# Rethinking AI: Services-Led Innovation in the $250B IT Market

**Podcast:** AI + a16z
**Published:** 2026-04-01

## Transcript

The biggest area of impact AI's had thus far has been improving individual or small team productivity.
There's trillions of dollars of software infrastructure that's been built over decades that underpins the US and the global economy.
AI impacting, integrating with this whole pool of critical systems and production environments is going to take a long time and new business models to do.
And those business models are debatable across different categories, but this big $250 billion plus cut of IT and security services.
I just think it is a cool place to start that pursuit.
We have to remember 10 to 15 years ago, your internal IT team had to be standing next to a server to do something with it.
This model has improved over the last 10 to 15 years for the most obvious reasons.
Internet, cloud, remote work, software generally getting better.
As all of these technological trends continue and evolve, this like next iteration of the MSP space can just take on a new form where it's very clearly impacting how companies operate through well-built software systems.
These are the companies that keep IT and security running for small and mid-sized businesses across the country.
Most people in tech have never thought twice about them.
The model took shape in the early 2000s when technicians still needed to stand next to a server.
The cloud and remote work changed everything else, but the average MSP still runs on 30 to 35 stitched together software tools, with technicians waiting for tickets in a reactive loop.
Now AI is accelerating and the gap is only widening.
The conventional fix is to sell another SaaS product into the category or run a roll-up.
Neither gets into the guts of how these businesses actually work.
This episode examines a different approach.
Start as a services company on day one and build software into the operation iteratively without abandoning the humans who make it work.
Joe Schmidt speaks with Peter Doyle, CEO of Tree Line.
Today we're joined by Peter Doyle, the CEO of TreeLine.
TreeLine is a modern take on the managed service provider space and really the IT services space, which a lot of people don't realize this is a sneaky big market.
It's a hundred billion dollar market, and in many respects is the backbone of the US software economy and technology economy, bringing these solutions and software providers to the small and mid-sized business.
But that's just the beginning of the story.
Peter, why don't you tell us a little bit more about what TreeLine does?
Yeah, yeah.
Thanks, Joe.
Glad to be here with you.
That was sort of the first thing that fascinated me about this market is it's probably the biggest category in technology generally, like this whole cut of IT and security and now compliance services, but it's probably the least understood, especially from the Silicon Valley perspective.
And so what we're trying to set out to do is basically say, well, with modern technology, modern tools, and now AI, how can we essentially reinvent this category, not fully depart from the services model, but inject software and automation and AI that sits next to humans to fundamentally transform this market and the model of how we service end customers.
And like, I kind of recognize that the scope and sprawl of what's within this category is rather large, and that's why it's traditionally been a services category.
And so a traditional managed service provider or MSP will offer employee and asset life cycle, onboarding and offboarding users, help desk support for all of your employees who need help, insider threat management, endpoint security helping you get through compliance observation periods and maintenance periods, SOC2, HIPAA, CMMC, ISO, FedRAMP, like the scope is huge.
Every acronym you can think of yeah I made sure to start out with all the acronyms.
Good idea.
Good idea.
But basically you can't sassaify that like you have to have people in the loop and you still have to have technicians and expertise sitting alongside software.
But instead of those technicians just using a bunch of software tools, how can software fundamentally and now automation and AI be a core part of that product and how we service customers and that's what we're setting out to build.
Yeah it's interesting you talked a little bit about software and SaaS and I remember when we first talked about this company you know a couple years ago we were on a run through the Presidio and you turned to me my heart rate was about a 178.
And you said, Joe, SAS is dead, which was a really silly take for two venture capitalists on run to be talking about.
But you know, it was interesting.
You kind of talked about that.
You said, hey, there's a misframing here.
You know, people are kind of throwing everything out with the bathwater with that analysis.
Talk to me a little bit about the model that you settled on and why you think it's differentiated at this moment in time versus just everything should be an AI agent.
Yeah, that is definitely meant to be provocative, but it's kind of the perfect time to be proactive.
Yeah, yeah, for everything that's in the news now.
But it's kind of apt, especially for this category.
Like SaaS has been the predominant business model for software delivery for a long time for obvious reasons.
Recurring, high margin, near endlessly scalable.
But in a funny way, a lot of categories, most I would argue, and especially the one that we're in has too much SaaS in a funny way, leverages too much software.
And what I mean by that is when you look underneath the hood of these businesses, like even the best managed service providers that are operating right now is very messy, like even the best ones.
And so you have all these customers that all want the same thing from you, but have their own uniquenesses, their own idiosyncrasies.
And then on the other side, within the MSPs, you just have a pool of technicians that are kind of waiting to help your customers do something in a reactive manual way.
Yeah.
Different expertises, different levels of expertise.
And so to stitch all of that together, they need to use, they use on average 30 to 35 SaaS and software tool point solutions to communicate with customers, monitor environments, communicate internally, everything.
The interesting thing there is that, like at first, when we set out to start tree line with my co-founder Hussein, the initial idea for only a couple of weeks was, oh, let's build a SaaS tool.
We think that automation and now AI is going to be important for this category.
Let's sell it to the category.
And like the funny thing with that is very quickly, we just realized that we didn't want to be the 36th software tool and actually redefine and try to reinvent this space from the ground up with all of these modern technologies in mind.
We kind of needed to go into like the guts of the offering and the guts of how these technicians operate to actually try to build a new model that services customers better.
Yeah.
And say a little bit more about that.
Like, why do you have to go into the guts?
Why can't you just go and offer a software platform to the MSP and just say, hey, we're going to make this all clean for you?
Yeah.
We'll sit on top of your connect-wise or whatever their core system is and make it better.
Like, what about this system?
Yeah.
Makes it such that you need to own those workflows yourself.
Yeah, this is one of my soapboxes for a long time, because like it's one thing to buy software and for a software company to say we have all these customers, but very few customers actually implement and configure the software the way that you as a company even expect them to.
And that's true in spades in this market.
Those 35 tools aren't operating and firing on all cylinders.
They're kind of like half baked, half configured, purchased 10 years ago.
Here's a new one that's purchased that overlaps with this old one.
It's just kind of a mess.
And by extension, like these businesses are 15, 20, sometimes 30 plus years old.
They have all of these legacy processes.
They have data just like spiraling everywhere, very siloed.
And so it's not just like, let's implement a new software tool, spend a couple of weeks doing it.
You really have to look at the processes of how these companies operate, the like initial assumptions they have when they start using a new tool, but then also question them originally.
Why do you have these processes?
Why do you do this?
And oftentimes we find that the answer is, well, it's because we've been doing it for 15 years.
And so like change management is hard.
Why would we change?
Yeah.
And as you think about those workflows you're trying to go after, and maybe this is interesting for Tree Line, but also for others that are kind of going after this like automate services work space.
Like, how do you think about the software that you need to build kind of in-house versus maybe third-party tools and the way to kind of go and capture and iterate on workflows?
Yeah, that's a good question because we definitely can't build everything, especially in this world.
Like we need to partner with Microsoft, Google, Okta, security tools.
Like maybe there's some part of our infrastructure that we just don't want to build, like some parts of a ticketing system.
Like we don't need to build everything, but we need to make sure that the tools that we use and we partner with are either best of breed or just very extensible to plug into everything we're building in a customized way.
But like even more so, the way that I think about it is like you have all of these modern AI companies, and very quickly, they realize that they need very strong customer support, probably professional services, an implementation team, or a bunch of implementation partners.
Like we just onboarded a new ERP system and they immediately threw us to this Zoom video of 10 implementation partners from a company that I'd never heard of before, but that's how they do it.
And so, like the other way you look at it, this concept of a forward-deployed engineer is now very much in vogue.
Like all of this is an admission that AI software, as powerful as it is, it's just as hard to implement and use effectively, especially in like critical systems.
And so we share that view, but we kind of take the inverse, where the day one of tree line was a services company, right?
We hadn't built or written any software.
But over time, if we do this right with well-built software, automation, AI agents, we can continue to pull what we're doing more and more towards being a software company.
Yeah.
It probably doesn't make sense to like go all the way to being a SaaS company because we need humans and technicians in the loop.
But as close as possible to getting there enables scalability and just gives a way, way better product to the customer.
And we can do that in an iterative way.
It's not like one big SaaS app or software application or one big deployment.
It's like very iterative and compounding.
Yeah.
Is that the final kind of, you know, bastion of durable, you know, defensibility against the, you know, the the, you know, it seems like all encompassing, you know, mega labs and everything else out there.
Is it the fact that you have these humans delivering the tools?
Like, how do you see this like kind of competitive dynamic playing out with other players?
Um, and and really like how where do you hang your hat from a durability standpoint?
I I think I think so.
I mean, you can still like there will be a lot of modern software and AI companies that can win big, but you kind of look at what they're doing behind the scenes.
It's automation software and AI software.
Like every SaaS website you go on, there's like a canvas and you drag a node on there, and that's like an integration, and you like drag it to another node, and that's another software platform.
Like it's all automation and workflow builds versus, you know, here is a CRM or here is a system of record.
And so our view is that whatever way automation software and AI like fits your market, go for it.
But these services categories, like I just fundamentally believe for the most part that it's just gonna be really hard to sell pure play software into these categories.
Yeah.
Maybe switching gears, like you came from like a venture background.
It's obviously where you and I met.
Um, you know, you evaluated all these different markets.
What about this market made you so excited to go and run, you know, leave your very cushy job as a venture capitalist um and and decide to get into into founder founder mode?
Yeah.
Um, there's sort of one core insight that um, you know, Hussein and I continued to have as we would we'd just like chop it up and talk about whatever, like Hussein and I have been friends for for 15 years.
Um, and so we just kind of like constantly catch up and talk about work, life, gripe at gripe about our jobs, whatever it might be.
But um, he had a lot of context too on the IT and security services space.
Just he came from originally a security company before going to BRECS and he just was generally familiar with it.
Yeah.
And from the venture capital seat, I was looking at a lot of software that's sold into the space, and there was I think one poor insight that really uh snowballed where everything else snowballed from, and that is this managed service provider space, how IT and security services is delivered today is at least a decade behind where generally modern technology is, which is ironic because this is a technology category.
And with the pace of AI and just software very quickly getting better and better, that gap is only widening.
And we kind of we didn't really have like this huge long list of workflows we were ready to build or AI agents we were ready to build, and we didn't have everything fleshed out on the business model.
We kind of just like saw this huge gap and realized that there was just a lot of white space to navigate into building a big company.
Um so it was really, really from there, and then you know, naturally you just get into it and find and navigate to the right way.
But we don't we we definitely didn't start day one with this like perfect, pristine view of here's the two-year roadmap that we're gonna execute on and like here's where we want to be by 2030.
Yeah.
And obviously, you started with, you know, kind of a dual prong strategy of kind of inorganic growth partnership with yeah, you know, uh MSPs, and also alongside, you know, strong kind of organic growth and what you want to do there.
Yeah.
Why why why even start with the inorganic strategy at all?
Like, what's the advantages that come with you know partnering with an existing firm and modernizing versus just starting from scratch as most technology companies do?
We very much want to build tree line by combining strong industry insider expertise with like new point of view and perspective for lack of better phrase, uh, industry outsider points of view.
Um, and so very quickly, once we incorporated the company, we wanted to merge, we did merge with a couple select traditional service providers, less to tap into their revenue and and their cash flows and more to say, well, we need strong industry operators, we need experienced technicians because the technician team is very much a part of of our offering.
Um and over time we'll we'll certainly continue to opportunistically look to merge with and partner with additional traditional service providers and bring them into the fold of how we operate.
Um, but over time and and and starting even now, like we're investing heavily into organic growth because if we're building a scalable offering and company and differentiating in an otherwise undifferentiated category where it's essentially commoditized to a very low level of service, why not invest into organic growth and just like speak to the end customer ourselves?
And I think that's kind of the like you you hear a lot of talk about traditional roll-ups and now AI roll-ups, and that means a lot of different things to different people.
My view is that over indexing too much on, let's just call it an acquisitive growth strategy implies that your the crux of your business is focused on financial engineering and using AI as like yet another private equity tool to improve margins.
And I believe that can work.
We just want to try to reinvent this category and systemically innovate versus build a higher margin traditional service provider.
Like there's a much longer compounding roadmap we're going after.
Yeah.
And maybe like it'd be so interesting to tease this out too for the customer.
Okay, obviously, people talk a lot about AI roll-ups and like, you know, adding, you know, adding technology to traditional services organizations.
But like, how does this manifest for your customers?
Like, what's how do we change the way that they consume kind of ID services?
Yeah.
Yeah.
And again, this is why I like this model, because it's not some singular software application.
We're building in multiple fronts.
Where we've started is behind the scenes, how can we improve how technicians operate and respond to any customer request, but also be more proactive.
And so what that looks like is a lot of internal technician-facing tooling to say, well, any ticket, issue, alert, whatever it might be that comes into the system, when and where can uh automation and AI agents at the very least augment and at the most replace like the need for a manual workflow?
The core flow of how traditional um service providers operate is they have a bunch of customers, and those customers just throw a bunch of issues and tickets and requests to the MSP.
That can be we're onboarding multiple people on Monday.
Can you get them set up in all of these systems?
It could be an automated machine-generated alert from like CrowdStrike or some security tool that says you need to look into this vulnerability or this issue.
And so the technicians are kind of sitting there waiting for one of these.
And it's rather reactive.
And so even if it stays reactive, we can equip them with a lot of really interesting information and context and automation and agent tick tools to help them be really efficient with that.
But then also even more so be way more proactive.
Like we noticed that this was a problem before you submitted a ticket.
And so that goes to your question.
Like customers see right off the bat, improved service and just like a better experience, like my issue was resolved immediately before I had to say something or it was resolved in one minute, whereas historically it took 30.
That we will continue to iterate on forever.
But because of our model, we can also build towards the customer.
What interfaces, what information, what additional products and services can we sell and equip our customers with to give them better visibility into what we're doing, to help them leverage um AI themselves.
There's like all these ancillary categories and ways that we can engage with customers where once we quiet as much as we can the like IT and security noise, like you can never fully quiet it.
But like then, where does the customer relationship go and how do we deepen it uh in in really interesting ways?
Yeah.
You know, we've talked a lot about, you know, the kind of false choice that organizations have, right?
You either, so your point on just talking to the signation workflow in an outsourced manner, you have an outsource provider providing IT services, um, or you have a big complex internal IT infrastructure and you handle these tickets on your own and you build all these things yourself.
Like, why has that been the choice organizations have to make?
Is that the the right choice, or you know, why why is this the way that's operated?
There's no generalizable right answer, but like the reason why those are the only two options is like kind of a vestigial trait of where the industry came from.
Um we have to remember 10 to 15 years ago, uh, your internal IT team had to be standing next to a server to do something with it, or your traditional MSP or the precursor to what an MSP is today had to be within driving distance.
Like this model has improved over the last 10 to 15 years for the most obvious reasons: internet, cloud, yeah, remote work, software generally getting better.
Um, but basically it it's it's kind of stayed the same where it's like still this call and response from the customer to the MSP or the customer realizing that because of their scale or complexity or for whatever reason, they want internal people.
And so you just still have these two options.
And our view is that as all of these technological trends continue and evolve, and now with with AI progressing as rapidly as it is, this like next iteration of the MSP space can just take on a new form where it's very clearly impacting how companies operate through well-built software systems.
And that's what we're trying to offer to the category.
You know, it's something else that you I found interesting that you talked about is like the the biggest kind of you know hindrance to AI progress and uh you know isn't exactly the model progress, but it's actually, you know, the rate of kind of integration into core systems.
Um maybe talk a little bit about that and like how the tree line model, you know, allows you to take it most advantage here.
The biggest area of impact AI's had thus far has been brand new, like vibe-coded or otherwise apps, new applications, or these models improving individual or small team productivity, right?
Um the biggest well of impact that I think is is just starting to be tapped is there's trillions of dollars of software infrastructure that's been built over decades that underpins the US and the global economy.
AI impacting, integrating with, um, modernizing, and in any way like interacting with with this whole pool of critical systems and um production environments is gonna take a long time and new business models to do.
And those business models are debatable across different categories.
But this big 250 billion dollar plus cut of IT and security services, I just think is is a cool place to start that pursuit with everyone else that's trying to do it in different areas.
And it again goes back to like digging into the to the guts of the industry, the way that we dig into the guts of the business model and say, what can we integrate with?
What should we replace?
What software do we buy?
What do we build?
Like it's messy inherently, which is again why we need this unique model.
Yeah.
And when it for the customer, does this lead to lower costs, better service, both?
I think the idea is both, certainly over time.
Um, where as we continue to do um uh everything that we we set out to do on the core IT and security front, like, yes, we want to pass on a lot of those savings to the customer, but also, like I mentioned, just evolve the relationship.
It's not like, oh, we'll take down your your per user cost and we'll just kind of quiet everything down and that's our our business.
The hope is that we still grow, not necessarily in like a dollar value way, but just like in a relationship depth depth way with the customer.
And the byproduct of that is like, yeah, changing pricing models and engagements with businesses.
Um, but also, yes, along the way, like every pursuit that we have in the category should be what's in it for the customer, why do they care and why are we doing this for them?
As you're architecting, you know, the the platform, how do you think about like the right way to do that when everything on the kind of underlying underlying fundamental side is changing so rapidly?
Like as AI models improve or as the different providers improve?
Like, how do you think about like the right way to structure all of this such that you don't have to just rebuild everything every six months?
Yeah, it it's a good question because the way that we're trying to architect everything is like, yes, if if AI progress stopped fully today, we would still have a 10 plus year roadmap to execute on.
Um, but to the earlier imagery, I suppose I was giving of pulling what we're doing from being a services play to as close to a software one as possible.
Yeah.
It's basically just let's fold in new technology as it comes down the pipe and as we can leverage it.
And so maybe today there's an AI agent that we can see wanting to build, but perhaps the AI models and capabilities aren't there yet to reliably allow us to put it into production.
But maybe in a year it'll be very easy to do so.
And that's kind of how we want to like not only um proof ourselves, um, future-proof ourselves from whatever happens with with AI and just modern technology, but like actually be on the forefront of it.
And day one, it comes out, adopt it and implement it.
Yeah.
Do you think um, you know, these kind of AI roll-ups or these energetic strategies like can become venture scale outcomes?
My hunch is is no.
I do think that to build a compounding business that is actually continuously innovating while compounding, you can't just rely on that that acquisitive growth.
But again, like I said earlier, like it's not to say that those models can't be successful.
Like we look at these businesses all day long.
There's a lot of low-hanging fruit.
There's a lot within operations and within what goes into cogs and operating expenses that AI can brush away.
Um, but again, that's just not it in our view, it's it's a little bit more of an incremental approach to creating equity value versus actually creating some outsized opportunity to change the space.
Do you think there will still be a traditional MSP in 10 years or 15 years' time?
I I do.
I mean, these industries move so slowly, despite, you know, us being in Silicon Valley and watching all of these um wild takes of how fast AI is moving, however right or wrong they are, these industries take a long, long time to catch up.
The composition of the industry will change.
I think there will be way less fragmentation, bigger winners, but that long tail is just always gonna be there.
You still have a lot of MSPs out there that are driving to their customers and that are uh, you know, like don't even have an email address or managing server racks or whatever.
Yeah, call me, I'll go over, I'll fix it.
Like advising their customers not to move to the cloud if even if it's like the most obvious thing from our seat to do so.
Yeah.
If you fast forward that same time frame, 10, 15 years or even longer, like what's the the biggest version of tree line?
Is is it an expansion kind of across IT, outside of IT?
Like, what's the business look like in that?
Yeah, I mean, we we consistently debate internally what to even call the future of it, because like we don't want to rely on this like MSP or traditional um phrasing, because like, yes, the core way that we currently work with businesses is within IT and security and now compliance.
But just over time, what does becoming the most impactful, highest trust third-party partner for end businesses look like?
What is that?
And so there's just kind of this huge area of like how these businesses can adopt modern software in AI, what they're gonna need in the future once we quiet some of these things.
Um, I could I could sort of sit here and pontificate for a while, but the fun thing is that like we don't really need to figure it out just yet.
It's just let's let's continue to be on the forefront of of what we're affecting now within this core space.
And a nice byproduct to that is we're now capturing so much um good like information and data around how we operate, how we interact with our customers.
And we can do so much with that information over time and through building trust with the customers we serve.
Okay, so maybe going back to the like kind of false choice between like internal IT teams and outsourced uh MSPs, like I find it interesting that you went after like this outsource problem.
Um, why did you pick the outsource problem?
Um, why is it you why do you think this is the right answer?
And like what's the what's the biggest issue that we're really solving for here with with these providers?
There should definitely be next generation products that try to replace legacy ticketing systems and and tooling systems.
And you, of course, naturally are seeing a lot of that um being invested into within Silicon Valley, and Andreas it's made a lot of those investments and we can integrate and partner with those no problem.
Our view is that even for modern venture back tech companies, but also for just the rest of the US manufacturing, healthcare nonprofits, everyone needs really strong IT and security.
And if we have a really shiny new modern um point solution or ticketing system, like the adoption rate outside of Silicon Valley is gonna is gonna be low for a long time.
So let's meet the industry where they are.
Um, still in many ways look um like that traditional provider, but behind the scenes and and slowly over time, pull these customers forward with us.
And you can't just do that, I believe, by selling a software product to them.
When you were evaluating the market that you went after with treeline, like this MSP IT services space, was there any like kind of like spectrum of, you know, least interesting kind of services, you know, businesses to try to go and bring AI to to most interesting?
Like was there some sort of framework that you developed that helped you kind of pick this market, or was it just like, hey, I know this MSP market, I think there's an opportunity here.
Let's go after it.
It was the former, but retroactively, I I realize a lot of reasons why it's a good space because there's a spectrum of some services categories where technology and software can barely move the needle, like uh someone going to your house and fixing a pipe, like the HVAC space.
But then ones on the other end of the spectrum that are like really susceptible to AI coming in and and wiping it away.
Um and I think that the MSP space is, you know, maybe not squarely in the middle, but kind of in this this middle pack where there is and will continue to be so much complexity to how we we operate within the market.
Um, but we're not so far over on this end of the spectrum where in five or 10 years, we're at risk of AI like wiping this away.
Like IT security compliance services uh is going to be thorny for as far as I can see.
Okay.
So you talked a lot about how, you know, tree line can drive adoption within, you know, obviously your company and the tools that you're using.
Um it's been fascinating to kind of observe the big labs, obviously anthropic, you know, talking about publicly or open AI talking about publicly about the four-deployed engineers that they have and how they're building different tools for their larger enterprise customers.
Like, what does that kind of tell you about, you know, the way that adoption's working and how you're how these big companies are accelerating AI right now?
Uh I was glad to see it because I really don't think businesses should be afraid to have people, services as a part of their offering to the market.
And even if you have these leading frontier labs going into Goldman Sachs with a hundred people, they're recognizing that yes, their their growth rate and their scale is is unprecedented, but they're still realizing that they need to throw people at the problem.
Yeah.
And so we we're internalizing that too, but we're not reluctantly doing it.
And I don't think they are either, but it's more just we need this, and we think that we can um still hit scale and act and operate like what a traditional software company has operated like with people in the loop.
And I think that that's just like an important lesson in realization for a lot of companies that are building right now to have.
Yeah.
Okay, spicy take time.
What companies should be most afraid of the labs?
I think the the companies that don't have um wide company appeal and usage are are at are most at risk because to my earliest point, um and white company appeal and usage in the sense of like wide adoption across a large enterprise.
Wide adoption and just entrenched in how a company as a an organism operates, that's just really hard to rip out like whether it's a system of record or whether it's this or that like if everyone's got a seat and everyone's using it, um, that's just innately very sticky and very hard for a model company itself to replace those companies will probably just use the capabilities that the model companies have.
But individual and team based productivity is skyrocketing with these products.
Um I see it within treeline and I just like see it with with my my cohort of of um friends and and colleagues.
Like that is a very shaky, disruptive area.
Um, and if you're swiping a credit card to buy a few seats for your team or or for yourself, and and it's something that's like not core to how your company as a whole operates, I think that's where you're gonna be in trouble.
Yeah.
And do you think this uh whole SAS is dead thing is overblown?
How do you how do you kind of see this?
I know this is where we started our conversation with our run and you saying it is.
So do you still believe that?
I I do.
I I think that like I I believe in uh the future and like the overall power of AI and where it's going.
That's not to be discounted.
But just how the world slowly moves incrementally to adopt this change is just gonna be the biggest constraint.
And that's just gonna take way, way longer.
And I do think that it's harder to sit um in San Francisco and like being on Twitter and actually clock that in the right way.
There's just like a natural constraint to humans changing.
And that's just gonna be a huge limiting factor.
So it's dead, but not dead quite yet.
It's gonna take a while.
Ask me in 20 years.
Yeah, yeah.
Okay.
20 years though, on four of my stock picking strategies.
Yeah.
Um okay, quick uh quick lightning round, maybe to finish us off here.
Um, if you were in a Harry Potter house, which one would it be?
Uh no, it's oversed, but Griffindor.
Okay.
Best run in San Francisco and best trail run in Marin.
The 10 mile loop uh starting at the east side of the panhandle all the way to Water and Back uh in Marin and be the um Tennessee Valley five mile loop.
What's your shampoo of choice?
Uh I was gonna say Dr.
Browners, but that's the body wash.
Uh good.
So you're using body washing your old body.
I don't know.
Next next question.
Um, the best book you've read in the last 12 months.
Count of Monte Cristo.
Count of Monte Cristo again.
Um, and your favorite song that you've found recently.
No song specifically, but that whole new Fred again album.
Yep.
Favorite partner in entries in Horowitz.
No comments.
And with that, thank you, Peter, for coming on the pod.
Thanks, appreciate it.
Yep.
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