How to Build for AI Agents and a Claude Code Second Brain in 25 Min | Ryan Wiggins

Our job is being available wherever customers are. In the 1950s, that meant

customers are. In the 1950s, that meant building a bank branch. In the 70s, that meant building an ATM. In the '90s, that was a website. In the 2010s, that was a mobile app. In the 2020s and beyond,

mobile app. In the 2020s and beyond, that is going to be APIs and set of services that you can connect with what I call the conversational interfaces of the future. I pulled this together and

the future. I pulled this together and it was almost 5 million words from anything that was touching my surface area over the last 5 years and built that kind of as a knowledge base that then served as the foundation for everything. When I run a meeting, pod

everything. When I run a meeting, pod tells me, "Hey, in this meeting, you were doing this exact thing that is on your performance reviews." Of all the exacts I've talked to, this is the most impressive system at a high level I've seen.

So, yeah. So, why don't we get right into it? Um, do you want to walk us

into it? Um, do you want to walk us through Mercury's MCP and what you can do with it?

Yeah, 100%. So, Mercury's MCP is something we just recently launched. Uh,

it's available in the, uh, Claude app store and it has a a URL directly if you're taking it into different tools.

But if you go into Claude, you go into the connectors, uh, you'll be able to find the Mercury app here. I already

have it set up, so we're just going to jump right in. Uh, how Mercury MCP is useful is you can ask natural language questions about your bank. Something

like, "Hey, Mercury, look at my spend over the past couple of months and see how I could save some money." I like to use Whisper Flow for some things like this. And so uh what's happening here in

this. And so uh what's happening here in the background is this is connecting to our API and pulling the information that would answer this question and being able to take that and answer it pretty flexibly uh as well. MCP is a readon

version of our API to kind of keep it safe. But uh we launched this about six

safe. But uh we launched this about six months ago and we're really excited uh with how it's going so far.

And this is not your real account, right? Or

right? Or this is a this is a sandbox account for this demo and so it's going to have real data. Uh, and one of the nice things

data. Uh, and one of the nice things about Mercury is we kind of have a great demo environment where we can send some things here. So, it will show some real

things here. So, it will show some real data, but it is not my personal data.

Okay, $500 a month, man, that's a lot. I

subscribe to a lot of AI products, but I don't think I pay $500 a month.

You know, I think this is modeled after a startup, and some sometimes startups are spending quite a bit. and uh you know um okay so what we see here is uh you know Mercury is bringing in some of

the finance data into claude and claude's actually just launched a new update that has actually shown some of the data here in a pretty nice way it has some tables it has a bunch of different information but using this I

can really get a good sense of where my money is going and where I could be saving some money here so so the API is read only assets so so I can't be like hey cancel my Netflix subscription or something do that Yeah.

So, Mercury has an API uh that's broadly available and it matches exactly what you can do on the web application or the mobile app uh and that is a read and write but our MCP and the thing that is available in cloud and anthropic is read

only uh just to make sure that people have control and security over their finances.

Got it. So, what have like businesses or people's favorite use cases been since you launched this SAP? Has adoption been great and you know what's it been like?

One of the things is that we've been really surprised how people have responded to this. You know, Mercury generally is building uh banking and what we call uh radically different banking for entrepreneurs and ambitious

people of all kinds. MCP is just one of the ways that uh builders today are bringing in their finances to their different workflows. And so we've seen

different workflows. And so we've seen uh all sorts of people. One of my favorite examples is I was talking to an animation studio here in Los Angeles uh and there's a specific tax code and when

they connected their MCP into uh their finances and started asking questions they were able to find some tax breaks that they didn't know about otherwise that to me highlights the example of how MCP can be used. It's context about your

business that's unique, novel, but then your insight as a business owner and someone who is operating your business.

How those things come together becomes quite powerful. And uh we've heard a

quite powerful. And uh we've heard a couple a couple people have saved uh over $1,000. We have a a running

over $1,000. We have a a running scoreboard of this number and it's getting quite high.

Oh, already. Okay. So, so like two questions is like what are my top monthly expenses and uh where can I save? And another one is like where can

save? And another one is like where can I save money on tax? Right.

Yeah. Yeah. Exactly. I would say most people really love asking like how can I save money on spending? What could I be doing to optimize my spend? But one of the things about Mercury and our API is it offers all the information that you

have on your account. So it even offers things like your EIN, your uh business address and so you could have this kind of source of record of your business identity that then uh can come into your workflow whenever you need it. How many

things do you apply for where maybe you need your EIN? It's hard to find that.

And so uh we've tried to make that all available within the MCP uh and make it a great experience as part of it. It's

been really cool to see how people are creating their own dashboard and their own kind of workflow on it. And I think that's probably one of the best use cases for it is just what happens when you can bring your financial data wherever you are.

All right, dude. So, from one product person to another, let me ask you some hard questions, man. I'm okay. So, a lot of people are like, "Oh, I got to get my product agent ready. I I got to build an

MCP." But I feel like building MCP is

MCP." But I feel like building MCP is like the very last step, right? Like

like what are some steps that you took before even building MCP to make it like really easy to use?

Yeah. Yeah, I mean first Mercury uh really kind of has taken the journey that a lot of banks have taken over the last 20 years which is it starts with a great website. Uh the Mercury.com

great website. Uh the Mercury.com experience and you can see it at demo.mmercury.com we believe is one of

demo.mmercury.com we believe is one of the best banking products that's on the market. Our mobile app pairs super well

market. Our mobile app pairs super well with that. And what we're asking with

with that. And what we're asking with MCPS and API is what is the 2020s interface going to be like? And we think it is going to be uh you know kind of portable uh in a much bigger way. And so

you know this MCP is built on a huge foundation of the products that we built at Mercury. Things like really reliable

at Mercury. Things like really reliable uh depository accounts, treasury accounts, uh credit cards that people love, user management and uh different spin controls and things like that. And

so, uh, all of that stuff then comes into our API where when we built this MCP, we thought a lot about the experience of it. One of the things I found using a bunch of different MCPS was it's kind of hard to log in.

Sometimes you actually have to like go into like a text file or a config file to set up the server and set up your uh, credentials or whatever it may be. So,

we tried to make it like logging into the web app. We tried to make it an OOTH experience. It's just kind of one click,

experience. It's just kind of one click, same password. uses multiffactor

same password. uses multiffactor authentication to have that security that you need on a bank account, but it's seamless once you've connected it within cloud. It just works like it's

within cloud. It just works like it's your web dashboard. And that's what we think a banking experience should be like. Got it. Okay. And and of course

like. Got it. Okay. And and of course having like really good API coverage for like core workflows and you know the the data flows and stuff, right? like um um did you also think about like

documentation that agents can read or like any stuff like that or Yeah, I mean this is the journey we've kind of been on is we've been thinking about our API for a long time. Uh really

Mercury launched with an API and it's been around for a couple of years but over the last uh probably six months we've seen a huge amount of adoption for people uh creating API tokens wanting uh requesting into customer feedback

channels that they want to be able to bring their data elsewhere. And so what we've tried to do is uh have the API have high coverage, but then make it super useful wherever you go. So you can do things like OOTH or MCP. Uh and so it

starts with that foundation, but then it's really about where are customers and where can you meet them.

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All right, dude. Well, let me ask you another hard question. So, like like I said, Mercury's app is like the most beautiful the most beautiful user interface for a bank that I've used. And

um I don't know. Does it feel kind of weird that like now people are like, you know, now I'm getting my Mercury data through Jenke openclaw instead of using the app or the product like that, you know, may maybe you actually see like DA

going down a little bit because people are just like using these integrations instead. So, so, so how do you think

instead. So, so, so how do you think about um are you worried about where people like a world where people actually stop going to mercury.com and just go talk to your AI agents instead?

Yeah, I mean the short answer is no. I I

think that uh our job as a a technology company that is building incredible banking software is being available wherever customers are and meeting uh that moment and in the 1950s that meant building a bank branch. Uh in the 70s

that meant building an ATM in the '90s that was a website. In the 2010s, that was a mobile app. In the 2020s and beyond, that is going to be APIs and the set of services that you can connect with what I call the conversational

interfaces of the future. Uh I think that that we're already in a platform shift and we need to show up in that way and we need to make it available. And

you know, I was thinking about this for myself. I'm a consumer. I use Chase

myself. I'm a consumer. I use Chase Schwab and it is so hard to get my data out of those products and it makes me so angry as a consumer. I just really wanted to build something that I believe

was good for uh the experience of managing my finances and we try to do that every day at Mercury and like uh you know I I think it's actually great if people are saving time and able to do more have to spend less time in our web

dashboard. It means that they're able to

dashboard. It means that they're able to to spend time building what they want to build.

So so how do you like uh how do you like measure success for like a product like the MCP like because you know like a userfacing product is like you know uh DAU and like retention and stuff like that right? So, so, so I guess it's like

that right? So, so, so I guess it's like how often the agent calls your MCP or Yeah, totally. I mean, you know, uh,

Yeah, totally. I mean, you know, uh, it's funnels all the way down is is maybe one way of putting it. You know,

at the core, it's are people using it?

When they discover it, are they hitting errors? Are they going through? Once

errors? Are they going through? Once

they set it up, do they have multiple engagements with it? And then over time, do they retain? Do they expand? And did

they uh keep using it? And what we found is once people set it up, they really love using it. It's kind of exactly the use case you described where it becomes almost a week a daily, weekly or monthly workflow for them. And that's something I think we're really excited about. Uh

because it's something that maybe we wouldn't have built ourselves, but actually people can build on their own.

Uh so uh yeah.

Yeah, it's like way more convenient, man, because now I can get the open cloud to push stuff to me from Mercury.

Before I have to like remember to go to go login and check my stuff, but now like every week it pushes stuff to me.

So like and I can give it I can tell you to give me a pep talk. And the other the other thing is like it has my market data, it has my YouTube data. Yeah,

100%. I love that. Okay. So, um, okay, one one last question about the MCP. So,

there's been a bunch of tweets out there about saying like, oh, you know, MCPS are dead. It's like there's like too

are dead. It's like there's like too much bloat and too much context in there. Let's just build APIs and CLI

there. Let's just build APIs and CLI tools and all that kind of crap. Like,

how how do you think about how you think about this?

Yeah, I mean, there's a lot of noise and like the world's moving pretty quick and you know, one of the things that uh I think is yes, inevitably I use MCPs, they clog up a ton of context. We are

going to build a Mercury CLI and this is actually something we're going to release in the next couple of weeks and so uh breaking news here with you Peter.

The Mercury CLI is coming. We're really

excited about that. But one of the also ways of thinking about MCP is right now it is hard when someone is using one of the consumer products chatbt and anthropic to use the services like an

Mercury in that experience. APIs and

connecting to APIs directly is super hard. how those platforms have chosen to

hard. how those platforms have chosen to integrate is a first-party app ecosystem which you set up and work directly with them but then also the custom MCPs and I think that sort of uh app layer and

distribution layer is so critical in this platform shift if you look at like Apple they don't they don't allow third-party apps MCP is the third party apps of this ecosystem and I think going to make a big difference in how new

products can come to market and uh open up what is possible for different companies interesting okay so you think about MCP is made a little bit more accessible to the mass market and then the CLI maybe for like the dev the devs or like people who really want to

Yeah.

optimize their context. Yeah.

And it's particularly because OpenAI and Anthropic have gone in on the MCP ecosystem and they grid apps that are built on the MCP structure. And so by them choosing that uh method, you know, it's kind of become a distribution

service and the common one. And so it's not going away anytime soon until something can replace that. But what we see is kind of at the power user at the premium maybe not even the premium side the the you know deep builder they

definitely want tools that are much more flexible like CLI skills different things like that and I think that's something we're definitely going to meet them with.

Got it. Yeah. Yeah. I I feel like MCP is the only thing that open an can agree on.

Yeah, that might well No, they seem to agree on each other's product uh but after each other.

Yeah. Yeah, they seem to Okay. All

right. Well, why don't we shift gears a little bit? Let's talk about um how you

little bit? Let's talk about um how you use AI in your life as a product exec.

Yeah. Do you want to talk about like how you just use these different tools uh day-to-day or maybe like show us some work workflows?

Yeah, totally. All right. So, maybe just quick summary on my role. Uh I lead a product team at Mercury about 20 different products that cover what we call our software side of the experience. It is how do people discover

experience. It is how do people discover Mercury? How do they use it every day?

Mercury? How do they use it every day?

How do they expand? I've been here about five years and I also work on the data team. I've worked on growth here at

team. I've worked on growth here at Mercury. And so I have a ton of context,

Mercury. And so I have a ton of context, a ton of information, but you know, when I'm making decisions day-to-day, it is quite hard to access. And so I've been using cloud code to build out what I call uh my second brain. Uh and so I'd

love to walk you through it if that's okay.

Yeah, I'd love to see it. Yeah.

All right. So maybe first I'll show a diagram because uh uh then I can show you how it actually works. So So at its core, I uh built a what I call the context layer or the knowledgebased structure. Um this is essentially a

structure. Um this is essentially a download of all the information at Mercury from my five years at Mercury.

the company strategy docs, every spec that's ever been written, every query that's ever been run. I pulled this together and it was almost five million words. I I think I cut some for for this

words. I I think I cut some for for this just to make sure I didn't share anything too sensitive. But I tried to get all the information that has ever been created from anything that was touching my surface area over the last 5 years and built that kind of as a

knowledge base that is stored on a local file system. that then served as the

file system. that then served as the foundation for everything that I built on top of that which is kind of a workflow where every morning I open up terminal I go to cloud code and it

references a memory that has been built and is updated every day it references that knowledge base using QMD and Toby's kind of local indexing solution that he has built out and then it uses claude

hooks uh claude hooks uh to inject that context into every question I ask so I ask a question like how's activation trending I'm not just asking that question I'm asking that question with

all the knowledge and history of mercury going into that question and it's actually injected into uh into each request and it has made each request much much better. Um you know then uh

that uh kind of system plugs in to a set of different things skills that I built out which are kind of patterns like an analysis or building like a small little app for myself or learning uh kind of coming back and feeding back into the

memory system. MCP integrations. I plug

memory system. MCP integrations. I plug

in all the kind of core tools I have.

And then I have some things in workflows that are multi- aent teams. I, you know, can send in like a full analysis to go understand all the data, go think about all the problems, go run an analysis, go kind of discuss it, and then come up

with a report. And that is kind of the system uh that I call my second brain or mission control. And it really goes into

mission control. And it really goes into everything that I'm doing as I use it.

I'm in cloud code kind of all day, all the time. Uh and so this is kind of

the time. Uh and so this is kind of system that I have. And I could give you kind of a a preview of it if you want to see it.

Well, this is like I think of all the execs I've talked to, this is the most impressive system at a high level I've seen because most exacts are just in meetings all day, man. They don't have time to throw this stuff. So,

yeah. Well, what one of the interesting things that I I I have done as part of this is I've tried to make it so that I can pay more attention to meetings. So I

have notion transcribe it and I that feeds into the system so that every day at the start of every day I get a brief of what's my calendar what's on linear github slack uh what's the kind of meetings that I have and at the end of

the day it summarizes those meetings gives me the action points and other things that I have and so I've kind of really built this into my like workflow where I start the day I end the day and then like I start the week I end the week uh using this it has been so

surprising for like the knowledge and context that it has unlocked for me uh you know uh all sorts of things.

Yeah, you show me cloud code, dude.

Like, how do you do some of this stuff?

Okay, so what I have here is my cloud code and kind of the entry point to most of my workflows. So, I would start with a question like this.

Hey, knowledge base. I'm here with Peter. Uh, I want to operate in safe

Peter. Uh, I want to operate in safe mode for this conversation, but I want to show it how we would use some of the knowledge base that we have to be able to answer questions. One of the things Peter just asked me about is how is the

MCP doing? Could you answer this

MCP doing? Could you answer this question and try not to reveal anything sensitive? Yeah, I guess because all

sensitive? Yeah, I guess because all that information is locally, it's like searches super fast fast too, right? So,

exactly. And this the QMD the nice part about it is it's indexing and so it when it searches for something like MCP product traction growth, it's not searching for those terms, it's searching for the concepts of those

terms. So, it uh returns adjacent stuff.

Let me actually show you this and I'll I'll ask you to black this out uh because I can show you what it looks like and but this will stuff will be sensitive. So, it references like

sensitive. So, it references like strategic context which is a specific doc. uh it references you know the

doc. uh it references you know the growth product team check-ins that I have team charter uh yeah like different uh person's onboarding doc you know so it's able to pull from about like 20

different docs so that that context is inserted into uh the actual uh uh query that I run and so when I'm running something like this it is just again

like totally enhanced uh and yeah so here we have an answer uh on our kind of knowledge base I asked a question it brought in a couple of different uh pieces of content text from the knowledge base and then uh gives me an

answer and you know if I wanted to go run analysis I could actually trigger it from here. I have it hooked up to

from here. I have it hooked up to metabase and RBI tool omni to be able to run those and so uh this is kind of a system that not only has knowledge but it also has tools to be able to go take actions and run a full analysis get back

to me insights on that.

What is kind of like the proudest skill that you built that that that you can share with with us at this time is is there something that's not super sensitive? Yeah,

sensitive? Yeah, I mean I I think the uh one of the things that we built internally at Mercury kind of based on the system was an automated data analyst. I have spent five years at Mercury answering all

sorts of questions about uh you know how is growth going, how many people were how many people applied yesterday, how many sales leads have converted using this product and we built a uh you know

what I would call a an AI agent that can answer about 80 to 90% of the questions that most XFN teams are asking at Mercury. And it really kind of started

Mercury. And it really kind of started from me being able to prototype it locally, built the confidence that it's actually accurate enough and then go kind of peel that off and ship it internally to the company and it's something like that is really really

unlocking a bunch of speed and capacity.

So that's probably number one. I would

say that's like a pretty cool use case.

Number two uh is it's really been surprising how good of a coach it is.

you know, I get a performance review every six months and uh sometimes it is uh you know, high level themes or kind of abstractions, but when I run a meeting and it tells me uh one of the things I'm working on is that maybe I

jump to the solution too quick. I don't

probe enough about the question or work with my team enough, it tells me, hey, in this meeting you were doing this exact thing that is in your performance review. So, it can kind of keep me

review. So, it can kind of keep me honest at a much faster frequency than any other system can. And uh it's quite interesting just how that has actually changed my behavior because I know that

uh there's actually like a a a system I'm going to have to be accountable to uh that is shaping my behavior and uh I can tell you my manager and my people partner are so happy about this. Uh it

is definitely making the feedback land.

Oh hang on. Let's let's talk a little about how that works. So you have like granola or something take the meeting notes and then you feed it into the clock code and then it just gives you feedback after every meeting automatically. Uh so at the end of the

automatically. Uh so at the end of the day I essentially ask it I am prompting it and so it has the ability to pull the information from slack from linear from notion transcriptions uh or any other

docs that I've created and then I can ask it to summarize things and usually that's a conversation takes about 15 minutes but it's like hey did I have anything left over today that I need to take action on? Uh is there any anything that showed up today that I should be

thinking about for my performance? And

like you know it I go back and forth with it and it finds all sorts of things and man it's a it's a It's a great accountability measure is the way I would put that.

Yeah, that sounds great, man. Okay, so

so you have it hooked up to like Google Docs and everything so you can just like pull all the stuff that you did during that day, right? Is that how it works? Got it.

right? Is that how it works? Got it.

Okay, got it. Wow. Yeah, I I need that too. I

got it. Wow. Yeah, I I need that too. I

get feedback that I move too fast too.

Like it's like you move too fast, you got to keep bringing people along and then I always forget about it. I always

like move fast. So someone to remind me.

Yeah. Well, speaking of uh stats, dude, do you want to show us um Mercury Insights? I I think it's like more userf

Insights? I I think it's like more userf facing, but yeah.

So, one of the things that we've been thinking about is how are our customers, the startups of uh of America adopting AI tools and uh what's kind of changing as the ecosystem changes. I noticed

about six months ago that my behavior really started trending towards uh using anthropic cloud code and kind of building my workflows on that. And uh we did this analysis and looked at for new startups which Mercury gets a great

signal on because we serve one in three startups in the US. But we looked at uh what tools are they choosing first. Uh

is it open AI or anthropic and you know for the past kind of three four years that has been open AI but recently that really shifted to anthropic and it is both matching the kind of internal sentiment that we've had at Mercury but

also what I hear when I talk to customers uh also what we see in the data here at scale. So this is the first model that they choose, right? Yeah.

First model that that yeah, startups choose and for each kind of cohort uh each cohort of the cohort.

Yeah, I I definitely see a shift, but like I also feel like um there's no real loy loyalty of stuff. Like a lot of people are saying Codex is better now and I'm sure a lot of people are switching to Codeex now, switching back and forth. Yeah.

and forth. Yeah.

Yeah. I mean it's fascinating, right?

This is what competition looks like and it's like so exciting. I mean there are going to be many missteps. We uh went in and got chatupdia enterprise and then we found there was a huge kind of demand for claude as well and it turns out that

these products compete within companies uh themselves and so one of the things that I'm really looking for is are these products able to inter workflows for my example of my knowledge base what I call

my kind of second brain uh I can't go to codeex I can't easily flip that over maybe I could uh I've tried but like it is not an easy flip to switch I kind of have it now configured set up the way I like it kind of has trained on my

response and the memory and kind uh system that is building on that seems like it is locking me in. Uh but you know maybe OpenAI maybe Codex is going to be able to uh push that further. What

I'm really curious about is when a company chooses a product like this when they choose to use Open AI or anthropic first that model or that decision probably makes a bunch of other decisions in the company. The next

license that gets chosen the enterprise chat model that gets chosen. uh one kind of choice at the early stage of the startup makes a lot of other choices and I think that we're going to see that play out over the kind of next six 12 months.

That's true. That's true. Yeah. The more

context you give it, the less you're likely to churn and also there's a whole ecosystem, right? You can get co-work

ecosystem, right? You can get co-work and all this other other stuff too.

Yeah, exactly. And they're both moving super quick to extend that lock in. For

sure.

You know, you built a second brain with cloud code and um how have you noticed how you and the product team like how you guys are building products? like how

has it changed since all these tools became available internally and like you know now now you're kind of like age and pil like yeah how has all this stuff changed? Yeah.

changed? Yeah.

Yeah totally. I mean it's changed a ton and I would say Mercury has like significantly accelerated in the last six months but it's maybe kind of a continuum that we've been on. There's

really kind of like three things that we have anchored on that we find are the the big levers for kind of EPD teams and what we're building for our customers.

First is prototyping. We made a disposable front end. You can kind of see our demo uh demo. mercury.com and

what we've made is that that can be pulled by any PM designer quickly edited and you don't have to fully update the backend you are editing the production site and so it's helpful for sharing ideas early concepts getting it in front

of customers and what I found is that's collapsed the time it takes for us to get to a good idea and so uh you know if you can build disposable prototypes super easily that has kind of replaced specs and uh you know the kind of long writeups where you're conveying

something a meeting where you're trying to get everyone on the same page you can just show them that and we have a bunch of people at Mercury doing that Two, I maybe already mentioned this one a little bit, but an AI data analyst for everyone. I've been building a data team

everyone. I've been building a data team for the last five years, and I've never been able to get on top of the demand that we've had for data. There's so many people that just want to know basic questions about the business. Now, we

have an AI data analyst. And the thing that's become useful is that we can do analysis on that. What are people asking? What are the common things? And

asking? What are the common things? And

then we can go make sure the data infrastructure is set up to be able to answer those questions. And we actually found our sales team was asking something that didn't quite fit. Uh that

then let's helps us go improve the system. And so I think the system of

system. And so I think the system of self-improvement is a big thing as well.

Yeah. Yeah. Like ever since I got access to the codebase as a PM at work um for like small bug fixes and UI stuff like when I asked engineers like hey can you help me with this? They was like hey go do it yourself.

Yeah do yourself you know. Yeah, I mean the other part I found is that I'm not waiting on someone to give me information and I think being unblocked is one of the most important things uh in this environment and like you know my ability to actually go ask what does the

code do and have that conversation so that when I'm coming to the engineer and they're I'm treating their time with value. I think that's something that's

value. I think that's something that's also been really appreciated.

Yeah, I I hope all this stuff combined will shift the curve for being a PM to like just way more fun because prototyping is way more fun than writing docs. Yeah,

docs. Yeah, shipping stuff is way more fun than just writing a bunch of tickets, you know?

Like I I hope we can just like shift the curve slowly to more fun stuff. Yeah.

Well, what what I always say is there's going to be need to be someone that is keeping a group of people pointed in the same direction and making sure that we actually shift something. The job of a PM isn't going away, but it is changing,

but it changed when we built on cloud.

It changed when we built uh for AI and for uh cloud code and different products like that. The job is always changing,

like that. The job is always changing, but you know, getting the thing done is ultimately what the job of a PM is.

Cool. All right, Ryan. Well, thanks so much for your time, man. Um, uh, where can people find you?

Yeah, I'm on Twitter. That's probably

the best place. Rywigs, uh, if you want to follow me, but, uh, otherwise on Mercury.

Yeah. And if you have a Mercury account, definitely install the MCP and set up on your OpenClaw and hopefully, you know, thank stay safe. Yeah. Yeah.

Cool. All right, man. Thank Thanks so much man.