AI Is Killing The Career Ladder Within Agencies

I learned how to run an agency by sitting in rooms with people who had done it before.

Conference rooms. Client presentations. Post-mortems after deals went sideways. Watching a senior consulting partner navigate a tough conversation and then asking them about it afterward.

That's how it worked. You absorbed it. You watched. You asked questions. You made mistakes in low-stakes situations before anyone handed you the keys.

I'm not sure that path exists anymore.

There was a period of 30 days in my early consulting career where I worked the "night shift" — doing data entry in a database stored on a laptop. Only one person could use it at a time for security reasons. Now, Claude CoWork is the night shift.

Remote work has made it worse, too. It's hard to absorb anything through a screen when your camera's off and you're three Slacks deep.

So where does the next generation of agency operators actually come from?

I don't have a clean answer. But I keep thinking about it. Maybe the path forward is more self-directed — build something, start a side project, create work instead of waiting for someone to assign it.

That's what I'd tell a younger version of myself. Don't wait for a mentor to tap you on the shoulder. Go make something and figure it out.

But I also know that's easier to say from where I'm standing now.

At our agency, we kept running into the same problem: every client engagement required the same types of deep research, audits, and strategic planning — but the sequence and emphasis always varied based on the client's needs.

So we built Master Marketer.

The problem: Generic tools force you into someone else's workflow. You end up adapting your process to the platform instead of the other way around.

The approach: We built a modular API where each function does one thing well. A research report pulls from LinkedIn, YouTube, Moz, SpyFu, DataForSEO, Keywords Everywhere, Exa, and other live data sources — then synthesizes everything through AI into a structured document. An SEO audit crawls the site, converts it to clean markdown, analyzes keyword gaps, evaluates backlink profiles, and checks AI search engine visibility.

Outputs chain together. Research feeds into a roadmap. The roadmap and an SEO audit feed into a content plan. We decide the sequence based on what matters most for a given client. We determine how to weigh certain data inputs.

The outcome: Whether we're serving a SaaS startup or an enterprise B2B company, the underlying intelligence gathering follows the same rigorous process. The inputs change. The quality doesn't.

Here's what I'm noticing across the agencies I talk to and the ones we've acquired: the gap between "using AI tools" and "building AI into your operations" is becoming a competitive moat.

Most agencies are still in the first camp — bolting ChatGPT onto existing workflows, using it for first drafts, maybe automating some reporting.

The agencies pulling ahead are doing something different. They're treating AI as infrastructure, not a feature. They're building proprietary systems that encode their methodology, their quality standards, their way of doing the work.

This isn't about replacing people. It's about compounding what your team already knows how to do.

If you're not headed down this path, your customers certainly are.

I'm thinking a lot about this question: if the traditional apprenticeship model is breaking down, what replaces it?

For those of you running agencies or leading teams — how are you thinking about developing junior talent when the entry points are disappearing? Hit reply. I'm genuinely curious what's working.

Ready to discuss how AI is reshaping your industry? Reply and let me know what challenges you're seeing with talent development in your organization.