WEBVTT

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So last session of the day, thank you for sticking it out with us.

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To close out the day, this final talk is going to look at how AI is reshaping open source

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communities.

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Please welcome Amanda, Wagner, and David Allen.

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Hello, when I asked David earlier, how many people he thought would be in this session,

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he said 8 to 80.

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So thank you all for being here.

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We are talking about everybody's favorite subject, AI, the AI shockwave, and open source

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communities.

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How AI is reshaping the foundation of open source communities and communities as a whole.

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And I think it's really important to note that, to be on theme, AI put the visuals of

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this presentation together for us.

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So in joy, hi, I'm Amanda, that's me.

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I am the senior manager of developer communities at Grafana Labs.

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I have over a decade of experience in community strategy, shaping communities, maintaining

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them, starting them programs and initiatives, and I'm happy to be with you guys today.

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My name is David.

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I'm from Grafana.

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I do developer advocacy work.

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I've been an open source contributor since, before open source was a term, I started

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off with free software foundation, package, maintainer, ship.

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So to get us started here, what is the shockwave that we're actually talking about?

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Within Grafana relative to our community, our open source community, we do regular metrics

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to kind of monitor the health and progress of the community.

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Because our overall ecosystem is growing, I've gotten a little bit lazy and come to

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expect that our community would grow roughly 8 to 18 percent a quarter, almost no matter

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what I did.

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I mean, I could fall asleep and the community would grow because there's an influx of

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people who are interested.

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And so what we got our wake-up call when we looked at the numbers one quarter and it basically

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went down by 27 percent.

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That does not happen.

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So we had a lot of internal discussions to be messed up.

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The measurement is the data quality bad, something else happened, no, the number of people

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entering into the community dropped by 27 percent in one particular quarter.

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So we started asking around and we found, like for example, on the website team and also

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with the number of other companies that like traffic, organic traffic to the website, was

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broadly down by like 30 percent.

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And a lot of the reason why boiled down to question and answer behavior, being deferred

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to things like chatGPT and LOMs.

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And so in the wider marketing world, so to speak, this is not a mystery, this is a broad

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trend that everybody is seeing.

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The point here is that it's happening to community sign-up pages, your discourse instances,

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your slacks, your telegrams, all of those sorts of things.

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So this is the trigger.

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Yeah, and while this was a shock to us, like David is saying, it's not unique to us.

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Most famously, Stack Overflow when chatGPT launched had a 35 to 50 percent decline in traffic.

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So that's not really like a party.

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So what this is indicating, systemic signals across open source is, again, AI is replacing

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these peer-to-peer learning moments.

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It's decreasing that human interaction and connection.

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And those novice participants who would have formally gone to something like a Q&A

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for a mislock channel are now going to AI for that initial touch point.

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So the way that we look at our community journey is through these phases.

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The phase zero being those novice participants.

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It's that first touch point asking dumb questions in public.

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And then phase one is their first contribution.

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Maybe writing content.

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They're building confidence.

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They're getting familiar with the community you've made available.

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And two is where the magic starts to happen.

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This is a pattern of escalation, regular participation, and feeling really integrated into

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the community.

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And then phase three.

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This is the one percent of these community folks.

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It is the crem-delacrem of your community.

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The champions, the advocates, the maintainers and leaders.

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And the really important thing about phase three, while there's Lisa

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Mount of them, they're pumping back into other phases by driving content,

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creating educational material, mentoring.

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A good example of this for us is traditionally in the past.

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If you asked a question on our community forums,

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there was an incredible likelihood that a champion in our formal champions program

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is going to respond to you.

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And so they end up feeding back into this funnel.

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The key insight here that we've mentioned on these last few slides is

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that AI competes most directly with those phase zero and phase one.

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But those experts and veterans, they're remaining stable.

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And so that's something to take note of.

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So the veterans and the experts are remaining stable right now.

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If you look at a number of countries in Asia without picking any particular

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country, we have seen in global news a kind of trend where when birth rates fall,

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you get an inverted demographic pyramid.

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And so from the perspective of today, what we're reporting is perhaps not

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even that big of a deal, because if you're level two and level three folks

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are pretty much stable and still doing their thing, we have sustainability

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issues with open source.

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As previous speakers have addressed here, but we also know that we've got an

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inverted demographic pyramid that's coming.

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So from my perspective in the Grafana community, like I could probably ignore

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this problem for a couple of quarters, but we know for sure that it's coming

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here.

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So if you don't ask questions publicly anymore, then you lose opportunities

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for accidental mentorship and the social glues starts to break down.

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Now we've heard a lot of talks in this room today about concerns like

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sustainability and maintain our burnout.

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And while we need to do our best to address those issues, there's also natural

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attrition.

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People come and go in any kind of community and there needs to be replacement

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birth rate in effect, right?

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So we used to run programs that were like simple welcome.

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If you sign up for our, if you sign up for our slack, we were putting a lot of effort

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into welcoming you and having you talk to an actual human being when you first show

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up.

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But such a program, even if it's really well executed, can't do well if the number

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of new joiners is going to decline over time.

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And the key thing about the inverted demographic pyramid is that your top contributors

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and your maintainers, they don't appear magically without earlier social investment.

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So this doesn't apply equally to every single community out there.

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Back overflow was one of the most heavily hit because if you think about it, it's extremely

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QA heavy and it's extremely transactional.

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They were uniquely positioned to get messed up the worst by the kind of trends that we're

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talking about.

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There are resilience factors out there, which is the extent to which you orient to

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community around relationships and narratives.

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And so some of these factors that are here on the slide are going to start to tell the

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difference between not only communities that are going to survive long-term, but also

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the ones that are going to be less affected by what we're talking about in this talk.

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We'll return to this point in a little bit, but a key moment is basically when you can

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get a community member to prove effort.

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You see like asking a question is an extractive move and basically chatGPT has intermediated

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all of that, the thing that I particularly wonder about most of the people online today

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is who they didn't beat today because they were chatting to a robot all day.

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If you can move from getting people to do the extractive move as their first touch with

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the community to something contributive, that's going to be a very strong resilience factor.

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And we have a few more ideas on what you can do.

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Number one, I like to think about when I first joined working with communities and somebody

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told me the best way to destroy a community is to market and sell them.

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I think that counts extra for developer and engineering communities.

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And so there is this focus that's really important on authenticity.

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So throughout that slide, you're going to hear me say authenticity a lot.

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So focusing where humans matter, learning in public, giving opportunities for product

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feedback, and then building that mid funnel infrastructure, so creating mentorship cohorts,

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office hours, contribution ladders, and structured pathways.

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And then with three and four here, I think there's a really important acknowledgement of

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this moment, the fluidity of the transition.

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So you have the opportunity to establish AI governance early.

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So where is AI allowed in your community?

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Not swimming against the current because people are going to use AI instead of formal methods

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prior to this moment.

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But then also defining where that human experience is necessary and required.

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And then experiment intentionally with log in Q&A's, people's scientific badges, AI

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labels, and that intentionally is very important, right?

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Giving the community opportunities to communicate with you and learn from the ways in which

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they're acting, given this kind of technological moment.

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Okay, we've talked about the big problem.

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Folks in this room should want to hear about solutions and we've got a lot of them, much

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more than we can fit inside of this talk.

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It's difficult to just give you the easy three, do these three things and you're going

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to be great because a lot of this has to be tailored to your community context.

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If there's only one thing that you would take away from this, it's focused on the proof

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of effort moment.

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Now overall, I sort of feel like AI in regard to open source communities was a little bit

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of a Trojan horse that we rolled in through the front gate.

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Now a lot of us are normally tech people and so we're predisposed to be very positive about

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tech and it does have wonderful effects if you're coding and doing any number of other

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things.

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But on the social basis, there's no way to get around the fact that the machine is getting

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between two people and chopping off a relationship that could have otherwise existed or

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have been formed and that's kind of the Trojan's coming out of the horse, so to speak.

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But because we're in the tech industry, we're probably not going to go the lotite approach.

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I heard letters and referred, you know, mentioned in one of the earlier sessions, read

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the history on that and how it worked out for them.

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So basically, the horse is inside the gate, we're going to have to actually deal with

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this now.

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So the best frame of reference is to basically think about how you can take advantage of

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the key opportunities that this provides while rolling with it rather than trying to fight

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against the wave.

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So as one small example, because AI is invading everybody's community, you also have an

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automatic topic that's super, super hot for everybody in your community.

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Like within our context, we have an MCP server and we just kind of notice that whenever we talk

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about or do anything related to the MCP server, everybody comes out of the woodwork.

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Everybody wants to know about the MCP server.

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So ironically, since humans can connect about anything, you can connect about the AI instead

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of having it just get in the middle of you all the time.

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That's the kind of example of lateral thinking that communities need to be doing.

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So the last point that I want to make and then we'll open it up for Q&A and thank you for

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your attention is the wonderful devrim organizers had me here speaking last year and I got

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a cop to something.

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So last year I came and I did this talk and it was about appropriate use of LLMs and

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communities.

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And the key thing that I was trying to say last year was you've got to watch out and make

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sure that the robot doesn't get in between community members.

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You've got to make sure that it doesn't intermediate the relationship.

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Yeah, you can add it into an opt-in channel and people can know that they're talking

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to an LLM and they can choose to do that, but don't auto respond to your community members

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with robots.

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So we knew the principle, we didn't want AI to get in between human relationships and

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then it happened this year despite the fact that we knew that that was going to be a bad

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thing.

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So last year I was like, hey, you know, you can use LLMs to automate certain things and

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make things much easier and while maintaining respect and human connection.

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And well, the first part of that talk was right.

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The second part of the talk got taken away from me by other factors.

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And so now we're going to have to actually cope with that.

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And I really appreciate your attention and we would love any kind of questions that you

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have.

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I came to Faustem in person.

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I chose to be here and the first thing that we do about this kind of thing is that

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we actually connect with each other in person.

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Oh, I was just going to add, I wonder what we'll have to cop to next year.

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Do you need a term?

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Thank you very much.

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Questions?

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Do we have time for questions?

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Oh.

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Anybody have a question?

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You got a question?

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Okay.

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Yeah, thank you for the talk.

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You mentioned earlier that the worst way to run a community is to market and sell them.

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Could you go a bit deeper into what's specifically?

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Yeah, I think that just means using, taking advantage of that organic interaction to sell a

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product.

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I mean, we see it and it registers a lot of the time that's spam.

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There are organizations where the sole purpose of creating places for people to connect

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is to eventually sell them, is like giving information to sales.

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And I can speak from our experience, like we try to be punk rock as hell about this.

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And have a certain level of protection for the sake of collaboration and community.

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So that's kind of what I'm noting about marketing and sales.

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Yeah.

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So in any human relationship, the connection is fundamentally about the connection.

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And the problem with sales and marketing is that it makes the connection about something else.

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So imagine going out to your growing out with a friend for beers.

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And the first thing the friend says to you is, really glad that you came out tonight.

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It gives me the opportunity to tell you about a revolutionary new technology.

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You know?

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All right.

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Why is that Iki?

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That's Iki because the connection is about the connection and he's making it about

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something else.

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Any other questions?

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Yeah.

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Do you want to do this?

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I have a good very nasty question.

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I think you are missing one slide from your presentation to present your new products that you have.

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Maybe mapping the existing and extinguishing current products would show something else.

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Did you analyze this kind of things?

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I am not sure I understood the question to be a perfectly honest.

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I think if you're asking us to sell, I politely decline.

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Would you like to clarify?

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Because I've been using graphana for years and recently I've tried to use some new products.

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Unfortunately I have problems with trying to jump to them because they were completely different.

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Others were expecting to and some of them were removed deprecated and so on.

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So I was wondering if you have some kind of information about how people leave the community regarding that.

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So you got it now, right?

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So I don't need to run again.

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Well, so the issue is that I think without the mic, I'm not playing to the live stream.

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I can talk loud enough so that you can hear me.

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The reasons why people leave communities are shattered into a lot of different reasons.

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Some people have dissatisfactions with any product in any community.

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Some people like in some of the previous presentations have excessive expectations that can't be met by anybody.

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Some people have disagreements on any number of different things.

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I personally do not have broken down data on why people leave the community.

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The issue there is that when people leave a community, they leave.

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And you can't gather data because they're already gone.

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What we can do and what we do do is like observability surveys and community surveys to try to get a sense of how people are feeling before they go.

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When they go, it's probably too late to know why.

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At scale anyway.

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No, I haven't seen any ranting on the forum, but if you know of some and you want to bring it to my attention, I would be happy to take a look.

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Was there a question in here?

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Okay, maybe not.

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Oh, in the back, sorry.

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Thank you so much for your talk.

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I had a question about the different phases you talked about.

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So you talked about phase zero, which is people interacting with a community to get some expertise basically.

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We try to ask questions to understand the product and eventually they end up helping in phase two.

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Do you feel like there might be an opportunity where people jump straight to phase two with LLMs?

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As in, thanks to an LLM, I can contribute much quicker.

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I don't need to ask questions.

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I can just fix my problem myself.

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And then that's my entry into talking to humans.

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I'm going to deliver this to Amanda to answer.

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I feel like we're really using a lot of the room.

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Yeah, I mean, I think it can escalate faster.

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It's a very individual experience, right?

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In short, yeah, I think you can go through kind of that funnel quicker.

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The thing about phase zero is in a lot of ways you can't skip it because it's just the majority of people are going to have that like initial touch point.

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And then inevitably it drops, you know.

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But if they're persistent and want to contribute more, it does make some of the process smoother.

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I'll be the runner.

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We're on our way.

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Thanks.

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Okay, I'm not going to.

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If AI is taking over phase zero and one,

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could we integrate AI's into chat rooms and discussions and like where other people are.

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So that they happen despite AI being there.

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I mean, it's not going to solve the whole problem because.

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But we're still going to go to chat GPT to other private things,

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but we could have AI inside some room at least.

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If you want to add to this, you can, but in our particular community case, AI is already in the chat room.

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What we did in part from last year's talk is that we put AI in as an opt-in kind of a thing.

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So you can go to a particular Slack channel called Ask AI or a particular discourse category.

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So that it's explicit.

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There's no humans here.

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We're talking to robots.

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And anybody can use that.

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And then, of course, other people can see what people are asking and what the answer was.

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And whether it was you rated useful and so on and so forth.

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It's in the website.

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You know, it's in the Slack.

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It's in the discourse.

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Amanda and I, when we were talking and preparing for this talk,

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we're like, did we maybe a little bit do this to ourselves?

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Because we're talking about, for example, chat GPT,

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making it so people don't show up and ask questions and like,

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didn't David kind of launch that in like two places last year?

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Yeah, he did.

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Yeah, I think in short, yes, do those things.

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But I think it's also fair to acknowledge that you don't necessarily always have to recreate the wheel.

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Like, there's a piece of this that is swimming with a current instead of against it.

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And a level of it where we do have to accept that people are going to use.

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Things like Gemini and chat GPT.

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So while you should make things as available as possible,

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an efficient as possible and embrace AI.

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A part of that embracing AI is acknowledging what people are using and where they're meeting.

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One other thing to add here is in the ideation phase and thinking through this problem.

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There's a, there's a very vengeful way of thinking about this problem.

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We're saying, ah, stupid AI company.

