In this episode
Jim Rucinski, Solutions Engineer at the International Fresh Produce Association (IFPA), runs the association’s entire digital ecosystem — web platforms, content management, digital asset management, analytics, and personalization — with a digital team of two, serving growers, shippers, retailers, suppliers, researchers, media, and global event attendees across the fresh produce and floral supply chain. Recorded at Optimizely’s Opticon 2026 in New York, the conversation is about what a constraint that tight forces you to decide: the filters every content request has to clear, the sponsor-logo workflow that was eating hours a week until Optimizely DAM and GraphQL absorbed it, why IFPA now tracks AI citations alongside conversions, and how Rucinski separates AI that removes work from AI that hands you a system to supervise.
Key takeaways
- A two-person team changes the question from what to build to what to refuse. Every request runs through a substance check, a scope and authority check, a distributed ownership test, and a final technical test — and any one of them can end it.
- “Does this create a reusable capability, or is it just another thing we have to maintain forever?” is the governing question. Rucinski’s framing: the job isn’t to build more things, it’s to build reusable capabilities that create capacity.
- Every custom landing page and manual update is a permanent tax on the team’s time. Small teams get into trouble by continuously adding custom work without reducing manual effort.
- Automation should end in someone else’s hands, not the digital team’s. Sponsor logos went from five to fifteen minutes per page — across dozens to hundreds of sponsors — to an Optimizely DAM asset tagged once and served to the right event pages by GraphQL. In 2027 the update process moves to the sales team, and eventually to sponsors uploading their own logos.
- Leadership’s numbers and the team’s numbers are two views of the same house. Leadership tracks event registrations, global engagement, and verified member benefit usage; the team watches the data plumbing and operational signals underneath them.
- Human visitors are now roughly half the audience; AI engines are the other half. IFPA uses Optimizely’s citation agent to audit where and how its content is cited across generative AI platforms, because members increasingly ask their questions inside ChatGPT, Gemini and Perplexity rather than on the association’s site.
- Low human traffic is no longer a reason to retire a page. IFPA dials back the promotional slots, leaves the page in the structured index, and lets it ripen for AI engines and site search — demolition work is time a small team can’t recover.
- AI is an amplifier, not a replacement for engineering. Ignore the foundational data pipelines and AI tools ingest noise and output garbage; GraphQL’s clean, strongly typed API structure is what feeds predictable context to both the web apps and the generative engines.
- “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.” That is the adoption test.
Chapters
- 0:00 — A two-person team running a global digital experience
- 2:41 — Thirty years of engineering, pointed at business outcomes
- 3:47 — Why IFPA has no single audience
- 4:47 — The filters: substance, scope, distributed ownership
- 5:41 — Reusable capability, or a permanent tax on your time
- 6:56 — What maintenance eats every week, and the biggest dent in it
- 7:42 — The sponsor-logo fix: Optimizely DAM + GraphQL
- 9:16 — Sponsor break
- 10:57 — Leadership’s numbers vs. the team’s numbers
- 11:28 — Closing a multi-year cross-domain tracking gap
- 12:13 — Citation tracking: when half the audience is an AI engine
- 13:21 — What happens to content that doesn’t perform
- 15:17 — AI that removes work vs. AI you have to supervise
- 17:26 — Staying agile at a team of two
What a two-person digital team actually decides
Most organizations running personalization, content management, and multiple audience segments would staff it as a department. IFPA staffs it as two people, with development handled by solution partner Perficient. That constraint moves the decision upstream: before a line of code or a layout is touched, the request has to survive four filters. The substance check asks whether there is enough there to justify a page, let alone a campaign — and Rucinski will go back to the stakeholder and say so. The scope and authority check asks whether another organization is the real authority on the topic, in which case IFPA links out rather than recreating it. The distributed ownership test asks whether marketing managers will be able to maintain the result themselves, so the digital team doesn’t become the permanent webmaster. And the technical test asks the only question that compounds: reusable capability, or another thing to maintain forever.
Why maintenance is the real budget line
The maintenance load is a daily challenge, and a large share of the week disappears into routine content updates and page support — what Rucinski calls the run-the-engine work — while the team is simultaneously integrating the full Optimizely product suite. The way out is not to work faster on the support queue but to remove items from it permanently. Sponsor logos are the worked example: adding or updating one logo on an event page took five to fifteen minutes of formatting, resizing, uploading, and linking, multiplied across the dozens to hundreds of sponsors attached to IFPA’s worldwide events. Rebuilt on Optimizely DAM and GraphQL, the DAM handles resizing and the asset is tagged once; GraphQL serves the correct rendition to the correct pages. The team stopped touching individual pages at all.
The two-stage handoff that makes automation stick
Automating the task was the first stage. The second is giving the task away. Starting in 2027 the logo update process leaves the digital team entirely and becomes the sales team’s responsibility; past that, the intent is to let sponsor companies upload and approve their own logo files directly, removing the internal back-and-forth. This is the pattern Rucinski describes as fighting maintenance drag: take a repetitive support task, use the stack to automate it, and hand self-service ownership back to the business — which is the only version of automation that frees a two-person team rather than making it the operator of a new system.
Measuring when the answer happens somewhere else
Leadership wants macro business results: event registrations, global engagement, verified member benefit usage. Internally the team watches the plumbing. For years the most consequential problem was a broken cross-domain tracking setup between the marketing site and the member portal; closing that gap in 2026 gave IFPA a complete end-to-end view of the member journey for the first time. Optimizely and Opal AI now feed GA4 and ODP directly, so questions get asked in plain English in seconds instead of consuming hours in standard analytics reports. And because members increasingly ask their questions inside ChatGPT, Gemini and Perplexity rather than on IFPA’s website, the team uses Optimizely’s citation agent to audit exactly where and how its content is being cited across generative AI platforms. Page views fluctuate; being cited as the trusted source in the industry is the signal Rucinski treats as real impact.
Why underperforming content stays up
The historical reflex — a page misses its human traffic target, so it comes down — reads as shortsighted to Rucinski, because human visitors are only about half the audience now. A resource that draws little traffic today may be the page an AI engine picks up three months from now to answer a specific industry query. So the question stops being how to kill underperforming content and becomes how much operational effort to spend actively promoting it. Working with Perficient and Optimizely web experimentation, IFPA tests headlines and gives a page every chance to find its audience; if human traffic stays low, they dial back the active promo spots on the homepage, leave the page sitting cleanly in the structured index, and let it ripen. Nothing is wasted, and almost no time goes into demolition.
The AI adoption filter for a lean team
At a conference where nearly everything carries an AI label, the label spans a feature that speeds up a draft and a system that executes on its own — and Rucinski’s point is that a lean team can absorb one of those, not both. AI is an amplifier, not a replacement for fundamental engineering: ignore the foundational data pipelines and the tools ingest noise and output garbage. Behind IFPA’s personalization and AI work, GraphQL’s clean API structure is the workhorse, feeding strongly typed, predictable context into both the web apps and the generative engines. Practical adoption means removing manual friction from work already being done — Opal enforcing campaign taxonomy so tagging stays clean, conversational queries against GA4 and ODP replacing hours of report-pulling. Anything requiring constant prompt engineering, editing, and manual auditing has not removed work; it has hired you as its babysitter.
What agility means at a team of two
Rucinski’s own definition has nothing to do with speed. At sixty-one and thirty-plus years into the work, he has no patience for researching technology for its own sake or chasing every new tool. He starts from real operational problems — he knows when a workflow feels broken — does targeted research for a solid practical fix, and accepts that the right answer is often not the over-engineered best-in-class platform. It just has to be the right solution for a team of two: something that removes drag and actually works. Agility, in his framing, is creating enough operational room to focus on the next important thing.
FAQ
How does a two-person digital team decide what to build? IFPA runs every request through four filters: a substance check on whether the business case justifies a page at all, a scope and authority check that will link out to a better source rather than recreate it, a distributed ownership test so marketing managers can maintain the result without the digital team, and a technical test asking whether the work creates a reusable capability or one more thing to maintain forever.
What made the biggest dent in IFPA’s maintenance load? Sponsor logos on event pages. Adding or updating a single logo used to take five to fifteen minutes per page across dozens or hundreds of sponsors. IFPA rebuilt the process on Optimizely DAM and GraphQL so the DAM handles resizing and GraphQL serves the correct rendition to the correct event pages, and the team no longer touches individual pages.
How does IFPA measure reach beyond its own website? With citation tracking. Rucinski uses Optimizely’s citation agent to audit where and how IFPA content is cited across generative AI platforms, on the view that members increasingly ask their questions inside ChatGPT, Gemini and Perplexity rather than on the association’s site.
What happens to content that does not hit its traffic targets? It is not torn down. IFPA dials back the active promotional slots on the homepage and leaves the page in the structured index so AI engines and on-site search can surface it later. Rucinski argues that demolition work costs a small team hours it cannot spare, and that low human traffic no longer means the content has failed.
How do you tell useful AI tools from ones that create work? Rucinski’s test is whether the tool removes manual friction from work the team already does. If an AI system requires constant prompt engineering, editing and manual auditing, it has not removed work — it has hired you to supervise it.
What had to be fixed before any of IFPA’s measurement worked? A cross-domain tracking gap between the marketing site and the member portal that had persisted for years. It was closed in 2026, giving IFPA a complete end-to-end data set for the member journey for the first time.
About Jim Rucinski
Jim Rucinski is the Solutions Engineer at the International Fresh Produce Association (IFPA), where he oversees the evolution of the organization’s enterprise digital ecosystem. A self-taught programmer with more than 30 years of software engineering experience, Jim specializes in turning operational friction into automated, reusable capabilities. Partnering with solution provider Perficient, he focuses on leveraging modern CMS architecture, GraphQL, and practical AI tools to run a global digital presence efficiently.
Jim Rucinski on LinkedIn: https://www.linkedin.com/in/jim-rucinski-925004258/
Resources
IFPA: https://www.freshproduce.com/
Optimizely: https://www.optimizely.com
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Transcript
[00:01:03] Greg Kihlström: Hi, I’m Greg Kihlström, host of The Agile Brand, and here’s a question for you. What if the real limit on your digital experience isn’t the size of your team, but how much of that team’s week is already spoken for? At small scale, agility isn’t about moving fast. It’s about being deliberate enough about what you don’t take on, that there’s still room to build something new. Today we’re going to talk about running a global digital presence, personalization, content, multiple audiences with a two-person team, handling content and experience tools to non-technical colleagues without the experience coming apart, and telling the difference between technology that removes work and technology that adds something new to maintain. To help me discuss this topic, I’d like to welcome Jim Rucinski, Solution Engineer at International Fresh Produce Association, or IFPA. Jim, welcome to the show.
[00:02:34] Jim Rucinski: Thanks, Greg. It’s nice to be here.
[00:02:36] Greg Kihlström: Yeah, looking forward to diving in here. Before we do, though, why don’t you give a little background on yourself and your role at IFPA?
[00:02:41] Jim Rucinski: Sure. So I’m a self-taught programmer with a senior software development background, and because of this, I kind of view business problems through a different lens than a lot of marketers. I’ve spent more than thirty years in the technology world, but today my focus is much less about technology itself and more about how technology can support the business outcomes. At IFPA, I’m part of a digital team managing the evolution of our digital ecosystem that includes web platforms, content management, digital asset management, analytics, and personalization, not to mention some AI initiatives. Because our team’s really small, my role bridges the technical architecture with strategic operations. It’s about figuring out how we can create capacity through automation, governance, and smart systems integration rather than
[00:03:26] Jim Rucinski: just taking on more manual work. The actual development process is handled by our solution partner, Proficient, who we’ve been partnered with since the beginning of IFPA.
[00:03:35] Greg Kihlström: Great. Great. And, and just to, to set the stage a little bit more, can you tell us a little bit about what is IFPA? Who’s the, you know, what’s the mission? Who are the, who are the experiences that you’re building for?
[00:03:47] Jim Rucinski: What’s fascinating about IFPA is that we don’t have a single audience. We represent the entire global fresh produce and floral supply chain, growers, shippers, retailers, suppliers, media, researchers, and global event attendees and exhibitors. And to be clear, we don’t sell produce. We represent the industry. So the challenge isn’t simply publishing content, it’s helping vastly different audiences find the specific industry content relevant to them without creating dozens of separate digital experiences that need to be maintained.
[00:04:17] Greg Kihlström: Great. Great. So let’s dive in here, and we’re gonna start by talking about, you know, as you mentioned, a small team running quite a bit across quite, [chuckles] quite a few audiences. So, you know, most organizations running personalization, content management, and multiple audience segments would staff that as a department, but you’re operating with a team of two. when a new request lands, what’s the actual test you apply to decide whether it gets built, gets deferred, or even gets pushed back on?
[00:04:47] Jim Rucinski: I wish I could say it’s a neat, painless process, but it’s something we battle every single day. And if I’m being honest, the first step in the process is to complain about it all the time.
[00:04:56] Greg Kihlström: [laughs]
[00:04:56] Jim Rucinski: Then you get over the complaint, and you get down to the real work. And because we’re a team of two, we have to analyze the actual business validity of every content request before a single line of code or the layout is ever touched. So we run each request through a very real-world set of filters, and the first filter is the substance check. And sometimes we have to go right back to the business and stakeholder and say, “You just don’t have enough here to justify creating a page, let alone a campaign.” So then we go to the scope and authority check, and we’re not afraid to say if a topic is outside of our scope. If another organization or expert is truly the authority, we’ll suggest linking out to them rather than wasting time trying to create the wheel, recreate the wheel. So then we have the distributed ownership test, and when we
[00:05:41] Jim Rucinski: do build, the goal is always engaging content that doesn’t rely on us for daily maintenance. We design templates and workflows so that marketing managers can update content without our two-person team having to act as ongoing webmasters. And ultimately, our core, core technical test comes down to this: Does this create a reusable capability? Or is 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. We’re far from achieving nirvana, don’t get me wrong, but the end game is in sight, and our job isn’t to build more things.
[00:06:26] Jim Rucinski: Our job is to build reusable capabilities that create capacity.
[00:06:30] Greg Kihlström: Yeah, and, and building on that, you know, no, no matter how much you’re able to prioritize and, and, and think through things that are reusable, there’s always some kind of maintenance load, for, for any team. That’s stuff that has to happen whether or not the business moves forward directly because of it or not. Realistically, how much of your week is that today, and, what’s actually made a dent in it?
[00:06:56] Jim Rucinski: Yeah. So honestly, the maintenance load is a massive daily challenge. A huge chunk of our week is eaten up by some routine content updates and page support. And that’s a tough reality when you’re a team of two, especially right now, because not only are we doing this run the engine work, as I like to call it, we’re also deep in the middle of fully integrating the full Optimizely product suite. So trying to engineer new workflows while constantly servicing daily support requests can really eat up a lot of bandwidth. So that’s why we rely on our solution partner, Proficient, to do our development work. They handle all of the coding for us. We take care of the marketing content up front. And the biggest dent we’ve made in our support load this year was tackling how we handle sponsor logos. IFPA
[00:07:42] Jim Rucinski: runs multiple major events worldwide every year, and managing sponsor logos on event pages used to be a massive manual drag. Until recently, adding or updating a single logo could take anywhere from five to fifteen minutes per page. Formatting, resizing, uploading links, all that kind of stuff. Multiply that across dozens, sometimes hundreds of sponsors and events, and it’s a massive drain on our time. So we started working with our tech stack, and we built a solution using Optimizely DAM and GraphQL. Now the DAM automatically handles image resizing for us, and we simply tag the logo asset correctly in the DAM and GraphQL dynamically serves the correct logo rendition to the correct event pages across the site. We no longer touch, touch individual web pages to update
[00:08:27] Jim Rucinski: logos. 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. And then looking past that, we’re looking ahead so that we can use the DAM to let our sponsor companies upload or approve their own logos on file directly, eliminating internal back and forth completely. So that’s how we fight maintenance drag. 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.
[00:09:02] Greg Kihlström: Yeah. Yeah. That’s great. Yeah. And I’m sure you’re looking forward to, [laughs] to next year’s items. [laughs]
[00:09:06] Jim Rucinski: Very much. The, the logo thing, as anybody at IFPA will tell you, has been the bane of my existence for many, many, many years now.
[00:09:13] Greg Kihlström: I believe it.
[00:09:14] Jim Rucinski: It’s just, it’s really a drag.
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[00:10:57] Greg Kihlström: So then you’re planning things, you’re doing things, and then, you know, a critical component here is also just measurement and, you know, proving it worked and, and being able to measure that it worked. when every initiative has to count ’cause of, you know, limited resources to, to do and, and prioritize, what do you measure, you know? And is the number that lands with leadership the same one that’s most useful to you internally, or are those often two different things?
[00:11:28] Jim Rucinski: So those are definitely two different views of the same house. Leadership traditionally wants macro business results and, and event registrations, global engagement, verified member benefit usage. Okay? But internally, we look at the data plumbing and operational signals that drive those outcomes. For years, one of our biggest hurdles was a broken cross-domain tracking setup between our marketing site and our member portal. Due in no small part to Opal, we solved that multi-year cross-domain gap, just this year. Now we have a complete end-to-end data set for the member journey for the first time. So what really changed the game for us internally is how we pull and evaluate those insights. So we now get fast GA4 insights
[00:12:13] Jim Rucinski: instead of losing hours wrestling, wrestling with standard Google Analytics reports, which if you’ve ever been in Google Analytics, it’s just a nightmare. We now hooked up Optimizely and Opal AI directly into GA4 and ODP. Now we can ask plain English questions in seconds and get what’s working. So we have eliminated much time there. measuring reach beyond the website with citation tracking. Management loves to talk about meeting the member where they are, but the reality today is where they are quite often isn’t our website. People are asking questions directly inside ChatGPT, Gemini, Perplexity, et cetera. Page views might fluctuate, but in our industry, intelligence is being cited by AI, AI engines as the trusted source. That’s how you know you’re making a real impact. So we use Optimizely’s citation agent to audit and track exactly where and how IFPA content is
[00:13:06] Jim Rucinski: being cited across generative AI platforms. Leadership gets the macro conversion numbers they need, and we get fast modern signals from UX data to AI search citations that prove our content is driving the global conversion.
[00:13:21] Greg Kihlström: Yeah. Yeah. And you know, one, one other thing here as far as measurement goes, you know, with any test or experiment, not everything works, right? So it’s– You have to try things, but not everything is, is, is gonna test 100%. When something you built doesn’t perform, what actually happens to it? I, I ask this because a, you know, a small team can’t afford to leave a bunch of failed experiments running, but it also can’t easily afford the hours to unwind them.
[00:13:49] Jim Rucinski: Exactly. So I think here we need to challenge the whole concept of what failed content actually means in today’s digital landscape. You know, historically, if a page didn’t hit the human traffic targets, the knee-jerk reaction was to call it a failure and pull it down. But 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, 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.
[00:14:34] Jim Rucinski: So for us, the question isn’t how do we kill underperforming content, it’s how much operational effort do we spend actively promoting it? Working with our partner proficient in using Optimizely web experimentation, we can test headlines, give content every chance to find an audience. but if human traffic remains low, we don’t waste hours tearing the page down or unwinding code. Thanks to the modular setup of our CMS, we simply dial back the active promo spots on the homepage, let the page sit cleanly in our structured index, and let it ripen for AI engines and search tools to discover over time. So nothing’s really wasted. Little time is spent on demolition work, and our content continues to build long-term value in the background.
[00:15:17] Greg Kihlström: Got it. Got it. And so we’re here at Optimizely’s Opticon here in, in New York, where a lot of what’s on offer has AI on, on the label. and that label covers everything from a feature that speeds up a draft to a system that goes off and executes on its own or nearly on its own. For a team of two, those are very different propositions. What’s your filter for telling the difference between something that takes work off your plate and something that adds a system you now have to supervise?
[00:15:47] Jim Rucinski: Yeah, I think there’s another added, question that you ask yourself too, is how creepy do you wanna be with a lot of this stuff? so there’s a real danger right now of treating AI as a silver bullet for everything.
[00:15:58] Jim Rucinski: People get lured in by this shiny new AI tool and forget that AI is, it’s really just an amplifier. It’s a tool to help you do your work, not a replacement for fundamental engineering. A tool shouldn’t be expected to do vastly different things than what we would do ourselves if we had the time. If you ignore foundational data pipelines, AI tools just ingest noise and output garbage. Behind all our personalization and AI initiatives of GraphQL, the clean API structure, that is a true workhorse. It feeds strongly typed, predictable context into both our web apps and our generative AI engines. When we look at adopting AI, we stick to practical tools that remove manual friction from what we’re already doing. So trying to take the headache out of governance, for example. We use Optimizely’s
[00:16:44] Jim Rucinski: Opal AI to automatically enforce our campaign taxonomy on our target so that our tagging stays clean, while also auditing exactly where and how our content is being cited across generative AI search engines. We speed up analytics. Instead of spending hours pulling reports and manually building spreadsheets, we use conversational AI to query our GA4 and ODP data directly, getting instant plain English answers to what’s working. So 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.
[00:17:26] Greg Kihlström: Yeah. Yeah. Well, Tim, thanks so much for joining today. Great to see you here at, at Opticon. One last question as we wrap up. What do you do to stay agile in your role, and how do you find a way to do it consistently?
[00:17:38] Jim Rucinski: So first off, thanks for having me.
[00:17:40] Greg Kihlström: Of course.
[00:17:40] Jim Rucinski: It was a hoot. This was more enjoyable than I thought it might be.
[00:17:43] Greg Kihlström: [laughs] That’s good.
[00:17:43] Jim Rucinski: So kudos to you. for me, agility isn’t about moving faster or taking on more work. It’s about creating enough operational room to focus on the next important thing. I’ve been doing this for a long time. I’m sixty-one. I don’t know how I got here, but I’m that old. So at this point in my career, I don’t have the time or the patience to research technology just for the quote unquote “fun of it.” I can’t chase every shiny new tool that hits the market. So what I do is I have real operational problems, or as our managers would like to say, opportunities. I know when a workflow feels broken, and I know when something should be better. Agility for us is about taking those specific problems, doing targeted research to find a solid practical fix, and very often that means recognizing that the best solution for us might not be some over-engineered best-in-class platform. It just needs to be the right solution for a team of two that removes drag and actually works.
