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Taylor Wells

Jordan Ross

You didn’t build your agency to spend your days buried in project management tools, stuck on Slack, or cleaning up your team’s mistakes.

But if you’re like most 7-figure founders, you’re trapped in what I call Agency Prison:

You’re still involved in client fulfillment

Team members lean on you to solve problems

Growth stalls every time you try to scale

You know what’s broken—but never have the time to fix it

You’re not underperforming—your infrastructure is.
And it’s costing you time, freedom, and compounding revenue.

Here’s how we help:
At 8 Figure Agency, we serve as your Done-For-You COO—
installing the operational infrastructure that removes you from day-to-day execution.

✅ Document your systems
We map every step of how your business runs—from onboarding to fulfillment—so your team knows exactly what to do, when, and how.

✅ Turn training into a conveyor belt
We don’t just write SOPs—we build a repeatable, scalable training engine.
Video walkthroughs. Benchmarks. Decision trees. Structured onboarding.
New hires move through like a conveyor belt—trained the same way, every time.
So your team performs consistently without needing hand-holding or shadowing.

✅ Clarify roles & ownership
No more overlapping responsibilities. Everyone on your team will know what they’re responsible for, how they’re measured, and what success looks like.

✅ Create performance visibility
You’ll get a dashboard that shows how every client and team member is doing—so nothing slips through the cracks.

✅ Build a high-accountability culture
We install weekly meetings where your team comes prepared—ready to report wins, challenges, and next steps. No more status updates. Just action.

We’ve helped over 1,000 agencies install systems that actually scale—without chaining the founder to daily execution.

If you’re:

The only one who can fix client issues

Stuck in strategy, delivery, and managing the team

Turning down growth because your backend can’t handle more

Sick of feeling like your business owns you

Then DM me “8FOS.”

Let’s build a business that runs without you.

Build the dream.
Not a prison.

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Getting your business financials should not be hard. We are putting an end to poor communication and poor service in the bookkeeping and financial world. 
We are the financial partner you deserve.

Fully agentic agency. Built on N8N. Seven figures in profit. 90 days.

I've seen it with my own eyes.

SEO + content + GEO services. $15K/month retainers. 95% margins.

They're not a unicorn.

They're the beginning of a trend.

And they're building in silence because they don't want competition.

They're going upstream first - selling 6-7 figure retainers to enterprise clients.

Eventually, they'll come downstream.

To your market.

With better margins. Better delivery. Better results.

If you're still manually delivering services, you won't compete.

The race is on.

Helping 7-Figure Agency Founders Escape “Agency Prison” | Scale from $100k/mo → $1M/mo | DFY Operating Systems | 1K + Agencies

A company came to us wanting AI development with 500+ clients but had zero centralized data infrastructure.

🛑 We had to stop the project immediately.

Here's what 3,000+ hours of building AI into agencies taught us ...

AI doesn't replace clean operations, it makes them absolutely critical.

AI only works on clean, structured, predictable data. Without that foundation, your models will hallucinate, guess, and create more problems than they solve.

Why we always build the stack first:
✅ Source of truth - CRMs, data warehouses, and standardized workspaces ensure every field is consistent across systems.
✅ Predictable workflows - Structured processes tell AI agents exactly what to do next, eliminating edge cases that break automations.
✅ Data validation - Every agent has clear goals with built-in checks that improve output quality over time.

When the stack is missing 📉
❌ Hallucinated records and mismatched customer entities
❌ Prompts become massive and expensive as you try to handle every edge case
❌ Impossible to track bugs or measure AI performance

Bottom line: AI amplifies whatever system it runs on. Clean data compounds into better results. Messy data compounds into bigger disasters.

Build the foundation first, then add the intelligence. 🏗️

How clean is your current data infrastructure on a scale of 1-10?

"Just drop everything in a vector database and it'll be magical."

🚫 Wrong.

If your AI engineer told you this, they don't know what they're doing.

Proper AI infrastructure requires FOUR types of databases:
⚡ Vector Database - For semantic search and sentiment analysis
⚡ Data Warehouse - For structured numerical data and analytics
⚡ Knowledge Graph - For building relationships between data points
⚡ Relational Database - For transactional data

Each serves a specific purpose.

When you ask a complex question like "What's the average LTV of my clients in the last 6 months and what's their sentiment on renewing?" - the system needs to:

→ Pull numbers from the data warehouse 
→ Grab sentiment from the vector database
→ Connect relationships via the knowledge graph 
→ Query transactions from relational DB

Then synthesize everything into one answer.

This isn't simple. But it's necessary for production-level AI.

Building with just one database type is like trying to build a house with only a hammer.

We're building a pyramid from the bottom up.

Foundation - Worker agents 👷
- Slack agent (reads messages)
- Asana agent (pulls tasks)
- CRM agent (grabs deals)

Middle: Workflow agents 🏄
- Account manager workflow (combines Slack + Asana + CRM)
- Training workflow (combines different data sources)
- Reporting workflow (aggregates performance)

Top: Role agents 🤖
- Full account manager role (delegates to workflows)
- Full project manager role (orchestrates multiple workflows)

Peak: Manager agents 👨‍💼 
- Oversees all roles
- Monitors performance
- Makes strategic decisions

You can't skip levels.

You can't jump straight to manager agents.

You build from the bottom.

One layer at a time.

Most agencies are trying to start at the top.

That's why they fail.

Which level are you actually ready to build, or are you still trying to skip straight to the top?

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Most agencies see the tip of the AI iceberg.

They build a few automations in N8N. They connect some tools. They think they're done.

Then they try to scale.

And everything breaks.

Here's what's hidden below the surface:
→ Production-ready architecture 
→ Proper database schemas 
→ Mass data ingestion pipelines 
→ Error handling and monitoring 
→ Context window management 
→ Hallucination prevention layers 
→ Model-agnostic infrastructure 
→ Security and access controls

The tip of the iceberg gets you to level one.

But if you need deep company knowledge, meaningful insights, and reliable outputs at scale...you need to build below the waterline.

Most agencies won't tell you this.

Because they're still at the tip.

🙅 Don't quit your agency because "AI's taking over."

Quit this instead…

❌ Quit pretending you can compete with other agencies without your own AI system.

Every new AI tool coming to market requires MCP connections. 

MCP (Model Context Protocol) is your private data hub that lets AI tools actually understand your agency's context, history, and processes. 

Think of it as the new Zapier for the AI era. But instead of just moving data between tools, it makes your data intelligently accessible to AI.

Even platforms like Klaviyo are rolling out features to let you integrate your own MCP. This means your campaigns can tap into your entire agency's knowledge base to get smarter results.

I've been helping clients build AI so they can leverage these technologies as they become standard.

Meanwhile, agencies without AI are at a severe disadvantage.

Traditional agencies are getting undersold at 1-2x EBITDA. 

If you're betting your agency's future on publicly available tools, you're already behind.

Here's what building your AI system gives you:
- Every client interaction becomes training data
- Your campaigns get smarter with each iteration
- Premium buyers pay 10-20x EBITDA instead of 1-2x

MCP is essentially the next evolution of how we move and use data. 

It's the streamlined way to utilize your data across tools. 

Without it, you're locked out of the next generation of AI features.

You don't need to abandon your agency or pivot your model.

But you do need to build an AI backbone for your agency.

DM me “OPS” and I’ll show you where to begin.

After working with 1,000+ agency owners and helping them collectively scale by hundreds of millions in ARR, here's what I know:

Every agency that scales to 8 figures and beyond masters these 13 systems.

Every agency that stalls has 3 or more of these systems completely broken.

The 13 Systems:
- Financial Health
- Time & Stress Management
- Marketing & Positioning
- Predictable Lead Generation
- Sales Operations
- Cohesive, Documented Processes
- Delegation & Accountability
- Metrics That Drive Performance
- Client Retention & Expansion
- Hiring & Training Excellence
- Strategic Planning Mastery
- Technology & AI Integration
- Culture & Standards Leadership

If you have more than 3 of these systems broken, you should talk to us.

This is the only thing we focus on: building businesses that can operate without their founders.

Which of these 13 systems is the biggest bottleneck in your agency right now?

APIs are old news.

The future is MCPs (Model Context Protocol).

Here's why this matters:

Traditional APIs connect data between tools. Your CRM talks to your project management system.

MCPs connect your entire data ecosystem to AI models.

When you build a proper "Brain" with MCP servers, you can: → Plug into Claude instantly 
→ Switch between AI models seamlessly 
→ Upload entire client contexts in seconds 
→ Never get locked into one platform

You OWN your data.

If you want to change CRMs? Fine. Your data stays in the 
Brain.

New AI model launches? Plug it in.

Better transcription tool? Switch with zero friction.

This is how you future-proof your agency.

MCPs are the infrastructure layer that makes AI actually useful.

Analysis tasks that could be automated. 📊
- Manual report generation
- Data reconciliation across systems 

These data processing delays don't feel like your biggest problem. They're not dramatic. They don't create visible crises.

But they're quietly consuming massive amounts of high-skill time.

Here's what we typically find:
❌  Senior team members spend 4-6 hours per week generating reports that could be automated. That's 250+ hours per year of strategic thinking capacity being used for manual data manipulation.
❌ Analysts spend 10-15 hours per month reconciling data across multiple systems because there's no integration. That's time that could be spent on actual analysis and insights.
❌ Decision-makers wait days for data they need because it requires manual compilation. That delay slows the entire business. 

These tasks follow predictable patterns. They use the same data sources. They produce standardized outputs. They're perfect candidates for automation.

But they're also "good enough" as manual processes, so they never feel urgent enough to fix.

This is the classic capacity drain trap.

The task takes 2-3 hours. Not enough to scream for automation. 

But multiply that by weekly frequency, multiple team members, and compounding delays...

Suddenly, you've got 20-30 hours per week of collective capacity locked up in data processing that could be automated.

Here’s a real example: 

A client's finance team spent 6 hours every Monday morning compiling data for the weekly leadership meeting. Data from 5 different systems, manually copied into a spreadsheet, formatted, validated, and distributed.

6 hours x 52 weeks = 312 hours annually

We built an automated pipeline that pulls, validates, and distributes the same report in 15 minutes, requiring only a quick human review.

Result: 300 hours saved every year. 60 hours to build. ROI in 3 months. ✅

Once you see the hours saved, you start spotting the same patterns everywhere. 

Where to look:
- What reports do you generate regularly?
- What data do you manually move between systems?
- What analysis tasks follow the same pattern each time?
- Where are you "good enough" with manual processes?

That last one is key. "Good enough" manual processes are where the biggest opportunities hide.

What could your senior team accomplish with 300+ additional hours per year of strategic capacity?

That’s the real ROI: turning lost time into strategic output.

What data processing task is consuming more time than it should?

Most 7-figure agency owners celebrate when they hit a new revenue goal.
They're celebrating the wrong thing.

Revenue doesn't matter. What you KEEP matters.

One of the biggest mistakes I see founders making is focusing on revenue. 

It does not matter how much your business makes. It really just matters how much you keep.

Signs your financial foundation is broken:
❌  Margins below 20% 
❌ No visibility into profit this month, last month, or rolling 3 months ahead 
❌ No tracking of revenue, COGS, and team attribution 
❌ Bookkeeping doesn't assign contractors to specific buckets 
❌ You're paying yourself irregularly 
❌ Taking projects outside your wheelhouse just to make a buck

What good financial health looks like:
✅ Net margins at 35%+ 
✅ Monthly P&L accurate within 2-10 business days of month close 
✅ Clear tracking of CAC and LTV 
✅ Predictable 90-day cash forecast 
✅ Compensation is planned, consistent, and consistently growing

The big theme?

Visibility.

Most agency owners struggle because they don't have correct books and correct forecasts. Without them, you don't know the scoreboard of your business.

Stop celebrating revenue goals.

Start celebrating goals for 7- and 8-figure cash flow instead.

Simple agents do one thing. Department agents do everything.

Here's the evolution:

🤖 Level 0 - No AI 
🤖 Level 1 - Individual agents (pull ad data, flag issues, send alerts) 
🤖 Level 2 - Connected workflows (media buying associate who audits + flags + recommends) 
🤖 Level 3 - Department agents (complete strategic oversight across all company data)

A true department agent can: 
→ Analyze overall company LTV 
→ Review page view trends 
→ Identify sentiment from client communications 
→ Recommend strategic pivots

"Our page views are declining. We should create more content on X topic based on client feedback and performance data."

This level of insight is impossible without centralized data.

You can't build department agents when data is siloed across tools.

The Brain makes this possible.

For marketing agencies, this should be obvious, but most still get it wrong.

Marketing and positioning are how you get in front of your customers, nurture them, and where you live in their mind.

When they have the specific problem that your specific service should solve, do they think of you?

If your positioning doesn't work effectively:
→ You're constantly defending your price 
→ Prospects have longer sales cycle times (no clarity on how your solution is made for them) 
→ Your website isn't dialed in 
→ Marketing assets aren't congruent across the web 
→ You take projects outside your core service because you need the money

If you build this correctly:
→ Very clear positioning in your market 
→ You know exactly who you're talking to 
→ Every piece of content across the web talks to ONE ICP 
→ You're able to price a premium because you focus on a narrow problem that's extremely valuable to solve 
→ Your message resonates with even people not hiring you tell you your content speaks to them

The way to measure this:

If someone hits your website, will they have clarity within 60 seconds if your service is specifically built for them?

If not, they'll find a business that is.

Once you nail positioning, you naturally flow into the next system → lead generation.

And quality leads become exponentially easier.

What problem do you solve so well that people refer you even when they're not buying?

You can't hit 8-figures without killer operators.

Here's how to attract, fund, and recruit them without destroying your margins:

1️⃣ Fix your money model before recruiting

Most agencies sit at $2.5k-$5k monthly retainers. That pricing caps your talent pool.

You need to go upmarket by tightening your ICP, promise, and proof. Then rework your offer and funnel.

Between $1M-$5M is revenue purgatory because cash flow blocks recruiting, not talent availability. 

Great talent costs more but returns 3-5x output.

Fix cash flow first, then recruit, then fix delivery.

2️⃣ Add $1k to Month-1 fees and watch $200k-$300k appear annually

Add a setup, diagnostic, or implementation fee to your first month.

If you're signing 15-25 new clients monthly, that extra $1k = $15k-$25k per month. 

That's $200k-$300k annually to fund operators.

This single adjustment funds your next two senior operators without touching base pricing or destroying margins.

3️⃣ Build a poaching pipeline of 100-200 targets

Define role outcomes, KPIs, and comp range first.

Build your target list through LinkedIn, focusing on competitors and adjacent agencies. Use 1:1 voice memos instead of templates.

Start with referral requests and offer $5k-$10k referral bonuses. If they're the actual fit, pivot to recruiting them directly.

Run this pipeline for 30-60 days parallel to your cash flow improvements.

4️⃣ Structure profit-sharing that wins A-players without giving equity
Senior operators want upside more than inflated base salaries.

Offer 5-12% of profit after expenses, capped at specific amounts. Tie targets to pod KPIs, not company-wide chaos.

Top media agencies allocate 5-10% of revenue to team pools where share grows with seniority.

Structure as phantom equity or incentive comp, never actual cap table. A-players choose upside over base because they bet on themselves.

5️⃣ Install financial guardrails before making offers

Add ceilings and clawbacks to every profit-sharing agreement.

Create eligibility gates based on tenure, quality scores, and retention rates. Tie upside to pod-level performance so company-wide issues don't affect individual payouts.

Track gross margin delta post-hire versus pre-hire to ensure each operator improves unit economics.

The bottom line:

Most agencies hire ten mediocre people with vague responsibilities when they 
should hire two elite operators with crystal-clear KPIs, capped profit shares, and specific pod outcomes.

Get precise on what each seat produces, what triggers bonuses, and what metrics matter.

Once that's set in stone, then you scale.

Are you hiring more bodies or better operators?

Let's talk about ROI, because this is where most companies get it wrong. 💰

They think about AI development as a tech expense. It's not. It's a capacity investment.

Every dollar you invest in AI development should create measurable capacity that enables revenue growth without proportional cost increases.

Not "improved efficiency." 

Not "better workflows." 

Measurable capacity quantified in hours per week or clients served.

Here’s the math:
- Average retainer: $5K
- Hours freed per week from your team’s capacity: 10 hours
- New clients you can serve without hiring: 2
- New monthly revenue from freed capacity: $10K
- Annual new revenue: $120K
- Development investment: $10–20K/month ($120–240K/year)

Break even to slight profit in Year One. Now you have both the capital and the operational foundation to increase investment in Year Two.

To evaluate every development initiative, you should ask: 
❓  How much time does this process consume now?
❓ How much can we reduce or eliminate?
❓ What will the team do with the freed hours?
❓ How does that translate to additional clients served?
❓ What’s the revenue value of that capacity? 

If you can't answer these questions with specific numbers, you're not ready to build yet. 📊

Also factor in error reduction.

If a process causes 5 hours of rework weekly, and automation cuts that by 80%, that’s 4 hours of high-skill time gained.  What's that worth?

Why most AI initiatives fail to deliver ROI:
- They build things that are "cool" or "innovative" without tying them to specific capacity creation or revenue enablement.
- They don't measure baseline time consumption before automation, so they can't prove actual time saved.
- They don't track what team members actually do with freed capacity, so it dissipates into general "busy work" rather than revenue-generating activities.

You need to stay disciplined. 

Track time before you build, set clear capacity goals during, and measure what you actually gain after. 

This is how you ensure AI development delivers measurable business value.

How are you measuring the ROI of your AI investments?

This is Pareto's principle: 20% of your time can and should lead to 80% of your results.

But most founders are living a reactive lifestyle.

They're working a lot of hours, but not putting time into the things that actually lead to leverage and growth.

Broken time management looks like:
→ Constantly firefighting and switching between tasks 
→ High levels of stress and anxiety 
→ Not able to be present with family 
→ Vacation time doesn't exist (or you're working through it)

Proper time and stress management systems:
→ At least 25% of your time is protected for highly strategic work 
→ You're able to get into deep work 
→ Operations run smooth without needing you there 
→ Meetings are short and structured with clear agendas 
→ Your calendar has space to do the most important thing as founder: THINK

Simple test to measure this system:

If you take two weeks off, how well will your business run?

If the answer is poorly, this system is broken.

At Amazon, one of the key ways you got promoted was when you left your operation, your operation was able to run without you.

The same principle applies to your agency.

What percentage of your time last week was truly strategic vs. reactive? 

Be honest.

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Jordan Ross

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