Call —
Transcript batch
0:00 Caller: Hey, Jed, this is
0:00 You: Hello.
0:02 You: I'm well and yourself?
0:04 Caller: Gritty from Maven.
0:05 Caller: How are you?
0:07 You: Yes.
0:08 Caller: Yeah, good, good.
0:11 Caller: It's funny, your phone number is so,
0:13 Caller: do you do that on purpose, like the anytime thing?
0:16 You: I got that phone number a while ago actually in high school.
0:22 You: So this was at a time when we had to memorize each other's phone numbers.
0:26 You: So having mine spell something was just a bonus.
0:27 Caller: Yeah.
0:29 You: I saw the opportunity and I struck.
0:30 Caller: Wow. Okay, so you just, you happen to get that number and it end up spelling out any time?
0:36 Caller: Or, oh, gotcha. Okay, very cool. I've had, I very, really, yeah, it's definitely such a throwback, but very cool. Well, lovely to meet, yeah, lovely to meet you.
0:49 Caller: Really quickly, my, a quick background on myself, so joined Maven about two-ish years ago to help build out there, basically anything.
0:59 You: Thank you.
1:00 Caller: data science and AI and machine learning related. I previously, my exposure in terms of executive
1:00 You: Thank you.
1:01 You: Thank you.
1:02 You: Thank you.
1:03 You: Thank you.
1:05 You: Thank you.
1:07 Caller: search was recruiting C-suite executives to early-state startups, and then I did a little bit of work for
1:07 You: Thank you.
1:09 You: Thank you.
1:12 Caller: hedge funds, and then they brought me on here to effectively kind of do both. So I still do work with,
1:18 Caller: actually, early-state startups. I also do work with hedge funds, but it's predominantly kind of mid-to-sener-level
1:24 Caller: hires and kind of across the stack in terms of like research.
1:30 Caller: research scientist, product managers, and yeah, so that's a little bit about me and kind of what
1:35 Caller: I do. I would love to hear a little bit about you, and then I can effectively go into the details
1:39 You: So.
1:40 Caller: that Neha kind of sent across, and I'm really here to talk you through any sort of questions.
1:46 You: So, most recently.
1:47 You: So, most recently at Rowe.
1:48 Caller: My objective really is to kind of tell you everything I know, and then if these themes of interest,
1:49 You: So, most recently at Role, I, I, I,
1:53 Caller: we can do a little bit more of a deep dive of your background, or we can reschedule another call
1:57 Caller: depending on how many questions you really have. So yeah, I'll hand it over to you. We'd love to learn a little bit about you.
2:08 You: I handle my own infrastructure.
2:12 You: I handle most of the internals independent of the rest of the engineering organization.
2:18 You: And what that allows is for me to build out a lot of the services that row now depends upon across every leader.
2:26 You: Some 250 odd microservices, a few of them customer facing, most internal, and all managed by myself and a fleet of agents.
2:27 Caller: Thank you.
2:36 You: Prior to that,
2:37 You: Prior to that, I was at Meta, where I handled all of the telemetry for Instagram's notification systems.
2:44 You: So everything on the notification page was captured by the systems I built and then turned from data into information to serve data scientists,
2:57 You: product managers, product analysts, and machine learning engineers.
2:57 Caller: Thank you.
3:01 You: Prior to that, I was at Spotify, where I managed the ATTOPHs
3:06 You: the ATL marketing measurement, so things like TV commercials, billboard stuff you can't measure at a place like Facebook.
3:14 You: and there I built auto ATL and got it distributed to data science teams at Spotify worldwide using something called Bayesian Structural Time Series.
3:25 You: Think of it as a mathematically defensible way to measure what if.
3:27 Caller: Okay, very cool.
3:29 You: And prior to that, stints in marketing technology and on Wall Street.
3:35 You: So I'm happy to go into more detail if you'd like.
3:37 Caller: Yeah, I'm curious to understand a little bit of, maybe a little bit of, maybe even like, maybe even like the switches from Spotify to meta and then meta to row.
3:40 You: So, Spotify at the time, this is the middle of COVID, and they were offering substantial severance to those who volunteered.
3:46 Caller: What kind of cause that career arc?
3:57 Caller: Mm-hmm. Mm-hmm.
3:58 You: So I raised my hand.
4:00 You: Meta, at the time, Zuck was touting META.
4:04 You: touting Metaverse and was cutting $10 billion a year to make Metaverse a thing.
4:11 You: And Wall Street punished Meta, oh, Facebook at the time for it.
4:15 You: And so the stock was down 60%, rumors of layoffs were swirling,
4:18 You: and I figured might as well jump now instead of having to compete with my soon-to-be former Metamates.
4:24 You: And then I left it at Rowe, and well, it's been a good run. It still is.
4:27 Caller: Okay, great. And I guess what made you curious about, you know, potentially exploring
4:34 You: A number of hedge funds have already reached out, and forgive me, I forgot your colleague's name, but they wouldn't give me any more information, so I pretty much had to take the call.
4:36 Caller: this opportunity?
4:37 Caller: Yeah, yeah, Neha, yeah.
4:50 You: I think, Neha.
4:54 Caller: Okay, fair enough.
4:55 Caller: Sure enough. So yeah, I can give you a little bit of background. So the hedge fund in this case is actually called Bridgewater Associates. It's Ray Dahlio's firm. Does that ring a bell, or do you know kind of much about Bridgewater?
5:04 You: I know who they are, but is this the Westport office, or is this the one in, I believe, near the Empire State Building?
5:14 Caller: So Bridgewater is headquartered in Connecticut, but they're AIA Lab.
5:25 Caller: other colloquial, they call it, AIA, is based in Manhattan. So the one, so to answer your question, it would be the Manhattan office. Yeah, correct.
5:34 You: The Manhattan office, okay.
5:38 You: Okay.
5:40 Caller: Yeah. But yeah, so a little bit about them. Do you know much about Aya? It sounds like you kind of, the fact that you even know that there was like a second location, more than most people know. So what's your, what's your kind of intradate?
5:41 You: I didn't know I was exclusively
5:55 Caller: Aya.
5:57 You: I didn't know IA was exclusively in New York.
6:00 You: I just know that Bridgewater had at least those two offices.
6:02 Caller: Okay. Okay, great. Yeah, let me give you kind of the rundown then. So Bridgewater established
6:03 You: Thank you.
6:10 Caller: many, many years ago, like I think in the mid-1970s, I, I unofficially started in 2022.
6:19 Caller: It was kind of like an independent group within Bridgewater that had this idea to really create an end-to-end.
6:25 Caller: autonomous investor. In 2023, they officially launched and they were actually able to
6:33 You: Thank you.
6:33 Caller: extract pure alpha and ultimately get DNL attributed to their first initial kind of attempt of creating
6:42 Caller: an end-end autonomous investor, which then led to capital being raised, 2024 and 2025
6:50 Caller: across many, I would say, prolific investors. But
6:54 Caller: most well-known as Open AIA and Anthropic actually invested in this as well, and they have
7:00 Caller: some board members at Bridgewater working on this. They have raised about like $4 billion in terms of
7:03 You: Thank you.
7:05 You: Thank you.
7:07 You: Thank you.
7:07 Caller: both constructing AIA as well as put investment capital within the actual investment portfolio. So
7:15 Caller: pretty exciting in terms of how quickly they fundraise and were able to kind of garner this sort of
7:19 Caller: this attention. They then expanded from 2020.
7:24 Caller: until now, about 60-ish people. And now they're expecting to, they have a headcount growth
7:31 Caller: projected to about 100 by the end of this year. And that's across both the technology, the science
7:37 You: Thank you
7:37 Caller: and investment pillars, which is how their organization is effectively structured.
7:43 Caller: The other kind of differentiating factor is, I operate actually quite independently from Bridgewater.
7:44 You: Thank you
7:52 Caller: They initially started out, you know, obviously.
7:54 Caller: obviously from Bridgewater's kind of main hedge fund, but effectively have become a startup
7:59 Caller: within their own kind of organization. You know, they have their own infrastructure,
8:03 Caller: their own C-suite, their own executives, their own sort of leadership style. And it's quite
8:09 Caller: different in terms of like the business model that they're trying to build out than what
8:13 Caller: Bridgewater is. They, but, you know, they obviously relied initially on Bridgewater's initial
8:14 You: Thank you.
8:18 Caller: kind of infrastructure and talent set and so and so forth. So that is a little bit about I.
8:24 Caller: and what brings basically me to you is they are now working on, and a few people
8:33 Caller: have been working on this, to be clear, but it's a little bit in rudimentary kind of, I would
8:40 Caller: say, form, is they want to create a platform quite similar to what you've effectively
8:44 You: Thank you.
8:45 Caller: have created where people internally can develop agents as well as, like, persons, like, persons
8:54 Caller: in need will also be creating agents or at least the platform where the agents will be
9:00 Caller: created or working on agents that help build the platform. So it's a little bit kind of multifaceted.
9:07 Caller: They don't know if this, this is going to be like one person doing all three, or if one person's
9:12 Caller: really versed in like infrastructure or one person's really good at creating agents, they're definitely
9:14 You: Thank you.
9:17 Caller: open to kind of how that spread looks like, also given the fact that agents are a relatively
9:22 Caller: new field. You know, I think that's also kind of an effect on why there's a little bit of
9:28 Caller: openness here. But what it really is trying to do is right now researchers internally are, you know,
9:36 Caller: manually stitching their models together, their prompts and their data workflow. So this role is
9:41 Caller: that the objective of the role is to really build a unified system where an investor or a researcher
9:44 You: Thank you.
9:46 Caller: can ask a question and the system automatically runs the research, you know, pulls the data,
9:52 Caller: runs analysis, tests the hypothesis, iterates on the ideas, and ultimately synthesizes
9:58 Caller: the outputs, which could even mean, you know, the theoretical return decision of a trading strategy.
10:05 Caller: So yeah, that is kind of the synopsis of it. I'll pause there. Did that make sense?
10:14 You: It does. Now I know you have my resume. Have you
10:18 You: have you seen my website or GitHub?
10:20 You: Have you seen my website or GitHub?
10:22 Caller: But I can pull that up as we speak.
10:23 You: Both should be on my
10:26 Caller: All right, here we go.
10:30 Caller: Yes, okay. I have your GitHub up.
10:33 You: excellent.
10:34 You: There are some
10:35 You: there are some
10:36 You: some
10:37 You: meta analyses on
10:40 You: on
10:44 You: necessary infrastructure for agents to run headless.
10:47 You: So where Claude Code requires you to be in the interactive CLI, I'm able to have agents receive occasionally vague instructions, and then based on some predefined workflow workflow, attempt to satisfy or meet the user's request using the tools available to it.
10:52 Caller: Thank you.
11:09 You: So what makes this more powerful than what you might hear about?
11:14 You: on YouTube or Twitter or on X and any other social media is this runs mostly
11:21 You: autonomously, that is to say, as long as I feed it tokens, it will continue to independently conduct
11:22 Caller: Very interesting. This is, yeah, I'm just kind of skimming through really quickly you, you, I definitely, you, I definitely see your, both your news training and the options trading and the options trading kind of posts. This is very interesting. So I guess, has finance been something, has finance been something you would ever kind of return.
11:28 You: the research and service of whatever goals or steering that I provided.
11:44 You: It's certainly something to consider.
11:52 Caller: turn into, obviously we're taking this call, but yeah, curious to hear what you, how you think about it.
12:00 You: The biggest thing I want to understand is if AIA now would accept how I work, because many other funds
12:11 You: that I've spoken to still insist at least some amount of being able to hand code algorithms.
12:18 You: And while I acknowledge the advantage, I also think the advantage is declining, or the spread between
12:22 Caller: Yeah, I mean, I think, candidly, they have themselves admitted that most of their engineers are, if anything, have become more product owners is what they're calling them internally, very few actually, even code by hand anymore. It's a lot like code review. And I think you will, given that, you know,
12:24 You: that advantage and those who can't is declining.
12:41 You: I'm going to be.
12:43 You: You know, I'm going to be able to see.
12:46 You: You want to do.
12:48 You: It's all right.
12:50 You: Thank you.
12:51 You: Thank you.
12:52 Caller: you want to proceed kind of in the interview rounds and get to that kind of the technical portion as well, you'll, they allow, like, cloud code as a primary tool to complete those aspects.
12:52 You: Thank you.
12:53 You: Thank you.
12:54 You: Thank you.
12:55 You: Thank you.
12:57 You: Thank you.
12:59 You: Thank you.
13:04 Caller: So obviously, I'm sure there, you might probably have a lot more questions and need kind of like that in-depth discussion.
13:10 Caller: But from my point of view, what I've seen with IA, how they talk about themselves and in terms of even running kind of like the search, I do think that, I mean, I think this is kind of,
13:22 Caller: their objective is to be almost, you know, like, handless in terms of, like, manually writing code.
13:29 Caller: Does I answer your question? Or at least give you some insight? Yeah.
13:29 You: It does.
13:31 You: Well, that is a refreshing response.
13:36 You: Now seeing seeing that what I dis what I did what I pioneered for myself maybe a year and a half ago now is that is now becoming embraced as the norm.
13:36 Caller: Good. I'm glad.
13:52 Caller: Yeah, outside of even for like Bridgewater, I think what I've been seeing is the hedge fund space is slowly moving to this. I think there's, for whatever reason, some compliance issues that they probably have to deal with. But I think Bridgewater is definitely a little bit more on the forefront of embracing this technology and also actively making sure people use it. And I think we'll start seeing a little bit more and more of this down the line. But yeah, I definitely think Bridgewater is definitely kind of
13:59 You: Thank you.
14:22 Caller: of on the forefront of this aspect. Cool. Okay. What other questions do you have or is there anything else that you kind of want to get clarification on?
14:29 You: So what can you tell me about the reporting line?
14:30 Caller: It goes, it directly reports into Erin. Yeah. The CTO. Yes. Correct. Yeah. Mm-hmm.
14:33 You: Does it go to Greg Jensen, Justjit Sekhon, or Aaron Linsky?
14:39 You: Or maybe someone else?
14:41 You: Excellent.
14:43 You: Okay.
14:44 You: And then what can you tell me about the team they want built?
14:50 You: I know you mentioned multiple disciplines and the ambiguity about an individual versus a team, but
14:52 Caller: Yeah, great question. And the actual answer is both. So, yes. And given the way that they work, there's definitely a lot of blurred lines as well.
14:56 You: in practice, is this meant predominantly?
14:58 You: predominantly to build the thing that makes investment decisions or to build the thing that helps others build investment, make decision-making things?
15:20 Caller: So I would say it almost even depends on your interest and where you think you would align well.
15:26 Caller: But if it helps as well, the first conversation is actually with Aaron.
15:28 You: Thank you.
15:29 You: Thank you.
15:30 You: Thank you.
15:32 You: Thank you.
15:33 Caller: And he can kind of tell you a little bit more about how he's thinking about the structure in terms of like the team buildout itself.
15:40 Caller: He has already allocated for this person to at least have two or three people reporting beneath him, at least at the initial stages.
15:48 Caller: And I'm sure whoever steps in may have further insights or plans or maybe won't need anyone.
15:55 Caller: And we'll just use whatever existing team there might be. So there's definitely a lot of openness around what that plan looks like.
16:02 You: Understood.
16:02 Caller: But he's actually really noted that there will be likely two or three people that will come in to work with this leader effectively.
16:12 You: Then I guess what would the next
16:14 You: what would the next steps be?
16:16 Caller: Yeah, so I just need to,
16:18 Caller: to kind of do a little bit of a deep dive. I would love to really understand how and what you've built out at Roe predominantly. And then my, and then I just present you to Aaron. And then he'll come back and say whether or not he's interested, more than likely even from what you've already seen and what you've already told me, I feel like I'm pretty confident he'll want to speak with you. And the first conversation really is just many people describe it as quite conversational. It's actually even labeled as a pre-
16:32 You: Thank you.
16:48 Caller: screen. With Aaron, many people would describe it as very much like an engineer, talking to an
16:54 Caller: engineer about AI and how they see kind of the evolution. And he'll tell you a little bit more about the
16:59 Caller: details of what he's thinking. He'll kind of ask you what your thoughts on, thoughts are on. And given that
17:02 You: Okay.
17:04 Caller: you've kind of even worked around this independently, I'm sure all guys will have a lot to talk about.
17:09 Caller: But it's almost, it's quite informal. And then, yeah, that's kind of like the first step. And then I would
17:14 You: Okay.
17:15 You: How can I help you.
17:15 Caller: I also need a CB or resume, but I can also, oh, which you have already given me, sorry,
17:19 Caller: I was going on an autopilot, but, and I'll, you know, I'll just send that across. So, yeah,
17:25 Caller: that's kind of the next step.
17:30 You: better present my case, well, I guess before we get to this, in terms of what I've done at Rowe, I was originally brought on to help the underwriting function.
17:39 You: Because at the time, the credit product was quite literally underwritten using distressed credit style Excel sheets.
17:45 Caller: Thank you.
17:47 You: So I did away with most of that, and after a series of improvements, increased underwriting's capacity, their ability to generate a credit limit by 400x.
17:58 You: So not only could the backlog of credit applications be processed much faster, but a client's creditworthiness can be updated multiple times per month, especially as new data comes in.
18:09 You: And after achieving that, the attitude from leadership was, what else can you do?
18:15 Caller: Thank you.
18:16 You: So it ended up me building more automations to help sales, to help compliance, to help finance, the engineering org, and so on, to the point now where every
18:28 You: every leader consumes something from me directly.
18:30 Caller: Thank you.
18:32 You: These kinds of automations are all LLM or, or what's the term, deterministic, things like generating reports,
18:44 You: or enriching prospect information with other metadata so that sales reps can be more personalable, more personalized in their outreach, recommending responses for support requests, flagging compliance,
18:45 Caller: Mm-hmm.
18:58 You: when fraudulent activity is noted, or if a client has some new lawsuit against them, or other newsworthy alerts.
19:08 You: But I think the most impactful project was being able to make agents headless.
19:15 Caller: Thank you.
19:20 You: So engineers nominally are productive 6 to 8 hours a day, actually writing code or using their cloud code instances.
19:28 You: And I was able to extend that productivity further using my own brand,
19:34 You: well, using, for lack of a better term, self-learning agents or creating an environment where agents are able to correct themselves or can safely make mistakes that are reversible.
19:45 Caller: Thank you.
19:47 You: Because I'm of the opinion that an agent can, will always do the right thing after trying everything else.
19:56 You: And so making sure they have a way to measure progress against some outcome and correct against missteps means that in the otherwise unproductive time, when an engineer isn't awake or isn't at their computer, there is still progress toward a goal being made.
20:15 Caller: Yeah, definitely.
20:15 You: Does that make sense?
20:18 Caller: Very.
20:19 Caller: Um, go on.
20:20 Caller: When you're, I guess.
20:20 You: So that's the kind of unlock that, at least today, is something that
20:22 Caller: When you're, I guess you're, I guess you're, I work with, I guess, um, work with, I, I guess, uh, work, work with, uh, what, work with
20:26 You: Many people I speak with at the various AI networking events describe as the future.
20:32 You: For me, it's the present.
20:43 Caller: deployed, what is their, I guess, like, functional objectives, what are they usually solving for,
20:49 Caller: or what are they building out? What's kind of like the end product?
20:53 You: It depends.
20:54 You: It depends.
20:56 You: coding agents. They're responsible predominantly for creating new container images on Kubernetes clusters that serve data processing or alerts management or generate dashboards. The spec or the requirements are very detailed in advance. And they always have some form of goal or objective against which an agent in flight trying to implement that spec is able to assess a decision point.
21:13 Caller: Thank you.
21:26 You: whether they go left or right in terms of architecture in service of that goal.
21:33 You: Other agents are responsible for crawling the web.
21:37 You: So within the compliance team, when an applicant applies to open an account with Roe, they include a website sometimes.
21:43 Caller: Mm-hmm.
21:48 You: And so that website will be, we'll receive a visit from some of our agents.
21:53 You: And the contents of that website will be, will be analyzed.
21:56 You: against the remaining contents of the application.
22:00 You: So if the applicant is an e-commerce business, the expectation is the website would have a checkout button or some other way to receive payment for goods purchased.
22:10 You: It's rather impressive how many don't have that feature.
22:13 Caller: Hmm.
22:16 You: For our product team, we have recordings of many of the calls with support and with the sales reps, and that in those calls occasionally include requests.
22:26 You: for features as well as the pain point that the users are experiencing and it's painful enough.
22:32 You: They are passing that feedback voluntarily to our success and support reps.
22:39 You: So being able to coalesce all of those responses, weight them by the size of client,
22:43 Caller: Thank you.
22:48 You: their contribution to gross profit, and future business from that client, along with all others
22:56 You: with the same problem helps the product team better prioritize which features to task the engineering team is to work on next.
23:06 You: So these are, well, I'd say a representative sample of the breadth of agents that I directly control or build.
23:13 Caller: Okay, very interesting.
23:17 Caller: And you kind of, um, leaned into this a little bit near the end, but I'm kind of, um, leaned into this a little bit near the end, but I'm kind of curious to understand, are you also responsible for kind of like the U-X side of thing, like, um, yeah, like, if a, if a, for example, when you were kind of talking about, like, the sales and the sales reps, like, if they were to tap into the, the, the, um, uh, kind of the features that needed to be added, I guess, how does that interaction actually,
23:26 You: So a client calls in, they're describing a process to the transaction that caused them, and how they're describing a process, let's say, assigning receipts to the transaction that caused them, and how, when they're trying to process,
23:43 Caller: happen.
23:55 You: a business trip's worth of receipts, let's say, 15, 20 receipts, the interface does not permit
24:02 You: bulk assignment.
24:04 You: So the solution that came from that was automatically parsing the received receipts and attempting to
24:12 You: pre-fill or pre-assign them to the transactions that caused the receipt. So instead of having to enter the
24:13 Caller: Thank you.
24:20 You: transaction every time, the user only had to agree or disagree.
24:25 You: with the recommendation made by the machine.
24:28 You: And so it increased the receipt processing speed about 8 or 9x,
24:34 You: or 80, 90% accuracy, give or take, attributed to this feature.
24:41 You: And that came from the problem that was highlighted, that was gathered by the sales reps
24:43 Caller: Mm-hmm.
24:48 You: into the recordings from the calls, transcribed and automatically collated to see
24:54 You: where the biggest plausible wins could be.
24:59 You: So in an investing context, I imagine being able to take whatever inputs at some point in time, use that
25:07 You: to generate some sort of investment thesis, and then test that investment thesis on a walk-forward basis.
25:13 Caller: Yeah. Yeah, yeah, absolutely. Okay. Okay. Okay. Okay. Very cool. Okay. Very cool. Um, nice. All right. And then in terms of, um, you know, you're already, um, you know, you're already.
25:14 You: And because these investments are objectively measurable, it should be possible to see if an
25:23 You: investment thesis works or doesn't?
25:43 Caller: based in New York, so that is fine.
25:46 Caller: In terms of, um, I would say notice period, what would that look like for you?
25:52 Caller: Um, I guess in terms of, um, okay, great. Um, and then I guess currently, do you, um, I guess,
25:53 You: Officially, it's an at-will contract.
25:56 You: In practice, I anticipate four to six weeks to transition the entirety of my surface area to the respective teams.
26:09 Caller: in terms of, like, your own team, do you manage anyone or how do you view kind of, like, like, like,
26:13 Caller: like that leadership aspects, just generally, you know, generally speaking.
26:16 You: I used to have people who reported into me.
26:19 You: I used to have people who reported into me, and then they were allowed to
26:21 You: when they left Rome for various reasons, the headcount was refilled back in Europe.
26:29 You: So now it's myself operating a similar surface area as I used to operate with a team,
26:34 You: but now augmented by dozens upon dozens of agents.
26:38 You: In terms of people management, I try to lean away from it, mainly because that is not my strength.
26:43 Caller: Okay. Okay. Great. Um, this, yeah, this, yeah, as I said, you know, this is definitely, you know, this is definitely, it leans a little bit more on the leadership side, but if you truly wanted to be an ICA, I think there's definitely openness about it, I think there's definitely so openness about it, also, given the fact that this
26:44 You: I lean more toward technical leadership.
26:47 You: So while officially I have no one that reports into me, I still.
26:51 You: have plenty of people who come to me within Roe as a subject matter expert to help solve their problems.
27:13 Caller: person will be very similarly managing agents as similar to what you're doing. I think there's
27:18 Caller: certainly a very real conversation there that that was what management will look like for, for this team.
27:21 You: I think that depends on the scope of work and how the priority of that work ranks versus the other priorities.
27:24 Caller: So, um, yeah.
27:33 You: So I imagine the amount of work is enough.
27:37 You: It'll require maybe two or three people, but the skill sets will likely be different or complementary to my own.
27:43 Caller: Yeah, of course. Um, okay, great. And we can, we can talk about that a little bit more as, as you kind of progress in and this rule actually starts a little bit revolving around your skill set as well, because there will definitely be a lot of that. Um, okay, wonderful. And then, um, okay, and then in terms of timelines or other processes, I know you kind of mentioned that you were speaking with other hedge funds and potentially maybe even other companies. Is there any sort of
27:51 You: Nothing imminent, but there.
28:13 Caller: timeline pressure that I'm working up with right now.
28:21 You: I imagine as those timelines, as those processes continue, the timeline pressure will ramp up in maybe three to five weeks.
28:32 Caller: Okay. They operate pretty quickly so, um, operate pretty relatively quickly. So, but keeping posted as soon as those, you know, those processes start moving to kind of, like, mid to,
28:43 Caller: And then I will try to push on my end as well or try to at least proactively get you scheduled for rounds
28:51 Caller: earlier than later. So, okay, good to know. And then in terms of compensation, what are you ideally targeting?
28:51 You: The budget you shared works nicely.
29:02 Caller: Okay, great. And again, we can start kind of evolving that conversation as we get further along the line. But as long as, yeah, what Neha kind of it's shared is good.
29:13 Caller: that works well for me as well. So, okay, I think I have everything that I need to represent
29:20 Caller: you well. Obviously, I have a lot of information on your website to kind of talk along with this as well.
29:21 You: Nothing at the way.
29:26 Caller: So I will get going on my end. You should more most likely hear from me or hear back from the
29:33 Caller: Bridgewater team within the next like 48 to 72 like business hours, if not sooner. So yeah, I'll keep you posted.
29:36 You: How do you want to be able to be contacted?
29:42 Caller: Anything else I can help you.
29:43 Caller: email is good. Yeah. Email is good. Yeah, email works. Yeah.
29:50 You: or some other way, so I can pass along with that status.
29:55 You: Okay, then I'll, once I have anything to share, they're happy to pass it along.
29:58 Caller: Yeah. Okay. Perfect. Well, really appreciate your time. It was lovely speaking with you and I'll talk to you soon.
30:02 You: I'll pass it along.
30:09 You: Splendid, take care.
30:11 Caller: Thanks. Bye. Bye.
30:13 Caller: Thank you.