and coordination
The problem is not that your team uses spreadsheets. The problem is when the spreadsheet becomes the only operating system for status, ownership, and next action.
Look for posts about reporting and coordination and add one concrete question about ownership, handoffs, measurement, or data quality.
Which spreadsheet would create the most disruption if the one person who maintains it took a week off?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 8
Ownership and governance
Automation without ownership becomes another system to babysit. Before building, decide who owns the rules, who reviews exceptions, and who changes the workflow when reality changes.
Look for posts about ownership and governance and add one concrete question about ownership, handoffs, measurement, or data quality.
For the workflow you most want to improve, who owns the rules and who handles exceptions today?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 9
Data readiness
Your data does not need to be perfect before AI can help. It needs to be clean enough for the specific workflow decision you want to improve.
Look for posts about data readiness and add one concrete question about ownership, handoffs, measurement, or data quality.
Could your team pull five good examples and five messy examples of the workflow you want to automate?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 10
Human review design
The first AI win does not have to be full autonomy. In many operations, the practical win is a better draft, cleaner routing, faster summary, or smarter recommendation with human approval.
Look for posts about human review design and add one concrete question about ownership, handoffs, measurement, or data quality.
Which step in your workflow would you be comfortable automating first: draft, route, summarize, recommend, or act?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 11
Business case
Do not price automation by how interesting the technology is. Price it by the operational value it creates: time saved, errors reduced, capacity unlocked, or revenue protected.
Look for posts about business case and add one concrete question about ownership, handoffs, measurement, or data quality.
What would one hour per week saved across that workflow be worth to your team over a quarter?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Week 12
Operating cadence
The goal is not one AI pilot. The goal is a cadence for finding operational drag, fixing one workflow, measuring the result, and choosing the next improvement from evidence.
Look for posts about operating cadence and add one concrete question about ownership, handoffs, measurement, or data quality.
After a workflow improvement goes live, what metric would tell you whether it should be expanded or left alone?
If this workflow is active, invite the person to find the bottleneck with the Recruiting Workflow Diagnostic and compare the result to their current priority list.
Strategic commenting
Comment to diagnose, not to promote.
The comment strategy should make the operational problem clearer before mentioning a tool, diagnostic, or call.
Name the hidden workflow
When someone complains about AI adoption, identify the underlying operational workflow before mentioning tools.
Add a diagnostic question
Ask about frequency, handoffs, owner, data quality, or measurement so the comment creates a real conversation.
Offer a narrow next step
Suggest mapping the trigger, output, review point, and metric before building an automation.
Outreach Templates
Use these as starting points, then personalize with the person, company, post, or workflow context.
New connection opener
Thanks for connecting, {firstName}. I noticed your work around {specificContext}. Curious: where does manual follow-up or reporting create the most drag for your team right now?
Comment follow-up
Your point about {topic} stood out. I see that show up a lot when teams try to add AI before the workflow is clear. Is that something your team is actively working through?
Diagnostic invitation
That sounds like a good candidate for the Recruiting Workflow Diagnostic. It shows whether a recruiting bottleneck is automation-ready, needs cleanup first, or should stay human-led. Want me to send it?
Soft close
Based on what you described, the next useful step is probably not a broad AI strategy session. It is a 20-minute look at one workflow to decide whether it is worth automating now.
Qualification Signals
Invite someone into the diagnostic when the conversation points to real workflow pain, ownership, and repeatability.
The handoff into sales is consultation.
When a qualified workflow emerges, the next step is not a pitch. It is a short workflow consultation to understand the process, decide whether automation fits, and name the smallest useful next move.