One product. Three tiers. The system behind managing 19 Google Ads brands from a single terminal.
19 brands. One terminal. Zero headcount added.
The Google Ads AI Agentic System is the architecture, the curriculum, and (if you want it) the production codebase behind a system currently managing 19 brands across $30M+ in Google Ads spend. Three tiers, one decision: how much do you want already built? The **Blueprint** gives you the full 20-module build guide. The **Blueprint + Agent Codebase** adds the 24-command core system. The **Blueprint + End-to-End Codebase** ships the entire 75-command production system - operational in days, not months.
For agency operators who stopped believing hiring solves the scale problem.
Tier-Appropriate GuaranteesSecure checkout via StripeLifetime access
The pattern is familiar to anyone who has run an agency past five accounts. Execution scales linearly with headcount, but margins do not. Feed rewrites take a full day per client. Landing pages get deprioritized because nobody has the hours. Competitive intel becomes something the team does "when there's time" - which translates to never. Reporting is stitched together from four dashboards and delivered late.
We lived this at 8 accounts. Tried hiring - margins compressed, training took 6 months, quality varied by who managed which brand. Tried SaaS tools - Optmyzr, Adalysis, three others - each solved a piece, none of them generated feed titles, built landing pages, created demand gen creative, or connected to Shopify inventory. The industry keeps offering incremental fixes to a structural problem. The bottleneck is not strategy. It never was. The bottleneck is orchestrating Shopping feeds, Search RSAs, landing pages, creative assets, competitive intelligence, and reporting - simultaneously, across multiple brands - without proportional headcount.
> We spent two years trying the obvious fixes before we accepted the real answer: manual execution does not scale linearly, and headcount growth does not either. This system exists because we built the system we could not buy.
The Build-vs-Buy Question
Choose Your Implementation Depth
Category
Blueprint
Blueprint + Agent Codebase
Blueprint + End-to-End Codebase
Price
$4,997
$9,997
$19,997
Curriculum
Full 20 modules
Full 20 modules
Full 20 modules
Codebase
Architecture docs only
24-command core project
75-command full system
Commands
Architecture + command maps
24 implemented
75 implemented
Python Utilities
Patterns documented
86 production-ready
188 production-ready
Custom Skills
None
6
31
Pipelines
Build guides for all 8
Shopping, Search, Presell
+ Demand Gen, Offer, Intel, Workflow Control
JSON Schemas
Reference specs
33
35 + 16 data contracts
Creative Themes
Design references
Basic set
27+ (10 presell, 10 image, 7 offer)
Eval Harness
Architecture only
Not included
11-command quality system
n8n Workflows
Import-ready templates
Import-ready templates
21 production workflows
Time to operational
5-7 days
2-3 days
1-2 days
Best for
Technical builders
Core operators
Full-scale agencies
Upgrade path
+$5,000 to Agent / +$15,000 to End-to-End
+$10,000 to End-to-End
--
How This Compares to Alternatives
Alternative
Cost
Timeline
Scope
Ownership
AI automation agency (custom build)
Enterprise AI development
SaaS tools (Optmyzr, Adalysis, etc.)
Google Ads scripts
AI training programs (AAA Accelerator, etc.)
The Google Ads AI Agentic System
The Three-Phase AI Agency System
Step 1
ARCHITECT
(Infrastructure) - Build the foundation before a single ad gets optimized. Claude Code workspace with slash commands and skills. GCP project with 7 Google APIs enabled and OAuth2 configured. Python client library wrapping 8 external APIs (DataForSEO, Brave Search, OpenAI, Google GenAI, video generation, audio/TTS, Meta, Firehose). Multi-brand data architecture with 16 JSON contracts, 35 schemas, and 20+ reusable frameworks. Brand onboarding pipeline that takes a new client from zero to research-complete in a single command - 24 phases, 21 DataForSEO queries, 380-620 unique angles per brand. By the end of Phase 1, the infrastructure works. Every subsequent module builds on it.
Step 2
GENERATE
(Pipelines) - Build eight production pipelines that take raw inputs and produce deployable assets. Shopping Feed: 7-command chain from raw feed to optimized campaigns with 152-point validation. Presell Pages: 13-command chain from product discovery to deployed landing pages with PMax campaigns. Search Ads: RSA creation with 3-per-cluster architecture and 45 headlines per set, plus 17-phase competitive intelligence pipeline. DG Image: multi-model image generation (GPT Image, Gemini, Imagen) with Cooper Framework. DG Video: AI video generation with script-to-render pipeline and YouTube upload. Offer Pages: bundle strategy with native Shopify deployment. Creative Themes: automated theme extraction and variant testing. Product Discovery: catalog-wide opportunity detection and angle scoring. Each pipeline runs end-to-end. Output of one command feeds the input of the next.
Step 3
EXECUTE
(Autonomy) - Close the loop. Unified reporting across Shopping + Search + Presell + PMax + Demand Gen + GSC organic. Autonomous optimization with append-only knowledge base that captures every winning and losing decision. Shopify inventory sync (real-time + daily batch). n8n orchestration brain - 21 workflows across three layers: monitoring (anomaly detection, budget pacing), intelligence (competitor tracking, search trend triggers), and action dispatch (automated pipeline runs). Workflow control with AutoResearch quality system for autonomous research loops. Account lifecycle management from onboarding through scaling. Portfolio-level health management with cross-brand learning propagation across 19 brands. Production hardening with preflight checks, credential rotation, and error handling.
How This System Came to Exist
Three years ago, our agency was managing 8 Google Ads accounts and struggling. Not with strategy - the frameworks were solid. The problem was execution at scale. Every feed rewrite was a spreadsheet marathon. Landing pages were a luxury nobody had time to build. Competitive intel happened once a quarter when someone remembered. Reporting ate entire afternoons every week.
We tried hiring. Margins compressed. Training took 6 months. Quality varied by who was managing which account.
We tried SaaS tools. Optmyzr, Adalysis, three others. Each one solved a piece. None of them generated feed titles, built landing pages, created demand gen creative, or connected to Shopify stores. We were paying $800-2,500/month per tool and still doing 80% of the work manually.
So we built it ourselves. Not a tool. Not a dashboard. A system. Started with the feed pipeline - a chain of CLI commands that could rewrite an entire product feed with 152-point quality validation. Then presell pages, search ads, competitive intel, demand gen creative, offer pages. Took 14 months to get it right. Some commands were rewritten 4-5 times before they were production-grade.
The result: 19 brands managed from a single terminal. 30 minutes of monitoring per day instead of 3+ hours per account per week. New clients onboarded in hours, not weeks.
Then we documented it. 72,000 words across 20 modules became the Blueprint - the complete build guide. But we kept hearing the same feedback: "I do not want to build it. I want to run it."
So we stripped the credentials, removed the brand data, and packaged what already existed. The Agent Codebase ships the core 24-command system for operators who want the main pipelines running fast. The End-to-End Codebase ships all 75 commands, all 189 utilities, all 31 skills - the full production system with a deployment guide instead of a build curriculum.
We built it, documented it (Blueprint), packaged the core system (Agent Codebase), and now ship the full production system (End-to-End Codebase). Same architecture at every tier. Different starting lines.
What Ships Per Tier
All tiers receive the 20-module curriculum - the complete Three-Phase AI Agency System covering 8 production pipelines, data architecture, API integrations, orchestration, and multi-brand operations.
Blueprint ($4,997) ships the curriculum, architecture documentation, command maps, workflow documentation, all templates, and the core bonuses. Everything needed to build the system from the ground up.
Blueprint + Agent Codebase ($9,997) adds the core production codebase: 24 slash commands, 86 Python utilities, 5 custom skill folders plus the skill-routing layer, 33 JSON schemas. Shopping Feed, Search Ads, Presell Pages, brand onboarding, reporting, image generation, and research - implemented, tested, ready to configure and run.
Blueprint + End-to-End Codebase ($19,997) adds the complete production system: 75 slash commands, 189 Python utilities, 31 custom skills, 35 JSON schemas, 16 data contracts, 27+ creative themes, 11-command eval harness, 21 n8n production workflows, and the Firehose Intel microservice. Every pipeline. Every automation layer. Every operational tool. Plus a 10-module deployment guide for going live in 1-2 days.
Before and After
Before
| Blueprint Builder
**Starting point**
**Week 1**
**Week 4**
**Month 3**
**Time to first output**
**Total build/deploy time**
**Skills needed**
**What you own**
After
Agent Codebase Deployer | End-to-End Operator
Full architecture docs + build guide | 24 working commands + build guide | 75 working commands + deployment guide
Environment setup, GCP configured | Environment setup, first pipeline running | Full system configured, first brand live
First pipeline built and tested | Core pipelines operational, customizing | 3+ brands running, knowledge base growing
Full system operational on pilot brand | Extended system with custom additions | Portfolio at scale, 15 min/day management
3 weeks (after infrastructure) | 3-5 days | 1-2 days
Everything - you built every line | Core system + everything you extend | Complete production system
What Each Tier Looks Like in Practice
Blueprint buyer, 90 days from now:
The system is built. Not downloaded - built. Every command, every utility, every schema written by hand following the curriculum. The understanding runs deep because there is no black box. When an API changes or a pipeline needs a new capability, the modification takes hours, not days - because every architectural decision was made consciously. The pilot brand is running all 8 pipelines. The second brand is onboarding. And the system reflects how the operator thinks, not how someone else designed it.
Agent Codebase buyer, 30 days from now:
The core pipelines are running on two brands. Shopping feeds optimized with 152-point validation. Presell pages deployed with PMax campaigns converting. Search RSAs live with competitive intelligence informing every generation. The first month was spent configuring, customizing, and extending the 24-command base - not writing it from scratch. Now the operator is building the demand gen and offer page layers on top of a foundation that already works.
End-to-End Codebase buyer, 7 days from now:
The first brand is live. Every pipeline operational. Shopping feed uploaded to Merchant Center. Search RSAs deployed. Presell pages converting. Demand Gen creative running across YouTube, Gmail, and Discover. The morning check takes 15 minutes - the n8n monitoring layer catches anomalies before anyone does. By week two, the second brand is onboarding. By month one, the portfolio is growing. The system gets smarter with every brand because the knowledge base propagates learnings across the entire portfolio.
All 20 Modules
Three Timelines, One System
Choose Your Tier - From $4,997
The curriculum is the same. The difference is how fast the system is running.
20 modules. 8 pipelines. Full curriculum at every tier. Codebase tiers ship production-tested code. Cross-upgrade available - pay the difference anytime.
Tier-Appropriate GuaranteesSecure checkout via StripeLifetime access
Included Bonuses
Value: $1,997
Bonus 1: Command Reference Manual
Every command in the system documented: arguments, expected inputs, expected outputs, chain position, verification checkpoints, common errors, and example invocations. Blueprint buyers use it as the build reference. Codebase buyers use it as the operational manual.
Value: $997
Bonus 2: n8n Workflow Templates - 21 Workflows
Import-ready workflow JSONs for n8n. Monitoring workflows (budget pacing, anomaly detection). Intelligence workflows (competitor tracking, trend triggers). Action dispatch workflows (pipeline triggers, notifications). Import, connect to APIs, and the orchestration layer is live.
Value: $597
Bonus 3: Creative Theme Library
91+ presell themes, 23 image themes, and 5 video themes. Mobile-first design. Fast-loading (under 2s on 3G). Themes span awareness levels: educational, comparison, problem-solution, testimonial-driven, and product-focused. Drop into the presell pipeline and landing pages look professional without design work.
Value: $1,997
Bonus 4: Command Center Agent Spec
Level 3 system agent specification for multi-pipeline coordination. The agent understands all commands, all pipelines, and the orchestration layer. Route tasks to the right pipeline. Maintain cross-brand context. Query the knowledge base. Debug pipeline failures. One agent interface that ties the entire system together.
### Agent Codebase + End-to-End Codebase Add (3 Bonuses)
Value: $2,997
Bonus 5: 75-Command Operational Reference
The deep-dive reference for every command in the production system. Beyond the standard reference manual - this includes chain position logic, error recovery patterns, cross-command dependencies, and production edge cases documented from running the system across 19 brands. (The reference covers all 75 commands regardless of tier - Agent Codebase buyers get the full reference to guide their extension work.)
Value: $1,997
Bonus 6: Pipeline Decision Flowcharts
Visual decision trees for all 8 major pipelines. Standard Shopping vs PMax vs Thief/Protector? Cloudflare vs Shopify? Which image model for which creative type? Every operational judgment call mapped as a branching flowchart. Printed and taped next to the monitor by more than one buyer.
Value: $1,497
Bonus 7: API Cost Optimizer
Cost-per-call analysis across all 12+ APIs. Monthly projections at 3, 5, 10, and 20 brand scale. Image and video model cost comparison. Optimization strategies including the 90-day keyword cache that saves 85% on DataForSEO calls.
One product with three tiers, not three separate products
Built from a system currently managing 19 brands across $30M+ in spend
20 modules that produce working infrastructure, not theoretical knowledge
A Blueprint (build guide), an Agent Codebase (core system), or an End-to-End Codebase (full production system) - depending on tier
Code patterns, API architectures, workflow templates, and data contracts you own forever
A CLI-based system that runs in Claude Code
A one-time purchase with lifetime updates at every tier
What This Isn't
Cross-upgradeable - pay the difference between tiers anytime
Three separate products (it is one offer with three implementation depths)
A Google Ads strategy course (the assumption is that the buyer already knows Google Ads)
A SaaS platform or hosted dashboard (the buyer owns and runs the system)
A plug-and-play solution requiring zero technical knowledge (terminal comfort is required)
A guarantee of specific results (outcomes depend on execution and account quality)
Is This For You?
This is for you if:
You manage 3+ Google Ads accounts and the execution is not scaling with the portfolio
You understand Google Ads at an intermediate or advanced level
You are comfortable working in a terminal and can read Python code
You want to scale to 10-20+ accounts without proportional headcount growth
You see AI as infrastructure to build, not a chatbot to prompt
You have (or are willing to set up) Google Cloud, Merchant Center, and API accounts
Which tier fits:
Blueprint if you are a technical builder who wants to understand every layer and rebuild the system internally. 5-7 day setup commitment. Python and API experience strongly preferred.
Agent Codebase if you want the core pipelines (Shopping, Search, Presell) running in 2-4 weeks and plan to extend from there. Terminal comfort and configuration skills required.
End-to-End Codebase if you want the full system operational in days. Managing multiple brands already. The investment is in speed - the $19,997 buys back 83 days of build time worth $74,700+ at $900/day operator cost.
This is NOT for you if:
You are still learning Google Ads fundamentals
You have never used a terminal or command line
You want a visual dashboard instead of a CLI system
You manage fewer than 3 accounts (the ROI math does not justify the investment at any tier)
You want someone to build it for you (ask about DFY implementation services instead)
The Alternatives, Mapped Out
Alternative
Cost
Timeline
What You Get
What You Do Not Get
Hire a systems architect
$150K-$300K+
6-12 months
Custom build, your specs
Domain expertise. They can code but do not know Google Ads at the pipeline level. Uncertain outcome.
AI automation agency
$10K-$50K/project
2-6 months
One use case built
Multi-pipeline orchestration. You get a chatbot or single workflow, not an 8-pipeline system.
Enterprise AI development
$80K-$200K+
6-12 months
Custom multi-agent system
Speed. At this budget and timeline, the system described here ships faster for less.
SaaS tools (Optmyzr, etc.)
$2.5K-$10K/year (ongoing)
Immediate
Dashboard automation
Ownership. Feed generation. Landing pages. Creative. Knowledge base. When you cancel, the system disappears.
Production code. API integrations. Data contracts. The difference between prompting a chatbot and deploying infrastructure.
Claude Code docs + DIY
Free + 14 months
Trial and error
Raw documentation
Domain-specific architecture. Google Ads pipeline design. Production patterns. The 14 months of iteration already completed.
The Google Ads AI Agentic System
$4,997-$19,997 once
Days to 90 days
Full system - curriculum, architecture, and (optionally) production codebase
Requires terminal comfort and Google Ads expertise.
Three Pipelines, Three Proof Points
The Feed Pipeline (2.1x ROAS Improvement)
An e-commerce brand, 2,400 SKUs across 3 markets. Generic feed titles - manufacturer descriptions copied into the title field. 31% impression share. Feed updates done manually in spreadsheets, which meant they happened maybe once a quarter.
The 7-command Shopping Feed pipeline changed the workflow completely. `feed-segment` grouped products by margin and velocity. `feed-rewrite` generated Zone Architecture titles - keyword-first structure in the 0-70 character zone, modifiers in 71-110, long-tail qualifiers in 111-150. Every title individually written by the LLM (no templates, no find-and-replace). 152-point validation scored each title and auto-fixed formatting issues.
Six weeks from pipeline build to full deployment. Impression share went from 31% to 67%. ROAS improved 2.1x. Feed updates that used to take a full day now run in minutes per segment. Monthly incremental revenue from feed improvements alone: $8K.
The Presell Pipeline (2x Conversion Rate)
A DTC supplement brand with 12 hero products. All traffic going direct to product detail pages. 1.8% conversion rate. No landing pages - the team considered them a "nice-to-have" they never had time to build.
The 13-command Presell Pages pipeline turned "we do not have time" into "it takes 30 minutes." 4 highest-potential products identified. 3 angle variants per product using Emotional Truth Extraction. Responsive HTML deployed to Cloudflare Pages. PMax campaigns created pointing to the new pages.
Three weeks from discovery to deployment. 12 landing pages live. Presell traffic conversion rate: 3.7% (vs 1.8% on PDPs). PMax campaigns: 4.2x ROAS. Monthly incremental revenue: $22K.
The Multi-Brand Scale (3 New Clients, Zero New Hires)
An agency managing 4 brands manually. Owner plus one account manager. Hitting the wall at 15+ hours per week across 4 accounts. Two clients lost the previous year due to quality drops. Three prospects turned away because there was no capacity.
Built the full system over 90 days. Migrated existing 4 brands. Onboarded 3 new clients using the 24-phase brand-onboard pipeline. Each new brand took hours instead of the previous 2-3 weeks.
Result: 7 brands managed in 3 hours per week total. 3 additional clients at $5K/month average retainer. Zero additional headcount. Annual impact: $180K in new client revenue + $120K in retained clients (zero capacity-related churn). Total: $300K/year.
20-module curriculum (Three-Phase AI Agency System)
Consulting engagement | $15,000
10-module operational deployment guide
Implementation consulting | $10,000
6 templates
Planning and operational tools | $1,200
BonusBonus 1: Command Reference Manual
Technical documentation | $1,997
BonusBonus 2: n8n Workflow Templates
Automation build | $997
BonusBonus 3: Creative Theme Library
Frontend development | $597
BonusBonus 4: Command Center Agent Spec
Agent architecture consulting | $1,997
BonusBonus 5: 75-Command Operational Reference
Deep operational docs | $2,997
BonusBonus 6: Pipeline Decision Flowcharts
Workflow consulting | $1,997
BonusBonus 7: API Cost Optimizer
Cost engineering analysis | $1,497
End-to-End Codebase price
| $19,997
Value multiple
| 28.1x
Total Value$21,588
$0
Tier-Appropriate Guarantees
### Blueprint: 90-Day Build-and-Test Guarantee
Build Phase 1 (Modules 1-5). Get the infrastructure live. Run the brand onboarding pipeline on the first client. When the pipeline produces a research baseline more comprehensive than what is currently built manually - keyword universe, competitive landscape, audience angles, product analysis - the system works. And it will, because every module has verification checkpoints that prove it before moving to the next.
90 days because Phase 1 takes 2-3 weeks, and there should be enough time to build without rushing. Most buyers know within the first week whether the architecture fits their workflow.
Either the system produces better infrastructure than the manual process - making it the best investment of the year - or a full refund is issued. The bonuses are kept either way.
Deploy the system on one brand within 30 days. Run `/brand-onboard` and at least one pipeline end-to-end. Either the system produces exactly what the operational guide describes - optimized feeds, generated ads, deployed pages - and it pays for itself within months. Or it does not, and the full purchase price is refunded.
Both outcomes are worth the 30 days. If the system works, the infrastructure compounds from day one. If it does not work for a particular setup, the buyer walks away with zero financial risk and a clear answer. This guarantee is offered confidently because the system is already running across 19 production brands.
Frequently asked questions about The Google Ads AI Agentic System
Choose Your Tier
One product. Three implementation depths. The architecture behind managing 19 brands and $30M+ in spend from a single terminal.
One-time purchase. Lifetime updates. Cross-upgrade available anytime - pay the difference between tiers.
Tier-Appropriate GuaranteesSecure checkout via StripeLifetime access
The Google Ads AI Agentic System$4997Tier-Appropriate Guarantees
“We went from 'nothing we try works anymore' to a system we actually trust. The research phase alone changed how we think about ad copy. Should have done this years ago.”
— Daniel K., Marketing Director, Supplements Brand, $45K/mo ad spend
“The audit workflow blew my mind. What used to take me half a day now takes less than 10 minutes. And the output is more thorough than what I was doing manually.”
— Priya S., PPC Manager, Fashion E-commerce, $32K/mo ad spend
“Competitors were outranking us everywhere. The research workflows found angles we had never considered - pulled straight from customer reviews we had not read. CTR up 38% in 6 weeks.”
— Sarah L., Head of Growth, Pet Products, $28K/mo ad spend
“This is not a prompt library. It is an operating system. The context-loading alone is worth 10x the price. My AI outputs went from 'sounds like AI' to 'sounds like our brand' overnight.”
— Anika R., Performance Marketer, Food & Beverage Brand, $22K/mo ad spend
“We were flying blind. Pasting product descriptions into ChatGPT and hoping for the best. The structured workflow approach was the proven framework we needed. It saved me weeks.”
— Tom H., E-commerce Director, Fitness Equipment, $55K/mo ad spend
“We bought the Blueprint first and spent three weeks on Phase 1. Then the codebase edition came out. Had the full system running in four days. The codebase alone saved us two months of build time.”
A service with ongoing support or implementation assistance (self-sufficient by design)
— Marcus T., Agency Owner, 7 Google Ads clients, $180K/mo managed spend
“The feed pipeline paid for the entire product on the first brand. 118 products rewritten and uploaded in one afternoon. Our previous workflow was two full days per feed refresh.”
— Rachel K., E-commerce Operations, DTC Supplements, $65K/mo ad spend
“I was skeptical about a five-figure digital product. Then I looked at what my team spent building a similar system last year - north of $120K in developer time and we only covered search and shopping. This covers everything.”
— James W., VP of Performance, Multi-brand Retailer, 12 brands
“The presell pipeline is what sold me. Twelve landing pages with PMax campaigns in a single session. We used to outsource landing pages at $2,500 each. The math was obvious.”
— Sofia M., Growth Lead, Beauty & Skincare, $42K/mo ad spend
“Not for beginners - you need to know your way around Google Ads and a terminal. But if you do, this is the closest thing to cloning an experienced agency's entire tech stack. The knowledge base alone keeps getting smarter with every run.”
— David P., Independent Consultant, 5 clients, $90K/mo managed spend
“We went from 'nothing we try works anymore' to a system we actually trust. The research phase alone changed how we think about ad copy. Should have done this years ago.”
— Daniel K., Marketing Director, Supplements Brand, $45K/mo ad spend
“The audit workflow blew my mind. What used to take me half a day now takes less than 10 minutes. And the output is more thorough than what I was doing manually.”
— Priya S., PPC Manager, Fashion E-commerce, $32K/mo ad spend
“Competitors were outranking us everywhere. The research workflows found angles we had never considered - pulled straight from customer reviews we had not read. CTR up 38% in 6 weeks.”
— Sarah L., Head of Growth, Pet Products, $28K/mo ad spend
“This is not a prompt library. It is an operating system. The context-loading alone is worth 10x the price. My AI outputs went from 'sounds like AI' to 'sounds like our brand' overnight.”
— Anika R., Performance Marketer, Food & Beverage Brand, $22K/mo ad spend
“We were flying blind. Pasting product descriptions into ChatGPT and hoping for the best. The structured workflow approach was the proven framework we needed. It saved me weeks.”
— Tom H., E-commerce Director, Fitness Equipment, $55K/mo ad spend
“We bought the Blueprint first and spent three weeks on Phase 1. Then the codebase edition came out. Had the full system running in four days. The codebase alone saved us two months of build time.”
— Marcus T., Agency Owner, 7 Google Ads clients, $180K/mo managed spend
“The feed pipeline paid for the entire product on the first brand. 118 products rewritten and uploaded in one afternoon. Our previous workflow was two full days per feed refresh.”
— Rachel K., E-commerce Operations, DTC Supplements, $65K/mo ad spend
“I was skeptical about a five-figure digital product. Then I looked at what my team spent building a similar system last year - north of $120K in developer time and we only covered search and shopping. This covers everything.”
— James W., VP of Performance, Multi-brand Retailer, 12 brands
“The presell pipeline is what sold me. Twelve landing pages with PMax campaigns in a single session. We used to outsource landing pages at $2,500 each. The math was obvious.”
— Sofia M., Growth Lead, Beauty & Skincare, $42K/mo ad spend
“Not for beginners - you need to know your way around Google Ads and a terminal. But if you do, this is the closest thing to cloning an experienced agency's entire tech stack. The knowledge base alone keeps getting smarter with every run.”
— David P., Independent Consultant, 5 clients, $90K/mo managed spend
Recent updates
LaunchApr 3Google Ads AI Agentic System — 3-Tier Agent Architecture