Exclusive workshop for Amazon operators
I Replaced My PPC Team With AI. Here's How.
Live webinar for Amazon brands on the exact AI workflows Chad Rubin uses to catch wasted spend, spot pricing and inventory issues early, and wake up to a prioritized morning brief.
- What AI should handle before you open Ads Manager
- The guardrails that keep humans in control
- The practical hacks you can steal right away
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Wednesday, April 22 • 1:00 PM EDT • Eastern Time
Overnight proof
What got done before I opened Ads Manager
Before the day started, the system had already caught waste, used a pricing window, reduced spend on inventory risk, flagged reimbursement dollars, and delivered the morning brief.
# overnight-actions
Five coordinated actions finished before the day started.
2:13 AM
MarkoWasted spend got caught and paused
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2:13 AM
MarkoWasted spend got caught and paused
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What happened
Marko paused "hepa filter replacement" and three related terms after 14 days, 0 sales, and $84 in wasted spend.
Why it mattered
Budget stopped leaking before the next workday and spend could be redirected into terms that were still converting.
Why a human sees it later
A human usually catches this after pulling the search term report later in the day or at the end of the week.
3:07 AM
OracleA competitor pricing window got used fast
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3:07 AM
OracleA competitor pricing window got used fast
Open details
What happened
Oracle detected a competitor stock-out on B09XK7 and raised price from $28.99 to $33.99 while the market had room.
Why it mattered
That captured margin immediately instead of waiting hours for someone to notice the opportunity in a pricing report.
Why a human sees it later
A human usually sees this after the competitor is already gone and the best pricing window has narrowed.
4:12 AM
BrunoInventory risk changed PPC before a stockout spiral
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4:12 AM
BrunoInventory risk changed PPC before a stockout spiral
Open details
What happened
Bruno surfaced an SKU with 11 days of cover left and triggered a 20% bid pullback across the campaigns pushing that item hardest.
Why it mattered
It protected inventory, reduced wasted clicks on a constrained SKU, and helped preserve ranking instead of selling the business into a tighter corner.
Why a human sees it later
A human usually catches this after inventory and PPC are reviewed separately, which is often after the risk is already more expensive.
5:04 AM
NestorA reimbursement opportunity did not sit in a queue
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5:04 AM
NestorA reimbursement opportunity did not sit in a queue
Open details
What happened
Nestor flagged a lost inbound shipment and queued the reimbursement claim with an estimated $312 recovery.
Why it mattered
That turns a buried ops issue into recovered dollars instead of letting it disappear into reconciliation work nobody gets to this week.
Why a human sees it later
A human usually finds this during a later audit, if it gets reviewed at all.
6:30 AM
ClaudiaThe morning brief showed the work already done
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6:30 AM
ClaudiaThe morning brief showed the work already done
Open details
What happened
Claudia sent a summary of the overnight actions, the financial impact, and the one exception that still needed judgment.
Why it mattered
Chad started the day with decisions, not detective work.
Why a human sees it later
A human usually pieces this together after opening multiple dashboards and Slack threads once the day is already underway.
One Tuesday. Multiply by the year.
Morning brief
6:30 AM morning brief
By 6:30 AM, the money leaks and exceptions were already surfaced. The human starts with judgment, not dashboard cleanup.
Wasted spend stopped
$84 paused
Margin window captured
+17% lift
Reimbursement found
$312 flagged
Before breakfast
- Wasted spend caught and paused
- Pricing window detected and used
- Inventory risk surfaced before it got expensive
- Reimbursement dollars flagged
- Morning brief delivered before the workday started
Why it converts
- Waste is stopped before the day burns budget.
- Only the exceptions worth judgment need human review.
- PPC, pricing, inventory, and ops move together instead of in silos.
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See the full operating system live.
Register for the walkthrough and Chad will show the workflows, guardrails, and rollout path behind these overnight actions.
Date
Wednesday, April 22
Time
1:00 PM EDT
Time zone
Eastern Time
Format
Live only
Free live webinar • No replay • Live Q&A
What you'll leave with
Practical takeaways you can use right away.
This webinar should still be useful even if you never buy anything. The point is to leave with a cleaner operating model for where AI helps, where it needs limits, and what to apply first.
Use cheaper models for routine work
Use low-cost models for monitoring, formatting, and first-pass analysis. Save the expensive reasoning for decisions that actually move margin, bids, and inventory.
Give AI instructions that do not drift
Move the core rules and operating context out of one-off prompts so the system does not reset every time a new chat starts.
Add memory, approvals, and simple rules
A little structure makes AI usable fast: remember what happened, require approval on risky moves, and put simple rules around the business-critical edges.
Know when PPC is not the real problem
Learn how to tell when the real issue is price, inventory, or listing quality so you stop trying to solve every bad outcome with bids.
Start using AI without a science project
Pick narrow, repeatable work that helps today so AI reduces operator load now instead of turning into another long internal build.
Why this works
Most teams use AI for content. Very few use it for work.
The difference is not a smarter model. It is memory, guardrails, cross-functional context, and a clear trust model for what AI can do alone versus what still needs a human.
Persistent instructions and memory
The system carries forward rules, context, and recent decisions so every new run does not start from zero.
Guardrails and approvals
Low-risk work can move fast. High-stakes actions still wait for a human before money, price, or inventory decisions get pushed live.
Cross-functional context
PPC is not treated like an isolated dashboard. Pricing, listing quality, inventory, and ops all affect what the system should do next.
Graduated trust
You do not hand everything to AI on day one. You start with narrow jobs, prove the signal, then expand the lane once the output is reliable.
Why listen to Chad
Built it. Sold it. Still in the trenches.
Chad Rubin
Founder & CEO, Profasee
Chad Rubin built and sold three companies, still runs an 8-figure Amazon brand, and is showing the same operating logic he uses in the real world. This is operator proof, not conference-theory AI.
Companies built and sold
3
Amazon brand still in-market
8-figure
System you will see live
Hackathon-winning
- Built and sold 3 companies, including exits to public companies and private equity
- Still runs Think Crucial, an 8-figure Amazon brand, in the trenches
- Showing the same workflows live, not a demo built just for the webinar
Questions before you register?
Straight answers before you commit the hour.
No. This is built around practical operator workflows: what gets automated, what still needs a human, and how the guardrails work in the real world. The goal is tactical leverage, not AI entertainment.
It is built for Amazon operators, founders, and PPC leaders. If that is your world, it will land. If you are outside Amazon, some of the logic still applies, but the examples are operator-specific.
Real workflows. You will see how the system catches wasted spend, reacts to pricing and inventory signals, and hands a human the right morning decisions instead of a pile of dashboards.
No. This session is live only. No replay, no recording. If you want the material, plan to be there live.
Final call
Reserve my seat
Live webinar. Practical AI workflows for Amazon brands. No replay. Live Q&A.
Wednesday, April 22 • 1:00 PM EDT • Eastern Time
Free live webinar
Wednesday, April 22 • 1:00 PM EDT • Live only