Why the Middle Layer of Your Agency Org Chart May Not Survive AI with Jennifer Bagley | Ep #841

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Are you still thinking of AI as just “ChatGPT with a better prompt”? Or maybe you’ve played around with Zapier automations and thought, yeah, that’s good enough. Today's featured guest knows that the agencies pulling ahead right now are building full-on AI agent networks that replace routine tasks, streamline data pipelines, and give their teams superpowers. She’s re-engineering her agency around AI and will talk about where she finds top-tier talent and why you don’t need to code to lead your agency into the future.

Jennifer Bagley is the CEO and founder of CI Web Group, a fully virtual digital marketing agency registered in 22 U.S. states with clients across the United States and Canada. A former corporate operator turned entrepreneur, Jennifer started in real estate and mortgage brokerage before leaning into the marketing work she built to support those businesses. Today she runs a modern, tech-forward agency that’s rebuilt its stack around AI, centralized data, and agentic networks, all while carrying the scars and lessons of scaling, pivoting, and re-founding a business from the ground up.

In this episode, we’ll discuss:

• Feeling trapped by the business.

• Hiring, firing, and the people reset

• AI, reskilling, and the end of “middle” roles

• What does this talent cost?

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E2M Solutions: Today's episode of the Smart Agency Masterclass is sponsored by E2M Solutions, a web design, and development agency that has provided white-label services for the past 10 years to agencies all over the world. Check out e2msolutions.com/smartagency and get 10% off for the first three months of service.

From Corporate Ladder to Accidental Agency Founder

Jennifer came from an operations background, a self-proclaimed black belt in Six Sigma and certified project manager. Having built that corporate background, she had made a promise to herself (“by 30 I’ll be an entrepreneur”), and started to build the side hustle that became the main event. She started in real estate and mortgage brokering where she had to learn marketing the hard way; not because she wanted to be a marketer, but because the survival of her businesses depended on it.

Initially, Jennifer didn’t set out to build a scalable agency; she built a team to support her broker network. When the market collapsed in 2008, the same team that did marketing for agents suddenly had a market outside real estate. That “we’ll just help this painter or HVAC company” phase is where the web group was born: small, service-focused, and useful to people in her network. That accidental turn became a business by solving real, pressing problems for paying clients, then leaned into that.

Trading Time for Freedom: The Hard Pivot

For the first five years, Jennifer describes the business as a “lifestyle” operation, profitable maybe, but trapping her time. She was trading billable hours for income and was reaching her limit when she hired a coach that forced a reckoning: if entrepreneurship isn’t buying you time, money, and freedom, what’s the point? So she made the brutal choice of cutting consulting contracts and burning the bridge to the “safety” of hourly work, and effectively gave herself a mulligan.

This is the classic founder pivot: you have to choose between growth that keeps you doing the work and growth that scales the business without you. Jennifer’s reset wasn’t pretty, for a while she lost everything and she and her son lived in an office for a while, but it bought her the permission to build something salable, not just sustainable. Agency owners who feel trapped in delivery need to remember that sometimes you have to give up short-term revenue to create long-term value.

Feeling Trapped by the Agency and Becoming a CEO

Those first five years, Jennifer continued to run a business that started as a supply chain consulting and eventually turned into a sales supply chain consulting. This change meant the business was now a good lead generator for the agency but it also meant Jennifer was essentially selling her image and her time. Until she ran out of time.

Once she felt trapped by the business, Jennifer actually hired a business coach that helped her change the model from “selling Jennifer with marketing on the side” to an actual sustainable business.

She had to go back to the basics and remember she, like every entrepreneur, started the business with the idea of having more time, money, and freedom. It took losing everything, but Jennifer knew she didn’t want a lifestyle business, she wanted a sellable business. The antidote was delegation plus systems.

If you want growth and a future exit, you need to own those CEO responsibilities and be comfortable with letting go of the day-to-day.

Hiring, Firing, and Resetting the Team

Jennifer’s talent strategy has evolved with each stage of growth. Her early hires were the classic “friends, family, fools” bootstrap crew; later she invested in developers, content teams, project managers, and over time, more strategic hires like CFOs, chief of staff, BI teams, and AI engineers. Each five-year arc brought a new set of needs and a new level of sophistication in hiring.

Now, she divides her time between promoting her agency’s work in podcasts and content and thinking of ways to navigate her business in these volatile and exciting times. Her most recent addition to the team was a technology and transformation team that is revisiting all of the agency’s processes, investments, and infrastructure. As a result, she has downsized her team from over 300 W2 employees and refocus the team. The takeaway for agency owners: be honest about whether your people are builders or maintainers, and hire accordingly. The workforce you need for growth is not the same as the workforce you need for stable operations.

Building AI Agent Networks with Centralized Data

Jennifer’s agency shifted from WordPress to Webflow and built agentic networks: hundreds of AI agents that crawl competitors, do strategy homework, and automate tasks that humans used to do. More importantly, they rebuilt infrastructure into a hub-and-spoke model with a centralized min.io data layer and ETL pipelines feeding analytics and BI.

Two big lessons here. One: invest in your tech stack deliberately so you’re not a Frankenstein of five different platforms that don’t talk to each other. Two: design your data architecture so your people (and your AI agents) have a single source of truth. That’s how you get from fire-fighting in six dashboards to proactive, predictive signals that tell you when a client engagement needs attention.

AI, Reskilling, and Shrinking Middle Roles

Jennifer draws a hard line: the agency now tends to hire either very seasoned client-facing leaders or AI engineers; the middle is shrinking. With agentic networks giving junior staff “superpowers,” the agency can afford fewer mid-level “lever pullers.” At this level there’s no room for slow execution or elementary work. That’s a cultural and ethical challenge, both for hiring and for workforce development.

For agency owners, this raises practical HR questions: do you reskill your people, or replace them? Jennifer suggests building agent-driven systems that augment humans, and being brutally honest about who can grow into that future. It’s also a call to action for how we prepare the next generation: schools won’t teach this; companies will need to.

Playing with AI Platforms: Why Leaders Need to Just Know Enough to Be Dangerous

Jennifer started like a lot of agency owners dipping into AI, playing around on tools like n8n, Make.com, Relevance, and Longchain. Her dev team laughed, calling her an “elementary school kid on a tricycle,” but here’s the point: she didn’t need to master the tech. She needed to know enough to point her team in the right direction.

Instead of obsessing over code, she framed the problem differently: “Here’s what I don’t want a human doing anymore. Can you make that happen?” That mindset shift is key for agency owners. You don’t need to be a full-stack AI engineer to lead an agency into the future; you just need to clearly define outcomes and invest in people who can deliver them.

Find Real AI Talent in Unlikely Places

This is where most agencies get stuck. You’re not going to find your next AI architect on Upwork. Jennifer leaned on her network, starting with her cousin Chris, a hardcore developer who initially thought AI platforms were “rookie business.” Once Chris realized the power of agentic networks to scale his expertise, he became the backbone of CI Web Group’s transformation.

Now, she hunts talent in unconventional places: hackathons, LinkedIn, and especially YouTube. Forget the flashy “10x growth hack” videos — she looks for nerds with four views, geeking out about orchestrators and ETL pipelines. Those are the builders who care about solving real problems, not just building hype. Her tip: if you find one, reach out immediately. They don’t want sales, they just want to build.

Designing AI Agents Like an Agency Org Chart

Jennifer compares AI agents to a company org chart. You don’t hire one person to do everything, that’s a recipe for burnout. Same thing with AI. Each agent should tightly focus on a single task, with checks, auditors, and orchestrators overseeing the system.

The payoff was massive efficiency gains. Instead of six different platforms that don’t talk, her agency built a centralized hub with min.io, ClickHouse, and AI layers on top. That’s how you go from patchwork automation to true predictive intelligence.

The Real Cost of AI Talent

If you’re wondering how much this all costs, the answer is… a lot. On the high end, seasoned AI engineers can run you a quarter million in salary. On the low end, Jennifer tests new hires on project-based sprints, maybe $6K for a 10-hour challenge. The point isn’t to cut costs; it’s to prove quickly who can deliver and who can’t.

Her recruiting process is brutal but effective: give candidates a project, a tight deadline, and see how they perform. If they stall, they’re out. If they screen-share fast and solve problems live, they’re in. No fluff, no endless interviews.

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