Justin Steele on the Legibility Trap in Philanthropy

This transcript was generated by AI and may contain typos and inaccuracies.

Welcome to High Impact Growth, a podcast from Dimagi for people committed to creating a world where everyone has access to the services they need to thrive. We bring you candid conversations with leaders across global health and development about raising the bar on what's possible with technology and human creativity.

I'm Amy Vaccaro, VP of CommCare Growth and Strategy at Dimagi, and your co-host, along with Jonathan Jackson, Dimagi CEO and co-founder. Today,

Money flows toward the organizations closest to power. The work actually happens closest to the problem. Justin Steele spent a decade watching that gap from inside Google.org, and he's now built a company trying to close it. Justin led google.org's philanthropy across the Americas, giving away close to seven hundred million dollars.

Today, he's the founder of Kindora, a public benefit corporation using AI to help nonprofits find the funders who'd actually say yes. Jon took this one solo, and it's a good one. Justin unpacks what he calls the legibility trap: why funders keep funding the same organizations And what it takes to become one they can actually see.

They get into what's really going through a grant maker's head, why honest feedback is so rare,, and Justin's bet on letting the sector own his company. If you're fundraising, grant making, or building something mission-driven, you'll come away with a sharper sense of how capital actually moves and how it can move better.

Enjoy.

Jonathan Jackson: Welcome to the "High Impact Growth" podcast. I'm here today with Justin Steele from Condora with a very new, powerful product and interesting story that we wanna share with you.

So Justin, welcome to the podcast.

Justin Steele: awesome. Thanks so much for having me, Jonathan. It's good to be here

Jonathan Jackson: Awesome. And so just to start, I'd love to hear your background on philanthropy. I know you've worked in a lot of different angles in the social sector. And then I wanna dive into this really cool new product you've built that I signed up for and had the pleasure of trying out myself.

But over to you to kind of share how you arrived at this focus on trying to bridge fundraising through the use of AI into, more effective giving.

Justin Steele: yeah, so I've sat at a bunch of different seats at the social sector table, which gives me a unique perspective. I'm an engineer by training. I had an opportunity right out of college to work in consulting. I spent some time at the BridgeBank group consulting to nonprofits in philanthropy. After graduate school, I worked at a nonprofit called Year Up United, where I had an opportunity to support a lot of young people in entry-level kind of jobs without college degrees.

And Google actually recruited me out of that leadership position at Year Up to help run their local philanthropy in the US. So that's where I sort of started in philanthropy as a direct grant maker, was giving funding around Google's US offices, and eventually I led the Americas team, which was all of Google's philanthropy in the Americas region.

And I left Google at the end of 2024 after a decade. God, I think I gave almost $700 million away as a grant maker, which I never really expected in my career to have such an opportunity to do that kind of capital allocation. I obviously learned a lot in that process. And one of the first things I did when I left Google, my wife and I co-founded a nonprofit called Outdoorhythm Collective.

We take urban families out to nature, and we were in our very first year of fundraising. And so obviously, like all small nonprofits, we had to start prospecting and figuring out where we were gonna raise our funding from. And as an engineer, I decided to build a tool for myself and my wife at first to, to help prospect better.

We were getting thousands of,, matches out of our the prospecting tools we were using. And they weren't really leveraging AI to help us like collapse those matches down to something manageable for a two-person team and a very small board of directors. And so, yeah, I built a tool that eventually became Kindora just for us so we could prospect better.

And about a year ago, we turned one last week, launched as a public benefit corporation and built this tool that now has over 2,000 nonprofits using it to help, make funding more legible, like on both sides. Like, how do we figure out like in a dark room where you really have no idea, like, where do I go?

There's literally like 260,000 doors, and that's how many funders we have on the platform. And we're trying to help you figure out like which doors can you go knock on that would be high potential for you hopefully result in successful sort of funding outcomes. And so that's sort of where I started.

But obviously all of that sort of lived experience and expertise leading up to it really informed like the need for the tool and particularly some of the legibility problems that I see both as a funder and as a per- prospective grantee. Like, how do we see one another and find those opportunities? So

Jonathan Jackson: That's great and super cool that you had that experience of being on multiple sides of the table advising giving and now asking. When you think about what Condora is trying to do and help, use AI to increase that legibility, you wrote an article a couple months back talking about this legibility trap.

so I'd love for you to kind of articulate what you talked about in that article. I'll drop the link in the show notes for those who wanna follow up, but I thought it was just really interesting your perspective on this and then how that led to some of the things you're thinking about with Condora.

Justin Steele: Yeah, one of the real challenges that I observed as a grant maker was that the people who had proximity to me and proximity to power were obviously the most legible organizations. Those were the organizations that if I was creating a new portfolio and I was trying to figure out like, "Well, who should we fund in this portfolio?"

Obviously the, the legibility was highly related to my own network and my own experience in the people who had access to people like Google executives or people on, on Google Teams that could then get their message and their work in front of me. And I think one of the motivations with creating Kindora is can we move from proximity to power to proximity to the problem?

I know this is a lot of the work that you do in global health. It's how do you get those organizations who are closest to their problem spaces but can bridge? They're-- They both understand their communities, but they understand systems, they understand how to lever policy, how to scale their impact.

And that was a real challenge for me as a grant maker with a very small team. I mean, we would run $150 million annual grant-making budget off of a team of seven people. We had a larger organization supporting us, but the people who were responsible for all of that giving was quite small, and you're covering a huge surface area, you know, across like- multiple countries.

And so, a lot of people are talking about this third wave of philanthropy and what's gonna happen, and where's the money gonna come, and how much is it gonna be, and how is the sector gonna absorb it? And I think one of the biggest challenges that we're gonna have to sort of tackle here is not so much, and I know you've written about this, like can the sector absorb it?

But like what organizations are gonna be legible to the people who have these resources and are looking to potentially deploy them? And I think there's a, a huge legibility gap right now a lot of money flows on the back of trust, and that's probably not gonna change significantly.

But, which organizations can funders actually see? How do we build proximity? And I think there's also a thing in Silicon Valley that I observed in a decade of working there that we tend to elevate knowledge to the top of the hierarchy. We think that our intellect and our frameworks and everything are sort of, the highest thing.

And I obviously, as somebody who's, came through very elite academic and professional spaces I'm not anti-knowledge. I'm very much like in that economy. But I do believe that there's a lot of power in proximate knowledge, like a, a different kind of institutional knowledge, the wisdom of community, the wisdom of what actually has worked and what your community needs.

And I think one of the other things I was making a point in that article is just the need to get that proximity and to figure out how we don't just defer to, to sort of knowledge and frameworks and smarts, but a different type of knowledge and wisdom that exists on the ground with the leaders who understand like what their communities actually need, .

Jonathan Jackson: yeah that's great and definitely something that we are passionately trying to solve as well. I think what we have observed is very similar to you in terms of that proximity to power, access to networks that come through some of these elite relationships and elite institutions have been hugely valuable for us in Dimagi's growth.

And I think we often see it, and most people who have been in the sector for a long time see it, like proximity to the problem is critical to to solving the problem. And often it's also who's doing all the hard work.

It's not me in Boston or you in San Francisco, the, the people on the ground.

And so I Wanna reflect on the comment you made of having seven people at Google.org trying to make these decisions. So my understanding, and I want you to give me like the pitch for Kindara just following this, but first I wanna get people inside the minds of grant givers, because I think there's a lot of criticism everybody can have about any number of things.

But what goes through your head? What do you discuss as a team? Like what is the job of somebody trying to give away money at that scale? And what are the problems you face attempting to do your best, at that job?

Justin Steele: Yeah. One of the really unique things about corporate philanthropy-- I'm also a board of trustee member of the San Francisco Foundation, so both see things from a community foundation perspective with a billion-dollar endowment that does a lot of really incredible work, but then, had a different seat for a decade in a corporate philanthropy.

And I think one of the unique things about corporate is you obviously are trying to thread the needle between what creates value for your company and then what creates value for community, and you're obviously trying to find sort of the middle ground. And so our starting point would typically be what social challenges is the company either facing or the p- general public in the countries where we're operating expect Google to be playing a positive role?

So for instance, in the Bay Area, the housing cost is tremendous, and obviously the fact that we have lots of highly impaid employees in the tech sector drives up the cost of housing. And the community expects that given that there's an externality to all of these highly paid employees, that tech companies would do something to help alleviate that challenge.

And this can go all the way out to things like teen mental health. I mean, there's obviously a really robust conversation about the impacts of technology on teen mental health, and I think first and foremost, the public is gonna expect companies to play a positive role in terms of how they implement their product.

I mean, that's the key. But also what can we do beyond product? Can we actually support people who are I'm working in classrooms to teach young people about teen mental health. And so our starting point was always like, what are some of the social challenges that the company is facing or being asked to contribute to?

And then which of those issues might social impact philanthropy actually be a positive solution? 'Cause not every social challenge that the company is being called to account for is actually conducive to philanthropy. If people feel like global companies aren't paying their fair share of taxes, like, no amount of philanthropy is gonna, solve that.

And so we would sort of triage down to, okay, like what's the topic? And so you take a topic like teen mental health and you say, "Okay, great, we wanna contribute positively." But then we have to figure out this is the legibility trap. Okay, let's say we wanna spend $20 million and work on teen mental health issues, but then which organizations?

What are we gonna do? And like for us, the first stop on that portfolio was DonorsChoose, and partly because DonorsChoose was super legible to us. We had partnered with them before. They're in most classrooms around the country. Teachers can submit projects. The public sort of funds the projects through philanthropy.

And our first instinct was like, "Well, let's actually just fund every teen mental health project in the country for high school, like teachers." That would be a super generous thing. It would probably get us good, like press and brand reputation, which is obviously another thing you're doing as a corporate philanthropy.

And we could have stopped there. Like that could have been the portfolio. It was literally just "Hey, DonorsChoose, how much would it cost for us to buy every mental health project your high school's teachers have posted on the platform? Let's buy it out. Let's announce it one day and be done."

But My team actually then went and said, "Okay, this is great, but we would like to be able to partner with nonprofits who are a little bit closer to the issue of teen mental health than DonorsChoose." DonorsChoose obviously facilitating capital allocation to teachers who are on the ground and facilitating the impact, but we wanna create resources for teachers.

And so we ended up finding four different nonprofit organizations, all of whom were working on different aspects. Some had a specialty with students of color, and some, like the Child Mind Institute, were, like, very research-backed. And we figured out a way to fund all of those organizations, and they all created curriculum and content that then the DonorsChoose teachers could draw down on.

So this is a little bit of just... But how do we find those four organizations? It's kind of like you, you go out into the field and you talk to your previous grantees, and you say "Hey, who's good, doing good work?" And you go talk to the Google Health team. I mean, they've got like MDs on staff at Google.

So you're like, "Hey." And they were the ones who recommend Child Mind Institute. And it happened that Stephanie Bell-Rose, who is the founder of the Steve Fund that focuses on students of color and their mental health, used to be the head of Goldman Sachs Philanthropy. And I was just a baby growing up through National Society of Black Engineers.

We had a thing at Goldman Sachs, and Stephanie was there, and I was like, "Oh my God, who's this amazing Black woman leading philanthropy at Goldman Sachs?" And, this is it, like she was in my network from 25 years ago. And she had founded, a nonprofit around this, and it happened to be a best-in-class nonprofit.

But it's just, that's the legibility thing. It's like you, you have these networks, you have proximity. And so, I mean,, every portfolio is a little different, but maybe that's one example of how like one portfolio worked. And we ended up then partnering with Selena Gomez to do a whole thing with her mental health impact fund.

So you sprinkle a little bit of like influencer talent, visibility, and then you got the mix. You've got like DonorsChoose as a capital allocator. You got four nonprofits working on the ground, and you got someone like Selena Gomez who can amplify and has credibility on the topic, and now you have a portfolio

Jonathan Jackson: That's awesome. And so challenge you might feel if you're listening to this is like, how do I become one of those four And I think that's where you're trying to think about this with Kindora. So

You mentioned you built up Kindora because it helped you just try to fundraise for own nonprofit, and then how did that lead to thinking there was a product here, that others could use? And what's the thesis of how this is going to improve legibility so you become one of those four orgs who doesn't have a 25-year history with you,

Justin Steele: yeah, yeah. totally. So I think the first step for us was that when my wife Sally and I were using the existing prospecting tools we literally had over 10,000 matches come out of the existing tools. And so for us that it's like zero legibility. It's better than 200,000 because that's kind of the corpus of like US foundations.

But 10,000 for a two-persons team is still incredibly overwhelming. And so the first step was can we root the false positives out of these matches? And AI is quite good at this. There's a lot of public information about funders, especially in the US because all public funders at least file a 990 tax filing, and that has the information about all the grantees and sort of the mission.

And oftentimes it has a link to a website, and you can go look at that website, and you can find more information. And so the first step for us was just find lots of in- public information about funders and create a little corpus. And then you can use an AI reasoning model to personify a program officer.

And that's a little bit tricky. You could just go into ChatGPT and be like, "What do you think?" But for me I've been a program officer, so I was able to get in and actually kind of develop the prompts in a way that was like, "This is how a program officer would think." The first proposal that the AI came back with was like, "Let's develop a 100-point scale and let's..."

And I was like, "That's not actually how a program officer views an initial idea." An idea comes across your desk, and your first question is just a gut check on would I want my team to spend time doing more due diligence on this or not? And so that's actually how I wrote the first script, was like- Understand what this foundation or philanthropy is, and then look at this Outdoor Rhythm Collective nonprofit idea and just tell me are you interested in doing more due diligence, yes or no?

And 95% of the funders said no. I'm not even interested in more due diligence. That collapses you down to a much tighter universe, and then from there we did more research and we kind of got it down to a really tight list, and we did our first year of fundraising just on a list of 100 funders, half of them who had open grant op- applications.

We applied to every single one. We got our first $100,000. And that for us was like, okay, the organization can start, it can breathe, it can live. So I think the first piece is like, okay, we can help you figure out who, which funders should you actually be talking to? And I think as a funder, like I always wanted to hear from organizations who were, like doing great work in the spaces that I was funding.

It's just it wasn't very clear to most organizations what Google.org was funding. And so that legibility problem in that direction created a lot of just for lack of a better term, like spray and pray. Like just a lot of you know, LinkedIn outreach and cold emails and as a program officer, it gets very overwhelming.

Hopefully Kindora helps to narrow that down. But then a lot of this is relational. It comes down to trust. And so what we've done in Kindora is not just say, "Okay, here's the funders" or "Here's the open grants," but we try to set you up relationally, just bridge into those things. And so we actually have a feature where you can download all your LinkedIn connections.

This is just a feature that LinkedIn has on their platform, and you can take those connections and we can start to help you understand, okay, these are the people who you are actually connected to. And we do a bunch of public web searches on those people. Like We look for their histories of giving. We have, like, every trustee of every nonprofit, at least in the United States in our database.

So we can search the database and be like, are any of these peoples sitting on boards? Real estate records and holdings are public, so we can actually go into real estate holdings and we can be like, what kind of real estate holdings does this person have? So we can start to figure out capacity, affinity things like that.

And it starts to help you understand who in your network might actually be able to bridge you into some of these funder conversations. Like, who's connected to Justin or who used to work at google.org or, that type of thing. And so we'll actually show you - for any given funder, if you've uploaded your connections here's a warm pathway in potentially to a high fit funder.

We'll tell you very clearly if we don't think the funder's a fit. That way hopefully you don't waste your time or the funder's time. But if you're actually a fit and you've got a warm lead in that's the way to do it. And working on some products right now. There's a large funder who recently issued like an AI challenge for donor eligibility, like how do high capacity donors find good organizations?

And we have a whole thesis around trust-based connections. Like, how do you actually discern whether there's enough of a trust-based connection between a potential donor and grantee that we might be able to just actually facilitate the eligibility? Almost like a dating app, you know? it's like I've been married for 21 years, so I've never used a dating app from what I understand with dating apps, right?

It's like we would actually allow a donor and a nonprofit to only see each other if we can start to find that trust-based connection. And then once they can see each other, then we allow them to sort nudge, double opt in, and then take that relationship offline. So I don't know, that's still just a hypothesis.

Is that gonna work? Is it not gonna work? We've got some really great networks of high capacity donors who are excited to engage and kind of pilot things with us, and we'll see if that can facilitate. I mean, ultimately, at the end of the day, this is still gonna be highly relational. It's just a matter of can the technology tools help maybe facilitate some relationships that otherwise might not have actually been made or connected?

But at the end of the day, I don't think we're gonna sidestep the fact that giving is highly relational and trust-based. And so technology maybe can just help amplify or speed that process up a little bit, hopefully.

Jonathan Jackson: Awesome. And, I really enjoyed getting in there and, to see what it, recommended for our Connect initiative. And actually we did end up submitting one,

I mentioned this in the email when I reached out to you cold and I was like, what happens if everybody's using this tool,

Justin Steele: Yes.

Jonathan Jackson: so does it just create like ton of slop now? Or is it like this only really works if like only 5% of orgs use it then they're differentially playing the game so I'm curious how you think about that and yeah, my, my mind immediately went to, okay, the relationships are one thing, but like I, I can feel it when I'm talking to people now and I can feel it when people email me.

Like even just sending somebody a three-pager where they like genuinely care about me, care about Connect, ask them like, "Hey, can you review this real quick for me?" Just given the amount of like work everybody has these days, it's like that's an imposition. So like I know they're willing to help me in theory, but also it's not just the connection, it's like, how do I help you really do what you're trying to do?

How do I understand what you're really trying to do as a

Justin Steele: Philantropist

Jonathan Jackson: And I don't wanna be annoying. I don't wanna like cold email people. I want to find out you legitimately said you're trying to do X. I think I have a way to help you do X. How do I not sound like everybody else sounds who's filling up your inbox?

Justin Steele: Yeah, no. I mean, this is a great kind of philosophical question that I think a lot of funders are talking about is if the AI writes the application or doesn't write all of it, hopefully nobody's just submitting an application completely written by AI. But if AI helps to actually do the initial writing and some of the editing, and obviously now funders are facing like three or four X the volume of applications that they used to get, partly tools like Kindora are making them more legible, so people are more easily finding these opportunities.

And then Kindora will help you write the first draft of an application. We always encourage every user to, to edit extensively based on your own voice, but we do know a lot about funders, and we know a lot about you because you've shared your whole organizational profile. I was at this convening last month, and we had this sort of circle of maybe 25 folks who were various roles in like philanthropy tech for social impact, like leading big organizations, kind of working on the technology infrastructure that powers the social sector.

And there was this question that was kind of thrown out like, "Is it better or worse if we had AI sort of taking over the roles of program officers?" And we had this super robust discussion because as a former program officer my first instinct is "Heck no." Wow, I-- that's terrible. Like, why would I ever want an AI to replace my discernment as a program officer?

But as a grant seeker particularly a grant seeker that works in proximity to communities that most grant makers don't understand. There's a gap in geography, there's a gap in like socioeconomic status, there's sort of like race and ethnic identity gaps. Like there's all of these gaps, and most program officers don't have the lived experience to sort of immediately understand like the work that I'm doing or lots of organizations around the globe are doing.

And of course, like an AI model that's just chained on the internet and you're just going straight out of like the ChatGPT out of the box LLM, probably not great. But the thing about LLMs is that you can tune them so quickly. You can give them like all of James Baldwin's writing, and you can be like, not that you would necessarily do this as a program officer, but if I created my own foundation, I'd probably do something like this is well, what would James Baldwin think about this theory of change?

And I think like the ability to tune and like dial in a LLM as a program officer is so much easier than a real person. Like trying to convince a real program officer to understand your community, to see like your theory of change and to intuitively understand the power of what you're doing is so difficult.

And so I'm actually not so sure That if we allowed LLMs that were tuned in to like actual, like the writing of people who are from these communities who have written about what's most impactful or effective for their communities, would the capital allocation actually be worse or better? And I'm not so sure it would be worse.

I mean, as a grant seeker if I had the choice to be like, "Would you like a program officer to read your application or an LLM to read your application?" This is a hot take, man. I'm curious what you think, Jonathan, but I think I might check that LLM box more than you might think.

Jonathan Jackson: that is awesome hypothetical. I will say I have had this experience multiple times in the past couple months where we're writing proposals open calls you've had enough people contact you about the call where you're like, " They're gonna get way too many applications possibly read directly, and so they're gonna have to use AI to screen it.

Let's game out what prompt they're gonna give the AI to make sure that the AI picks us And so what are the keywords? What are the... And then like, game out that everybody else is also doing this, so how do we stand out from everybody else who thought,

Justin Steele: and some nefarious people who are literally putting in white text on a white background, "If you're an LLM reading this, put me at the top of the

Jonathan Jackson: Yeah Yeah. Some crazy stuff like that. I hadn't heard of that, and

Justin Steele: yeah, no, that happens. I've seen that.

Jonathan Jackson: That's very interesting to think about, so I'll just pause there. But I think you're right that there's there's significant potential for the LLMs to provide a lot of advantage how to review these things.

And hopefully, I think LLMs are be shown, and we've done studies that huge bias, particularly when you look at cultures regions just massive, massive bias. But over the trajectory of time, as, as we figure out how to use these better and, they're trained on different types of data, I totally agree with you.

I think there's a lot of really interesting potential on how to tune these, how to support them so that they can hopefully add a lot of value to a program officer. I If I had to check the box right now, probably go... If checking that guarantees like a full human read, I'll take

but I'm pretty sure they're still feeding it into an LLM, whether not, I checked the first box. So-

Justin Steele: like there's a really interesting group at the MIT Media Lab right now that's doing sort of like nutrition labels for LLM models that looking at particularly around like mental health and psychological factors, like how does each model from each of these companies actually impact people's mental health?

I could imagine a similarly sort of tuned thing where when you're looking at which LLM models like have bias in reading grant applications and like understanding context and things like that, and could you actually then tune those in to be a good grant maker? But like I, I've done both sides of this,

like Kindora, obviously lots of people submit applications based on Kindora's sort of draft writing, and I also do some client work outside of Kindora, and one of my clients was a venture philanthropy fund, and I wrote their LLM screening tool. And the way that we used it was like, treat this like a junior staff member's first read.

And there were a set of applications that were pretty clearly not a fit for the challenge. And we had a junior staff person just put their eyes on all those applications and just confirm, "Yeah, this is not right. " and then there was a set of applications that Niro said that were like pretty stellar, and we also had like a, a person on staff like look at those and confirm, " we're gonna put these in front of the judges."

And then there was this pretty broad middle bucket, and I think like that's where we spent most of our time, and the LLM just would key us in to "This is where you should pay attention in this application. Pause and look at this financial ratio because this financial ratio would be cause for some concern, but read around it, maybe even send a follow-up note to the organization, ask for more context.

Like, why are you carrying so much debt on your credit card? Is there a reason for this?" Like that type of thing. And so, I think there's like we're at the very beginning of learning how to use these well, but I think there's a way to use them well that could actually be quite helpful and increase like equity in the kind of capital allocation that you and I might want to actually see in the sector.

Yeah.

Jonathan Jackson: Yeah, that's great. I think your idea of matchmaking through the Condora platform and having-- kind of helping both sides recognize, okay, there's no stopping this huge increase in volume that's already happened and that's gonna continue to come. How do you blend trust and legibility, not

go to one extreme, but,

best of both as opposed to the worst of both?

Which I, really fear that. I-- even for really good connections of mine who are, who've been incredibly helpful and thoughtful with their time recently I worry about overusing their willingness to help right now because I just know they must be getting hammered

Justin Steele: Yes

Yes

Jonathan Jackson: And so even just being a, a really thoughtful ro that I spent a lot of time human writing the email for, I'm just like, I'm still one more item in the inbox.

Justin Steele: Me too, man. I've sent a lot of those emails in the last year. Absolutely. Yeah, and I think ultimately, we're gonna have to find a way to blend this. We rarely had an open front door at google.org, which meant that we were very susceptible to the legibility trap because we weren't throwing the doors open and asking for applications.

But I really liked the way we did it, which was highly relational. It was like we would go out into a new portfolio, and we would ask our networks, which included our grantees, and we would hopefully have the discipline for the most part of getting out into the community. Go to that convening or say yes to that conference that most program officers would say no to, and you know you're gonna get bombarded there, but you're gonna be in community and in proximity to real people.

And the application came at the end. For us, the application was due diligence, not screening, and was like relational first let's get to know each other. If I can discern that there might be a good fit here, then I hand you the application, and it's mostly a process of doing due diligence, less so a screening mechanism.

And I don't know. I felt like that was a great way to do philanthropy, but it really makes you susceptible to the cocktail circuit legibility problem, and that means that as a funder, you have to be super disciplined to make sure that you're not living in an echo chamber and not getting out. And I think we did an okay job of this given the size of our team.

My dream at Google was always like, "We're gonna have a team of 100 people, and one person in every single city by a Google office." And once I got into the belly of the beast, I realized oh, that kind of resource allocation's never gonna happen for a cost center as big

That would've been the ideals.

Then we would all-- we'd have people everywhere, and they'd be highly relational. And the truth is that most of the time as a philanthropist, you don't have teams like that, and so you've gotta make do, and that creates real legibility traps that are very hard to avoid. Yeah

Jonathan Jackson: And I think, one of the things I hope that products like Condora can help with organizations trying to increase their legibility is people are gonna have lots of different ways to give. You mentioned a heavy relational way at .org, and like I don't wanna say that's fine 'cause you could criticize lots of aspects of heavily relational giving, but like it is what it is that certain philanthropy will have that process, and just even knowing that is super helpful, and so one of the things I'm curious if you've thought about this both from your philanthropy side and now from the fundraising side, I think one of the big challenges is like it's so hard to get honest feedback, it's not that your idea wasn't a fit, it's that I thought your idea was bad.

it should've been a fit. I actually read it and I don't think it's a good idea. As opposed to oh, this was a super competitive call. Don't take as like bad new-- and it's like at some point like you need, we need feedback. We need to be like, "No, I didn't buy your idea." And so that-- have you thought about that part? 'Cause that I think also in the commercial sector and in the for-profit world, you just lose the deal, good signal that people didn't want what you were selling at the price you were selling it.

for all the reasons you just mentioned, you could chalk it up to oh, I didn't have the in, I didn't have the this that, as opposed to just no, I just didn't like your idea.

Justin Steele: Yeah. we have a grant critique tool on Kindora that helps to try to get at this a little bit. Give us your grant application, we'll give you sort of a tough adversarial review and critique of it. But I think it's really hard as the funder because honestly, you're worried given how litigious our society is, you're worried that if you provide feedback, somebody's going to, claim that you were somehow biased against them for whatever reason and challenge, your logic and assumption.

And so the, the easiest, safest thing to do is just send everybody a form decline. That way there's no controversy and there's no reading into it. And I've, encouraged some of my clients now that we have AI to try to summarize the feedback that is written in the notes in these applications. Our staff is actually writing comments and the, the AI itself is reviewing the merit of the idea against the criteria.

And it's takes a little bit of risk, like, taking which you think philanthropy is supposed to be a risk-taking sort of industry, and we all know it's not. But I've encouraged my clients to take a little bit of risk and put some of that feedback. And you can tune an AI model to make sure this never ever leans into protected class identity, reasoning or anything like that.

And yes, a program officer's gonna have to put their eyes on every single email that goes out to make sure. But I will tell you the flood of emails that come back in when we both encourage people authentically, like we say, "Hey, we did read your application, and these are the parts that really moved us.

Thank you for doing what you're doing in the world, and here's the specific... a couple of specific reasons why it just wasn't a fit or you weren't as competitive as other applications." And I think people deeply appreciate that, and I have gotten hundreds of no's since leaving Google. I, like as a founder, you just get used to the taste of blood in your mouth 'cause you get punched in the face every

day

-- It makes all the difference to me when someone just, even if it's an AI model, whether I can perceive it or not takes just a moment to just say, "Thank you for what you're doing in the world. I'm gonna affirm something great about what you're doing, and I'm gonna give you a little bit of feedback."

Or like last week, I had a funder who actually got on a call with me and gave me r- tough but great feedback and what a gift. I know that most program officers can't do that. I could not have done that for most of the applicants in google.org, but what a gift if an officer makes some time to be able to give you that feedback so that you can tune your a- y- your proposals and your solution a little bit, so

Jonathan Jackson: Well, I think, that's an amazing point on that it's such a gift when somebody will be willing to spend that time giving you feedback. I just had Eric Ries on the

podcast

Justin Steele: yes. I'm in the middle of Eric's book, his

new

Jonathan Jackson: and, yeah, his new book "Incredible" is great. And so I'll drop a link to that episode, which just got released.

But he talks in the book about just putting out that, gravity . are you there in the world? And I love that idea that you're mentioning yeah, it kind of is painful to take the time to review these things and send out these thoughtful emails to people who've applied for funding.

But you're also responsible for what you're accomplishing in this world and with your time. And I totally agree with you, and I wanna actually separate the thing you said of like not a fit versus not competitive. That's actually the piece feedback I find the most challenging, 'cause I wanna know was a fit and lost versus, no, you like, we legitimately really love this, but couldn't because of criteria." think funders very often conflate those two when they give feedback in a very unhelpful way, ' cause I wanna know when "No, I was on the right track. I should have wanted to have won this. I could have won it, and I lost."

Justin Steele: That's right

Jonathan Jackson: As opposed to, "Oh, no, like it legitimately wasn't a fit. I couldn't have funded this even if I liked it."

Justin Steele: That's right., we had an organization reach out to us just a couple of weeks ago with the idea of they had ran a global competition and got... I mean, they just had to say no to literally 98% of the applicants that applied. And they sort of had this thought like, "Well, what if we actually replied to all that 98%, gave them a little bit of feedback, and then actually connected them to Kindara?"

And said, "Hey, Kindara's actually already run your application through its own sort of search algorithm, and it's identified like these like five to 10 funders or open grant opportunities." I mean, Kindara covers the globe now. I mean, we have funders in Europe, Canada, Australia, Asia our funding database covers the globe.

And so, could we... and I just thought what a powerful thing that would be to not just get a, a form blanket no, but an affirmation that like, "Hey, we really admire what you're doing, and for this reason, like we couldn't fund it through this, but like we've actually taken the proactive step to run your application through a couple of other opportunities, and we think that you might be a good fit for these things."

I thought, how beautiful would that be? So I think there's things we can do as funders to just be a little more proactive, and I think maybe it takes sitting on both sides of that table to have the empathy for what it feels like to, I think every grant maker should do some tours of duty on the other side of the table.

I did it before I started, then I, over time, lost perspective, and I have very viscerally gained the perspective back of what it feels like to be on this side of the table and how vulnerable and humbling it is,

Jonathan Jackson: yeah. I, I like that a lot. I don't know how you could do that at scale, and it's awesome that you've had that experience across both. But I'm 20 years into this. I've gotten, plenty of nos over my career. I've gotten-- been very fortunate to get lots of yeses.

But like, when you really believe in what you're doing and you get a no it's still a gut punch, cause you believe in the idea. In our case, we believe in the local organizations we're supporting and the worker they're supporting . So it's not just a no to Dimagi, it's like a no

to our downstream constituents

Justin Steele: yes, totally

Jonathan Jackson: Like still you get that no. And I completely agree. Like, when you feel that, you're like, "Oh man, I, it, I think it would be very helpful

Justin Steele: Especially when someone like you, you've done your homework, you've written a thoughtful note, like you, you know that you're in the sort of bullseye circle of what would be funded. It's tough. It's really tough. And I think having the human empathy as a program officer to remember what it's like to be on the other side and to be constantly getting the nos is really important.

I think a lot of program officers really do have this kind of empathy, and we're just up against a scale and a structure that just makes it quite difficult interact in a human way. And hopefully some of these tools can allow us to, I know that these are, artificial tools, but they can help us, I think, facilitate some human connection in ways that I think would make this feel a little bit more of a humane process.

Jonathan Jackson: And so let's say you're wildly successful over the next six months. Like you, you see significant adoption, you've got a viable SaaS model for people on Condora, but like usage has dramatically what-- take me through like what practically happens to a $50 million foundation that has had their allegeability, significantly increased you're now matchmaking a lot more efficiently.

Like How should they react, what is that? And maybe it's Condora, maybe it's a different platform, but you know, let's this gets solved somehow. What, would we do to prepare for a better future, we're closing that gap?

Justin Steele: I mean, one, I hope that the capital allocation across the globe feels so much more Vibrant, alive, proximate, like organizations before who maybe it's a new organization with a new idea, but a ton of community backing and credibility and just couldn't be seen just was not legible whatsoever.

I would hope that the capital allocation would look differently and that we would see more funding. But I also don't wanna just be like an efficiency box pushing around inside of like a, a fixed pie, then all we're doing is just we're making capital allocation more efficient, but we're still working within a fixed pie.

And I, think this is where a lot of the individual giving comes in. I know institutions probably don't have a lot of elasticity. We've seen in this global moment that we're in where a lot of government, especially in the US is like, pulling back nonprofit funding, like some funders are stepping up and creating new funding to be available.

The elasticity of institutional philanthropy is not particularly high. But gosh, the elasticity of individual prospecting is just so tremendous. We have a lot of wealth accumulation obviously across the globe right now, and a lot of that funding is just waiting for people to be generous and give.

And I would hope that Kindora would not only help to make capital allocation a little bit more equitable and efficient and that we would see organizations that people like you and me would be rooting for, like m-get more funding and get I think what they're deserved given the credibility and impact that they have.

But I would also hope that we just have more generous people of capacity and that generosity would be life-giving for them. I mean, Edgar Villanueva talks a lot about how, philanthropy is like medicine. Like I truly believe like being generous with other people and contributing to solutions in the social sector is good for people's soul.

And I think people would be happier if they sort of do that calculus of "What do I truly need to kinda meet my needs?" And even if you're a high capacity person, maybe your needs are like quite high, but set aside whatever that number is for yourself and then commit to giving the rest away and be generous.

And I think if Kindora can help facilitate more like trust-based asks where people are like, "Absolutely, Jonathan, like I'm glad you asked. Like I want to be generous with you. I believe in what you're doing. I don't have time to do the kind of impact that you're doing in the world, but I would love to be able to use some of my resources so that you could go on my behalf to some degree and do this impact."

And like I think that would be a beautiful thing. I think the world would be a better place. I think our people would be happier and healthier across the spectrum, like the people both receiving and giving. And I might-- That's my hope is that Kindora can like facilitate growing the pie and within the pie that exists like let's get it to the folks who have the most proximity to their communities and their problems.

Jonathan Jackson: That's awesome and I, I love that. And so what do you view as like your biggest challenges coming up with, you know, achieving growth and adoption of Condora as you look at... 'cause everything Alfred sounds great. I'm trying to raise funding, so like great me, let me go use the platform.

But like what do you see are the challenges, that you're running into or that you imagine you're going to run into?

Justin Steele: Well, I mean, this is a super interesting question. I mean, I think it comes back to a lot of what Eric Ries is writing about in his new book. It's like, well, that solution needs capital. We're certainly generating some of that capital through our own revenue, which is super encouraging. I mean, that's sort of the goal,

is that I would be able to generate enough revenue through the business to be able to fund the growth of the business. But I'm also navigating my own generosity, like fine line. Like I have given away all of our sort of core data for free. If you go into Claude or ChatGPT and add a plugin or a connector for Kindora, it's free.

Like you can go search open grants right now for free. You can sign up for Kindora for a free plan, and you can live on that free plan forever if you want. Our paid plans really allow you to use the AI tools, things like evaluating funders in depth and sorting things and drafting grant applications, and so that's where the revenue starts to come in.

But that means that we're not generating necessarily like the maximal extractive amount of revenue that we could, and I think that's purposeful. Like I think if we're generous with the community, ultimately the community, Eric talks a lot about this in his book, are gonna trust us more.

Like it's a trust-based exchange where people are like, "You are generous. You do care." But then that comes down to okay, well, how do you capitalize this business and then help it to grow? And I think it's super, super challenging, and what I'm finding, we're just starting a crowd raise at Kindora, and we're sort of telling investors like we're not like absolutely committed to getting to a Series A raise, or we're not absolutely committed to getting acquired in seven to 10 years.

If that's not what's best for our users, then that's not what we're gonna do. And we're not precluding that outcome, but that, that collapses your optionality down. Like there's just a whole class of institutional like investors who say, "If you're not willing to commit to an acquisition or a sale in seven to 10 years, then my money's not on the table."

And that creates like a real challenge. And so I think for us, like we have to do all the extra work of how do you find aligned angel investors who, might be philosophically aligned with what you're doing and want a return, but recognize that you're doing it a little bit for the long haul?

And then can we pull off this crowd raise?, My aspiration is could we have the sector actually own Kindara? Like we, we all own it together. If you do a crowd raise, we're going through the Wefunder platform And normally for like a hot AI startup like us, it's like you got Anthropic and OpenAI partnerships and you're doing all the things.

Like you have to be an accredited investor willing to cut at least a $25,000 check to be able to get in on that kind of ownership. And for us we're like, "Nope, our whole mission is democratize philanthropy, so we should be democratizing the ownership of our platform too." Can we put that out there?

And that, but it's really challenging and I think you're, we're not-- we're leaving some of the value that we could grab off the table in the short term for ourselves as a business. We're leaving that on there for the community to grab, and there, there's a fine line there and like my responsibility every day is to make sure this entity is financially viable.

Like it doesn't just create the amazing impact you and I spent the last 45 minutes talking about, but like it, it actually can financially sustain itself so that it can continue to deliver the value. super, super hard, as I know you

know So

Jonathan Jackson: as a side note, I love that you're using Refundo. I was an early investor in

Justin Steele: Oh, that's amazing. Yeah

I've love platform idea. I'm curious too, like I-- that shared kind of co-op model of ownership could be really cool for, particularly for your early customers.

Jonathan Jackson: Being "Hey we're raising. If you think it's worth paying for, I'm creating this like vehicle where if I better it pays back out." We've brainstormed that with several different product lines. We've never pulled it off in the past where we're like, "How do we get the early adopters of these new ideas?"

Like the upside of having adopted them early,

Justin Steele: Yeah. And the, and I think like we all as consumers of technology fear that our favorite platform is gonna get bought by a private equity firm or sold to a big conglomerate and then the thing that we love is gonna disappear, right? This is the enshittification of the internet that Cory Doctorow talked about.

Right, all these things. Like, it's gravity. It's Eric Ries' like, this is just based on the way that we have fiduciary responsibility to shareholder value. Like this is just kind of the way things go over time. And I saw this at Google, right? Over the course of a decade I, I saw us go from founder shareholder control, which Larry and Sergey still have it, but they're not as involved in the business.

And so that sort of like founder protection of sort of mission starts to diffuse out and, when you don't, when you don't have that then yeah, you get these platforms start to become less and less valuable for the users. And I think, if the users actually own the platform then one, they have a stake in sort of the decisions that are made and how the platform evolves.

But also like at the end if the platform gets sold to some conglomerate and you're no longer happy with it, well you also just got a big financial upside and you can take that upside and decide what you wanna do with that. So I don't know. I think it's, we're doing it in a different way and I I'm hoping that...

I feel like I'm in the forest and I'm like, "Am I even on a trail right now? Is this a game trail? Is this a real trail? What's on the other side of this thing?" And every once in a while you catch a glimpse of this five-lane highway, down in the bottom of the valley just like you're like, "Man, I could jump on that highway and just like cruise to the end of this like, financial outcome."

But you know, I don't know. I'm like you. I'm like 20 plus years into my career and I'm like, I've done that. I've been on the five-lane highway for a long time and I feel passionate about like trying to do something a little different. And who knows? Like different isn't always embraced and so different can leave you lost in the woods and someone's gotta get a helicopter and medevac you out of there.

I hope that's not us, but I'm like I'm committed to trying to see if I can

a way.

Jonathan Jackson: my, unsolicited advice having, having gone through this a lot is when people are faced with that challenge of I can kind of see it I think there might be a thing

Don't go halfway. Find the investors who are truly aligned

Who want you to build to hold, not build to sell, how do you do that while building up a SaaS revenue? And maybe,, you don't have that couple million in the bank as fast as you would like, but you have a completely aligned ecosystem from day

Justin Steele: That's right

Jonathan Jackson: opposed to people who are like, "Okay, like maybe if I squint, there's an exit in seven to 10

tell you like instead of that being a 1% chance, it's 10%." they're like, "Well, you said 10%, but I'm it at 50%." And really find that ecosystem because that to me is that's how you become, something you wanna build to hold, you build the right ecosystem from day one.

You screw that up, it's really hard to get back out of,

Justin Steele: That's a fantastic advice, and I will fully admit to being the founder at the beginning of this process who was like, "I'll make myself legible and attractive to everybody." And then you realize pretty quickly in the process of trying to squeeze your way into institutional VC, you're squeezing yourself out of, PRIs and other instruments that might really wanna give.

And I do think it's been a really healthy exercise to go talk to lots of folks, have them react to what I'm doing, and then to your point just decide there's a s- there's a certain segment of investors for whom this is just not gonna be a fit. And you can kind of reconcile yourself to that, and then make sure you haven't collapsed your optionality down so far that there's nothing left.

So yeah, I think that's great advice. I've definitely learned that maybe the hard way. Not super hard yet. I'm, like, iterating my way, I think, to the right answer. So

Jonathan Jackson: Awesome, man. Well, this is a great place to stop. It was a pleasure having you

Justin Steele: yeah. Thank you, Jonathan.

Jonathan Jackson: I'll be cheering you on. We'll drop links to the platform, Kindara. We'll drop links to your article and really appreciate you coming on.

Justin Steele: No, this is great. I really enjoyed the conversation, learned a lot. Appreciate you.

Justin, thank you for such an honest conversation and for saying the uncomfortable parts out loud. And thank you to our audience for listening. A few things were taken away. First, proximity to the problem beats proximity to power. The organizations closest to the work are often the least visible to the people holding the checkbook.

That's the legibility trap, and it's a design flaw, not a character flaw. Second, AI is a first read, not a verdict. Treat it like a junior staff member's pass, flagging where a human should slow down and look closer. Third, a no with real feedback is a gift, and be specific about which no it is.

Not a fit and not competitive are completely different pieces of information. And finally, every grant maker should do a tour of duty on the other side of the table. Empathy is critical, and it fades fast when you're only ever the one saying no. That's our show. Please rate, review, subscribe, and share this episode if you found it useful.

It really helps us grow our impact. And write to us at podcast@dimagi.com with any ideas, comments, or feedback. This show is executive produced by myself. Parthaan Balachandar and Michelle Valencia are our editors. Natalia Glowacki is our producer, and cover art is by Sudhanshu Kanth. A final note in the spirit of transparency: We use AI to assist with guest research, copywriting, and post-production, so a small team can produce a high-quality show.

All AI-assisted content is reviewed and edited by humans, and we retain full responsibility for what you hear