This is an honest reflection on my first community experiment.
A few weeks ago, I wrapped up something I call a "Learning Month" inside the Interledger Foundation community. The idea was simple: instead of pointing people at our documentation and hoping for the best, what if we created a structured, week-by-week learning journey together? A guided experience that built on itself, starting from the basics and working toward something more advanced.
Rafiki felt like the right place to start, it's one of ILF's core open-source projects.
So I designed a five-week program, shared curated resources every week in our Slack community, and watched what happened. Here's what I found.
The ILF Community Is Not One Audience
Before I get into the data, I want to name something that makes community work at ILF uniquely complex: our community is not a single audience, we have about 5 different personas within our audience.
On one end, we have deeply technical contributors, open-source developers, and engineers who can read a code and immediately orient themselves.
On the other, we have CEOs, policy folks, and ecosystem partners who are interested in the what and the why but have no intention of spinning up a Docker container.
I knew this going in. What I didn't fully anticipate was how sharply that divide would show up in the analytics.
How the Learning Month Was Structured
The five weeks were designed to follow a natural progression:
- Week 1 kicked off with high-level conceptual content: what Rafiki is, where it fits in the Interledger ecosystem, and how it relates to the broader protocol.
- Week 2 went deeper into core concepts: payment pointers, Open Payments, and Rafiki's double-entry accounting model.
- Week 3 shifted into hands-on territory: spinning up a local playground, Docker Compose deployment, and environment configuration.
- Week 4 covered peering and liquidity, which is fairly advanced operational knowledge.
- Week 5 closed with architecture deep-dives and a path to contributing to the Rafiki repo on GitHub.
Each week ended with an open invitation for feedback, and the whole series wrapped up with a live Rafiki Community Call.
What the Data Said
The #rafiki channel grew from 194 to 299 members over the course of the month. That alone felt like a signal the activity was worth doing. But the more interesting story was in the page analytics.
The pattern was consistent and pretty telling: Concepts performed well. Execution did not.
Week 1 and 2 were the strongest by far, the early resources were conceptual and far from code. The Open Payments concepts page saw a +68% lift in traffic. The accounting page was up +32%. People were reading, exploring, and engaging with the ideas.
Then Week 3 arrived, and we hit a wall. The local playground page dropped 34%. The Docker Compose deployment page dropped 30%. Week 4's liquidity content was largely flat. Week 5, which focused on contributing to GitHub, resulted in zero new pull requests.
The drop-off wasn't gradual, it was a cliff and I felt the free fall.
What I Think It Means
My honest read: the community that showed up for Rafiki Learning Month was less technical than what I had prepared for.
One signal I received was that a lot of people want to understand Rafiki, but not all are ready to run it. Designing five weeks of content that assumed increasing technical readiness probably lost a meaningful chunk of the audience right around week three.
That said, I'm cautious about over-indexing on one month of data. It could be a coincidence... It could be timing. I'm reading the signals, not drawing conclusions in permanent ink.
What I feel more confident about: five weeks is probably too long. Engagement was highest at the start and I suspect a tighter, three or four-week format would hold attention better and end before the drop-off has a chance to happen.
The Hard Part: Getting a Pulse on a Segmented Community
One of the trickiest things about running community programming for a mixed community is that you often don't know who's actually in the room.
When someone clicks a link in Slack, I can see the page view. What I can't easily see is whether that person is a developer trying to understand ILP packet flow or an executive who just wants a plain-language answer to "what does Rafiki actually do?" Without that context, it's really hard to know whether your content is landing or just... passing through.
This is a common problem in developer relations and open-source community work. Communities are rarely homogeneous and most analytics tools aren't built to tell you who is engaging, only that someone did.
One thing I'm planning to experiment with in the next Learning Month is parallel content tracks. One track focused on the technical folks, and one for those who aren’t.
What I'll Do Differently
Use UTM parameters from day one. Tracking engagement through page analytics alone made it hard to understand the full user journey. Next time, I'll tag every link with UTM parameters so I can see exactly where traffic is coming from and how people are moving through the content.
Keep the video format. Posts that combined a short video summary with curated resources consistently outperformed text-only updates. It's more work, but it's clearly worth it. People prefer to consume different types of content, some enjoy reading, some prefer visual accompaniment.
Think harder about the technical curve. If the community is mixed, the content structure needs to reflect that. Maybe that means parallel tracks, or being more explicit upfront about who each week is designed for.
Explore gamification. This one is still just an idea, but I keep coming back to it. What if there were real incentives for completing the series? Swag, community recognition, something that made finishing feel rewarding?
The Signals That Mattered Most
Beyond the page data, a few things happened that I found genuinely exciting.
A conversation that grew out of Learning Month connected us to ILF's Grants team in a way that hadn't happened before. And a community member who engaged throughout the month, is now presenting his own Rafiki project at the next Community Call.
Those aren't metrics. But they're exactly the kind of outcomes that make a community activity feel worthwhile.
What's Next
For our next Learning Month, we’re going full steam with Open Payments. This ties into our upcoming hackathon in late 2026 and will be a fantastic opportunity for those interested in grasping key concepts early on.
To learn more or chat with me directly, join us on Slack.
Catch y'all next time!!
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