This article was based on the interview with IFPA’s Jim Rucinski on running a global digital experience with two people by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
If you’re leading a marketing or technology team in the enterprise, you’re familiar with a persistent, gravitational pull: the desire to do more. More campaigns, more personalization, more content, more channels. The prevailing logic suggests that growth requires addition, and that the primary constraint is headcount or budget. We’ve all sat in meetings where the solution to a complex problem is framed as needing “more resources.” But what if the more potent strategy isn’t addition, but a highly disciplined form of subtraction? What if the key to agility at scale isn’t moving faster, but being more deliberate about what you choose not to do?
This isn’t a theoretical exercise. It’s the daily operational reality for Jim Rucinski, Solution Engineer at the International Fresh Produce Association (IFPA). He and his colleague are a digital team of two, responsible for a global digital ecosystem that serves a remarkably diverse set of audiences—from growers and shippers to retailers and researchers. Their story is not one of a scrappy startup making do, but a masterclass in operational leverage and strategic focus. They manage a complex web platform, content management, personalization, analytics, and AI initiatives by ruthlessly prioritizing what creates capacity over what simply adds another task to the list. It’s a compelling look at how the right mindset, paired with the right technology stack, can create an impact that belies the size of the team.
The Litmus Test: Is It a Capability or a Chore?
For any marketing leader, the influx of requests from across the business is relentless. The default response is often to accommodate, leading to a sprawling portfolio of custom landing pages, one-off campaigns, and technical debt. A small team doesn’t have this luxury, forcing a level of scrutiny that larger teams would do well to adopt. At IFPA, every request is run through a gauntlet of filters, from checking for substance and scope to ensuring distributed ownership. But the final, most critical test is about long-term value.
“Our core technical test comes down to this: Does this create a reusable capability? Or is it just another thing that we have to maintain forever? I think small teams can get into real trouble when they continuously add custom work without reducing manual effort. Every custom landing page or manual update is a permanent tax on our time. So reusable components and automated data flows eliminate that tax… Our job isn’t to build more things. Our job is to build reusable capabilities that create capacity.”
This is a fundamental shift in perspective. Rucinski frames maintenance not as a cost of doing business, but as a “permanent tax” on the team’s most valuable asset: their time. This changes the entire calculus of a project. A request is no longer evaluated on its immediate marketing impact alone, but on its total cost of ownership over time. By focusing on building reusable components and capabilities—whether that’s a flexible content template or an automated data flow—the team isn’t just fulfilling a single request. They are building an asset that reduces the effort required for all future, similar requests. For an enterprise leader, this is the blueprint for scaling operations without scaling headcount linearly. It’s about investing in systems that pay dividends in the form of reclaimed hours, allowing the team to focus on strategic work rather than perpetual maintenance.
Automating the “Maintenance Drag”
Every team has its own version of a recurring, low-value, high-effort task. It’s the digital equivalent of Sisyphean rock-pushing—work that has to be done to keep the engine running but creates no new forward momentum. Rucinski calls this the “maintenance drag,” and his team’s approach to solving a particularly tedious example—managing hundreds of sponsor logos for global events—is a case study in practical automation. The manual process was a time-sink of formatting, resizing, and uploading. The solution was to leverage their existing tech stack to engineer the problem away.
“We take a repetitive support task that used to eat up hours of our week, use our tech stack to automate it, and hand self-service ownership back to the business so we can focus on the next big opportunity. Starting in 2027, we’re looking to move the entire logo update process completely out of the digital team and let that become part of the sole responsibility of the sales team.”
This is tactical brilliance with strategic implications. By using Optimizely’s Digital Asset Management (DAM) to handle resizing and GraphQL to serve the correct logo dynamically, they didn’t just make the process faster; they fundamentally changed who is responsible for it. The roadmap is clear: first, automate the technical work; second, shift the now-simplified task back to the business unit that owns the relationship (the sales team); and third, eventually enable the sponsors to self-serve. This multi-stage plan systematically removes the digital team as a bottleneck. For marketing leaders, this is a powerful model. Identify the most significant “maintenance drags” within your organization, and architect a solution that not only automates the task but also empowers the business owners to manage it themselves, freeing up your expert resources for higher-value challenges.
Redefining “Failed” Content for the AI Era
In a world driven by dashboards and KPIs, content that doesn’t hit its human traffic targets is often labeled a failure. The standard procedure is to retire it, declutter the site, and move on. This, Rucinski argues, is an increasingly outdated model. The audience for your content is no longer just human visitors clicking through a homepage; it’s also the legion of AI engines, crawlers, and internal search tools constantly indexing the web for authoritative answers. A piece of content might not be a blockbuster with human readers, but it could be the perfect, specific answer an AI needs to satisfy a user query months from now.
“Retiring content just because human click-throughs were low is pretty shortsighted today. We have to remember that human visitors are only half of our audience now. The other half is other AI engines. So an article or resource might not get a flood of human traffic one day, but maybe three months down the road, an AI engine like ChatGPT, Gemini, or our own site’s AI search tools might pick that exact page up to answer specific industry queries. So the content still has tremendous long-term value. It’s just operating in non-human ways.”
This dual-audience mindset changes the definition of an asset’s value. The question shifts from “How do we kill underperforming content?” to “How much effort should we spend actively promoting it to humans?” If a page doesn’t resonate with the broader human audience after some initial experimentation, the solution isn’t to delete it. It’s to simply dial back the active promotion, let it settle into a well-structured site index, and allow it to function as a long-tail asset for machine audiences. This approach minimizes wasted effort on demolition while maximizing the long-term knowledge value of your content library. It’s a pragmatic strategy that recognizes content as a long-term investment, not just a short-term campaign tactic.
A Grounded Approach to AI: The Babysitter Test
With the explosion of AI tools, it’s easy for teams to get caught up in the hype cycle, adopting technology that promises to remove work but ends up adding a new layer of supervision. For a resource-constrained team, the distinction is critical. An AI tool that requires constant prompt engineering, manual auditing, and fact-checking isn’t a force multiplier; it’s a new, high-maintenance employee. Rucinski’s filter for adopting AI is refreshingly practical and serves as a valuable gut-check for any leader evaluating a new tool.
“If an AI engine requires constant prompt engineering, editing, and manual auditing, it hasn’t removed work. It’s just hired you to be a babysitter. So we focus on solid API coding first, and we use AI purely as a tool to create capacity.”
The “babysitter test” is a brilliant, simple heuristic. Does this tool automate a process and run reliably in the background, or does it require my constant attention to function correctly? At IFPA, the focus is on AI that removes friction from existing workflows—using it to enforce campaign taxonomy, audit AI search citations, or run plain-English queries against analytics data. This approach treats AI not as a magical replacement for strategy, but as an amplifier for a well-architected foundation. The real workhorse is the clean data and solid API structure that feeds the AI. This is a crucial lesson for enterprise leaders: before you invest in the shiny AI application layer, ensure your foundational data and content architecture are in order. Otherwise, you’re not automating intelligence; you’re just creating a more sophisticated, and potentially more frustrating, chore.
The lessons from a two-person team running a global digital operation are not about how to operate on a shoestring budget. They are about the power of intentionality. The principles Rucinski champions—building reusable capabilities, automating the maintenance drag, designing for both human and machine audiences, and applying a healthy skepticism to new technology—are universal. They are the core tenets of a modern, agile, and highly effective marketing technology function, regardless of its size.
Ultimately, the story of IFPA’s digital team is a powerful reminder that the most significant constraints we face are often the ones we impose on ourselves. By shifting the focus from simply “doing more” to “creating capacity,” we can build systems that are not only more efficient but also more resilient and more impactful. True agility, it turns out, might have less to do with the speed at which you work and everything to do with the operational room you create to focus on what matters next.