Mitchell Feldman’s relationship with technology started long before AI became the business world’s favorite buzzword. Introduced to computers by his mother in 1984, he began programming at just 12 years old and has spent nearly 25 years building a career at the intersection of technology, sales, and marketing. Along the way, Mitchell founded and sold several technology businesses, invested in others, and saw one of his larger companies acquired by Hewlett Packard Enterprise in 2018.

Today, he is the Founder and CEO of Jam 7, where he is rethinking how businesses approach one of their most demanding functions: marketing. At the center of that mission is AMP, the Agentic Marketing Platform, which combines an organization’s institutional knowledge with specialized AI agents to create strategic marketing content at scale. Interestingly, AMP did not begin as the main product—it was originally built as an internal tool for an AI-powered marketing agency Mitchell was running.

When the traditional agency model proved difficult to scale, he made the bold decision to abandon it and turn the technology behind the scenes into the business itself. In this conversation, Mitchell shares how that pivot changed everything, why AI is reshaping the marketing agency model, and what he has learned from decades of building technology companies.

When the Back-Office Tool Became the Business

Mitchell’s first version of Jam 7 looked very different from the company it is today. The original idea was to build an AI-powered marketing agency, using technology to produce human-like content at scale while keeping the service model familiar to clients. Behind the scenes, the team created AMP as an internal tool to make that work faster and smarter. But once Mitchell stepped onto the agency side for the first time, he quickly saw a problem: the model was hard to scale. Referrals brought in business, but inbound demand was weak, adding clients meant adding more people, and changing the messaging was not solving the underlying issue.

Then came the realization that changed the direction of the company. As AI became easier for businesses to access, Mitchell noticed that more companies wanted to take marketing capabilities in-house rather than hand everything over to an outside agency. The very tool Jam 7 had built to support its own team suddenly looked much more valuable than the service wrapped around it. Instead of asking customers to depend on Mitchell’s team to produce content, why not give them the platform and let them do it themselves?

That decision meant walking away from the agency model and turning Jam 7 into a platform-first business, but Mitchell says the change was worth it. Inbound inquiries started arriving, customers became enthusiastic advocates, and the company could grow without having to assemble another team every time a new account came on board. For Mitchell, the lesson was simple but powerful: sometimes the thing you build to support the business ends up being the business. The real opportunity was not in doing more marketing work for clients, but in giving clients the tools to reach the answers faster themselves.

The Hidden Tax Slowing Marketing Down

For Mitchell, one of the biggest problems in B2B marketing is not a lack of ideas—it is everything that has to happen before an idea becomes something customers can actually see. He calls it the “coordination tax”: the invisible time spent chasing input from sales, product, brand teams, and leadership just to get one piece of content approved. A white paper that should take days can suddenly take three or four weeks. The instinctive response is often to add more people and more specialists, but Mitchell argues that this can make the problem worse. More people means more conversations, more approvals, and even more knowledge scattered across the company.

That problem sits right at the heart of AMP. Instead of forcing teams to rebuild their understanding of the business every time they launch a campaign, the platform is designed to create a shared institutional memory—one place that understands the company, its customers, previous marketing performance, positioning, language, personas, products, and more. Mitchell sees this as especially valuable for B2B technology companies being pushed to grow while budgets and teams are getting smaller. The goal is not to remove the creative part of marketing, but to eliminate much of the repetitive groundwork so people can spend more time on the ideas, instincts, and emotions where humans still have the edge.

But Mitchell is equally careful about what goes into that shared brain. Simply connecting an AI tool to every document sitting in SharePoint or Google Drive might sound smart, but he believes it can actually sabotage the result—especially when a company has hundreds of conflicting versions of the same story. AMP instead checks information for consistency, challenges assumptions, tests positioning against synthetic audiences, and plays its conclusions back to the customer before treating anything as truth. That process can even reveal that the person experiencing a problem is not the executive the company thought it was targeting. Once sales, marketing, product, and leadership finally agree on how the business should talk about itself, Mitchell says that is where the real magic begins: AI stops producing generic content and starts communicating with genuine context.

How to Escape the AI Slop

Mitchell is not worried that AI will automatically make every brand sound the same. He is worried about companies using it badly. In his view, generic output usually starts with generic input: vague prompts, messy data, and no real understanding of the brand behind the words. That is why Jam 7 spends so much time on the shared marketing brain inside AMP. The platform does not just listen to what a company says about itself; it also watches the wider market, tracks what customers are talking about, and looks for moments where a brand can genuinely add something useful to the conversation.

One example came from a client in AI security. When news broke early in the morning about an AI agent going rogue and hacking into Hugging Face, AMP had already picked up the story before the client’s team arrived at work. By 9 a.m., the platform had connected the news to the company’s positioning, created a point of view in its own language, and prepared a blog that fitted into campaigns already underway. For Mitchell, that is the difference between simply generating content and creating something timely, relevant, and unmistakably connected to a brand.

That same curiosity shapes how Mitchell and his team build AMP itself. They experiment constantly, but they are careful not to chase every shiny new AI feature simply because it exists. Right now, the focus is firmly on content that can increase authority, visibility, and pipeline for customers. From there, Mitchell can already see AMP expanding into sales enablement, customer success, RFPs, award submissions, and other parts of the customer journey. The ambition is huge, but the approach is deliberately incremental: build one part of the flywheel well, prove that it works, and then move to the next.

AI Can Level the Field, Humans Still Win

For Mitchell, one of AI’s biggest promises is not replacing marketers—it is giving smaller companies access to capabilities that once belonged only to large enterprises. A growing business may not be able to hire separate experts for SEO, brand, product marketing, content, and creative strategy, but an AI-powered operating system can help fill many of those gaps. That changes the competitive equation. Instead of relying on a huge team, smaller companies can use AI to handle the checklists, connect campaigns, suggest the next step, and even create brand-aligned imagery at scale. What still matters most, though, is the person behind the machine: the one with the idea, the instinct, and the understanding of what customers actually care about.

That is why Mitchell believes the marketers who thrive in the future will not simply be the ones who understand AI best. They will be the ones who understand people. He describes the shift as moving beyond B2B or B2C toward “H2H”—human to human. AI can remove the groundwork, speed up research, and make content production dramatically more efficient, but it cannot replace empathy. The same applies to senior marketing leaders. Mitchell expects CMOs to stay firmly in the picture, but with a sharper focus on strategy and revenue rather than getting buried in coordination and execution.

And that human focus also shapes Mitchell’s advice for anyone building a company from scratch. His message is simple: start small and prove that people genuinely want what you are building before chasing scale. Find a handful of friendly customers, make them happy, listen carefully, and use their feedback to improve not just the product but the messaging and go-to-market strategy around it. Too many founders try to attack a huge market before they have earned the right to grow. As Mitchell puts it, the first goal should not be revenue at any cost—it should be creating something customers enjoy enough to keep asking for more.