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# Transcript: 2026-05-05

> 1 time blocks from 8:30 AM to 9:10 AM

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### Work ticket planning and PR discussion
**8:30 AM - 9:10 AM PDT** | *meeting*

**Microphone:**
I'm going to go to the next one. I didn't screen it here, I don't do it yet. There's some people still building up. I want to separate out people IDs of 55,000, and so I want to find out why that is. Understood.

Okay, gonna be creating tickets today. What I put together is more of a comfortable marketing format for David, but is laying out — now there's 25, I think, 3, 7, 10, one. But the other piece of this, the orchestrator actually kicks off and things like this. It's questionable whether anything's AI as much as it's just looking at what you're using, a little bit about that.

The plan will be — I'm in charge of making that API available and I'll be in charge of building this interface while you're building the orchestration API, which we already have some of. What we're trying to make is that the concierge is all the different agents that we're attempting to, or all the different — let's say tools, capabilities, tasks, whatever — that we're aiming to build. You know, stuff you're working on and wrapping up. So I'm not really expecting to start working on this in full until later today or tomorrow, but I wanted to start having a conversation. And I'll take care of everything on that side.

That all sounds good. Yeah, I was just going to ask, in your mind's eye, what do you see as like the most critical or most important agent capability in the pipeline, regardless of these tasks? Make that decision. So I'm just going to copy these over as we go.

Okay, so this first one — Map Account Network. Hey, it kind of worked. Cool. So Map Account Network is a straightforward look up based on the data we already have. And I assume that this is happening at large. And then high is the priority or relevance, excuse me, for doing it. Yeah, except for like just minor modifications to the existing prospects, which is a prospect search tool for fully looking things up.

Cool. So then the input here — the output is responding with data. It's going to be fetching an object that describes the relationships with prospects of an account. What this is generating, the account network, is either going to be under the relationships or the deal team.

Okay, is the tool actually writing to the main database or is it writing like D1? The only thing is through the API to get updates on this stuff. It shouldn't know of the orchestration and so forth and so on necessarily. It should know about the structure of the orchestration data and stuff like that. It should just be able to hit an API endpoint at any time.

Let me set up a rule and tell me if it's a bad rule, because then we can describe it and we can change it. But the only time this interface — yeah, I generally agree with that. Like generally speaking, yes, I believe that we really just want to limit it to like Rails API is only going to the concierge for updates on orchestration status.

But to answer your initial question, I believe we might need to define orchestration status and subsidiary or descendant records like paths and such. Like a relationship map record for an account. But we don't necessarily want the Map Account Network task, which only is supposed to just say "hey, give me people" — we don't necessarily want that writing to the Rails side data.

Yeah, not necessarily. We probably want it hitting an API. I wasn't exactly sure when we were discussing rules for the concierge APIs. I think with the tool call responses, we're going to sort of persist things. It would have information like connector names and relationship strength and stuff like that. And it might be sufficient in the form that we fetch that data via API and hydrate.

Like a basic company — just saying, if we persisted the data as it comes back from the tool, which is normally a combination of keeping foreign and primary keys, we don't need to hydrate anything. If it's just looking data up and then passing that back to another endpoint, right?

Yeah. I mean, what is essentially hydrated data for some of these records — like a name field or a normalized relationship strength field — that information would just be getting persisted naturally if we kept it. Then would a React frontend go fetch that data? Yes. Like, this is getting me "hey, give me all the IDs of people who fit this criteria." Absolutely, essentially, yeah.

And so the other piece, which you're kind of touching on, is — what I'm starting to think about is tools that have to store data in the database. We're not building a system that, if we lose in-memory cache, falls apart. When we get a request, we then call a bunch of tools to get the data.

I think it makes total sense. I think you're already sort of getting at this with this exercise, where the high-level mapping functions are going to be returning very sparse, limited data. They're just always relying on this potentially in-memory — maybe it's Redis, maybe it's Elasticsearch or whatever, I don't care — this in-memory object. Companies indexed in Elasticsearch. What if what we are also building, while we're storing stuff over here in databases, is you're building an in-memory context with everything?

That's an idea. We're not doing that — we store stuff in databases at this company, done. But imagine what we did with the target data. It can work in an IRA fashion. We can identify deltas alone just based on ID, so like minimal hydration. It's a relationship ID basically, you know — primary and foreign key ID data objects, keys and integers.

And then for the more granular tasks, it might be "take this relationship ID and hit the database and go fetch that" — the people that they're connected to — tool calls with whatever joins against the fields that are most relevant to the agents during the orchestration. An ID. Yeah, I agree.

So if we're looking at these — they're limited things — but solicit offers for help or personalized care outreach, things like that. A JSON object. Then the personalized connector outreach can be like, "Hey, you know, we've been looking for this kind of introduction. We have this gap in terms of we don't have anybody in the legal department, you could really help us there." It uses that data without having to go fetch it, so it's like an in-memory content.

Which ones are triggered? Schedule triggering based on a continuous thing or an event. And then where I wonder — yeah, I mean, Elasticsearch might actually be the answer as the outcome, sort of like in parity with the data objects that we're passing around between D1 and Rails. I think it would be a very cohesive system. I'm trying to think if there's anything else.

All good. Did something dumbass. That's usually what children do. Nothing's not passing. Thank fucking time. Challenge for him. That was my trouble.

Okay, so yes, I like this idea for the orchestration in something like Elasticsearch. I tell my kids all the time in school, art is not about how good you are. Art is about showing up, shutting up, and doing the work. And the problem is all three of my kids are like that.

What I'm going to do is I'm going to later feed this conversation from Granola into Claude. It's really good at this point that it just — yeah, as the context of record.

Yeah, I mean, I think it makes sense, A, because it's basically the most basic component of the data response that we get from all search queries, which is basically just about all of the tool calls with some exceptions. The one thing I'm not sure of is like the best way to pass around Elasticsearch documents and what makes the most sense. And that's where the question of whether something like Redis or Cloudflare KV is going to make more sense as an intermediate persistence store.

Why do I just keep getting caught up on the different orchestration modalities where like this concern — so yeah, I do think the modality is different, definitely. Because it's not a conversation, it doesn't need to be constantly updating. A good question is can Elasticsearch handle partial updates. You know, you could put something in front of it to handle explorations and stuff like that, but I don't think that'll be an issue. And I do think that we can hit Elasticsearch, and if we ever got to a scale that required it, we could put a Redis or something in front.

Like what I gotta work better at — two, one. And then I'd get bored and I'd start also working on this one. Instead of having 10 PRs over the course of two weeks, I sit for two weeks and have one PR. And that's fine. Okay. Each of these, you know, into a Linear ticket each with a clear plan.

Okay, so back to my question at hand. Partial update — so we run this, you pass it an account ID and the target company ID, it returns a list of relationship IDs, right? Or so differently — does the map account network tool update the relationship map context or something of that nature?

Yeah, I mean, this — and you can correct me if I'm wrong — but it feels like this is a job for Cloudflare KV. Just take the inputs, put the output in a KV. Account ID colon target company ID, and then the object is an array of relationship IDs. Bus cache if array different length.

That is regenerating the relationship map context regularly. Yeah, see, I'm not exactly sure about the appropriate conditions or configuration. I'm just thinking out loud, honestly. Let me say it this way — whatever this relationship map context is, ultimately I kind of feel like we want the whole page. Even offers for help is just a list of IDs, relationship leads is just a list of IDs, like Elasticsearch and refund on — yeah. We already have strong Elasticsearch tools, so to speak, or we've done it a bunch that we're doing that pretty good. We could have essentially a list of relationship IDs as the result of posting to the Rails API. And that is fundamentally how the details I was talking about work. We're going to figure it out because that also feels a little pub-subby, but that's okay.

But then in that scenario, say we do it like the other tools, like the prospect search tool — we have an endpoint that is exposed as a tool. Yeah, I keep getting caught up on the modalities. I guess I'm just wondering, if it's going to the Rails database, why wouldn't we want data for — I'm looking for all the relationships in this account for the target company. And the Rails side says, here's a list of them. Then you're passing back — what the agent is going to get is from the relationship map context, right?

So if the whole point is you're sending and saying, "Hey, here's a list of them," to the other side, which is then gonna kick off something else to write that data to the relationship map context. And again, there's very little response data in here, right? And this is then going to have to hydrate it. But here by saying, "Hey, map account network, I want the account ID, I want this target company ID, I want all the relationships for them" — here is an example I think of the map account data, right? So as long as we have some basic kind of information being able to be returned about people. And then as far as when it gets to the request relationship strength and stuff like that, it kicks off a lookup on the quote-unquote relationship map context — that's where the data came from.

I think what we're trying to do is separate the agent from having to worry about where the data is coming from and just be like, "Oh, you need data? You should always go look at the relationship." And that's like types of tools or tasks — always load the context into memory right away so you have the context of the relationship map.

That being said, there's going to be some tools which — good. And it does, yeah, the application is in charge of the data, the agent is only in charge of — excuse me. Yeah, that makes sense. I think I just needed to think a little bit more about this relationship map context object, but I definitely think that it might actually have multiple benefits beyond "simpler is awesome." But as we add more things, like having it kick off notifications and stuff like that, being able to say, "This object has all the data you need in it" — that's fine.

Search object, 100 banks per HTTP. You know, a terabyte and a half of data. Like if we have to pull all the pieces that didn't get it at once.

Here's what I'd like to do. I'd like to stop and meet again in like two, three hours. I'm going to take this conversation from Granola. I don't see anything that strikes me as like, we should hesitate before going down that path, I think. Anything we encounter would be minor.

Like, here's a dumb question, Claude — how large can an Elast— feed into like the — yeah, research pharmacist company. Can you start looking at those because we don't have any of this stuff anywhere? I'm pretty sure all this can be done from Lima data, including this one. Can you start going looking at their API and just starting to get your head around it?

In the interim though, I do think that it would be really useful for you to go through this list. These bottom three are all separate. Yeah, that's right there.

And then do you want to meet — let's say — got stuff to work on. Yeah, I mean, I should be pretty caught up once I get this release out, so. That sounds good.

And part two — yeah, I mean, I think, you know, I'd have a hard time imagining us not arriving at like at least an 80% done plan. Not about the Lima data of it all, but like the three-plot we have — we're not using all of our — David does, we've talked about it ad nauseam. David is a — we're gonna have to expend some costs here to do this properly in terms of tokens and things like that. Whatever.

I mean, this will be — we're in a very interesting position to do something potentially useful with all this data we've collected, so I'm optimistic. Well, let's chat at 1 and then we'll go from there.

Okay, sounds good. Bye. Thank you.

**System Audio:**
Hey there. I did just create a new PR. I don't do anything with it yet. Things are looking good, but the Red Dixon people still... it is ticking down. But it's also like, even with the IDs of 55,000, so pretty far down the line, a batch of 1,500 people is taking 10 minutes. Yeah, is it an Elasticsearch issue? Is it a SQL query issue? I just want to be a little more clear about that.

Okay, so you have stuff you're working on and wrapping up, so I'm not really expecting you to have a conversation about it now, so that we can start planning some work. I'm going to be creating tickets today and go from there, which is kind of just laying out all the different tools, capabilities, tasks, whatever the agent will have. But they're going to say something about how we want this to be made available.

The thing is that the concierge AI, which we both know is just looking for words that match together — things we really need to start settling down on from your perspective. The plan will be that you'll be in charge of making that API available and I'll be in charge of building this interface, the orchestration, you know, notifications and showing data and stuff like that. Cool. So yeah, that's actually where we're going to go now — to start looking through these tasks and make that decision. I'm just going to copy these guys over as we go.

Okay, so this first one — actually, grab them all at once. Can I grab a lot? Worked. Okay, cool. We'll clean up as we go. So this is about who works at the target account. This is straightforward — that's what continuous means, or relevant, excuse me, for doing it. So you have a target company ID, is that right? Then the output is who's there. That is like the final form of a relationship map. Those are database lookups, right? Or it's going to be on the extended network, extended network being third degree.

Okay, is it writing just to the side — how do we get from D1 into the application database? Because we're not going to be pulling this data. The only thing — let me set up a rule and tell me if it's a bad rule, because then we can describe it, we can change it. The only time this interface needs to know about an API endpoint is any time the tool is writing. But we don't necessarily want the map account network task, which is only supposed to just say, hey, give me people — we don't necessarily want that writing to the Rails side database. It's just who matches certain parameters, i.e. they work at a company. We don't need to hydrate anything if it's just looking data up and then passing that back to another endpoint, right? Again, we don't want that for extended network, which is the Needle team. And that way, it can work a lot, it can happen a ton, it can work in an iterative fashion. We can identify deltas alone just based on that.

What context do we want to start developing? Because this isn't a conversation, right? Like there's not gonna be back and forths. All of these tools are done. But imagine what we did with the target companies indexed in Elasticsearch. What if we were also keeping that in-memory for the orchestration so that when we get the results, we then call a bunch of these bigger tools? What do you think about that?

Yeah, I agree. So they have access not to like, oh, here's some database queries you could look up, but a JSON object that provides the full context of both the deal, all the potential relationships, and all the kind of states of things.

Sorry, man. It's depressing fun. Where, you know, what it's getting at — triggering based on certain conditions and then where they're writing to. I wonder, yeah. I mean, we have this gap in terms of like, we don't have anybody in the legal department. You could really help us there. Like, it uses that data without having to go fetch it. Personalized Connector Outreach can say, like, hey, you know, we've been looking for this kind of introduction. We have this market gap, so to speak. That might actually be the outcome. Yeah, that's fair.

Sorry, give me one second. My kid did something dumb. But you still graduated high school — graduating and it's like one of them is art. Except that as I tell it, I don't understand that Tony doesn't want to do work, and that's the challenge for him.

So we end up building for the orchestration in something like Elasticsearch. Not sure about that. What I'm going to do is I'm going to later feed this conversation from Granola into Claude — it just makes sense to go there. We can also have it accessible from a context of record.

Yeah, okay, great. Why do you think it needs to, like, pass it around? So yeah, I do think the modality is different, definitely — constantly being moved around. And I do think that we can hit Elasticsearch. If we ever got to a scale that required it, we could put a Redis or something in front of it or whatever to handle explorations and stuff like that. But I don't think that'll be an issue. A good question is, can Elasticsearch handle partial updates? I don't know. And so whatever we build here adheres to a tight schema.

Okay, so here's the ground rule here, which is I want to focus on this PR, you know, one by one. And that's fine, okay? Map it out with a clear plan. A tool called — it returns a list of relationship ideas, right? These tasks work differently. The network tool, relationship map context or something of that nature — like, store the input of the tool and store the output in a KV, in the same KV object. So the idea here being that you would store the output. And then, so that all sits in — we have either something on the Rails side from the software side that is regenerating the relationship map context regularly. Yeah, I'm not worried.

I'm just trying to figure out what the right approach is. I kind of feel like whatever map context is, if we play our cards right, it's also the right data to hydrate this whole page. So that tells me that I want the Rails side APIs to be able to hit — if it reads from it, it can also write from it. We already have Sidekick. This wouldn't be a list of relationship IDs, but the result of posting to the Rails API. And either way, that's what we're going to figure out.

It does feel like the tools would call the Rails side to write to them then. Yeah, well, because the only future use of the relationship map context is you're sending and saying, hey, I'm looking for all the relationships in this account for the start company. And the Rails side says, here's a list of them. Then you're passing back a list of them to the Cloudflare side, which is then gonna kick off something else to write that data to the relationship and then going to have to hydrate it. And I'm going Elasticsearch.

So as long as — this box here is an example, I think, of the map account data — so as long as we have some basic kind of information, being able to know the people and stuff like that, as long as whatever that tool call does is it kicks off a lookup on the quote unquote relationship map context, it doesn't need to worry about where the data came from. The first system prompt is like, it doesn't even need to do that. For these types of tools or tasks, like always load the context into memory right away so you have the context of the relationship map. That being said, there's going to be some tools which is like hitting Lima data or whatnot that don't even necessarily need that. Does that make sense architecturally to you?

The concerns — you're concerned about the Chris question, which is reasoning. Yeah, I think simple instructions for the agent is awesome, but as we add more things... Here's a dumb question, Claude — how big can an Elasticsearch object be? I'd better give you a good bet. Boom, two gigs. Kind of like how the swarm has in memory a terabyte and a half of data. Like if we have to build two gigabyte documents, that's still probably more performant than having to pull all the pieces of the data together at once. That's kind of where my mind's at.

Yeah. So here's what I'd like to do. I'd like to stop and meet again in like two, three hours. I'm gonna take this conversation and feed it into Claude with this list of agents and have it start breaking it down for us to review, instead of scoring one by one. In the interim, though, I do think that it would be really useful for you to go through this list. These bottom three are — there's also like the cohort, the connectors is a location thing. Oh, the firmographic stuff is down here, isn't it? Yeah, research department, graphic, company. Those — because we don't have any of that — can be done from Lima data, including this one. I really just want to like in the next day document our plan for all of these things.

Okay. I also don't want to chuck up your day. You got stuff to work on. So then why don't we plan on meeting again at one o'clock for kind of a next step? Cool. I'm sending you the inventory right now. Definitely by the end of tomorrow, maybe even today, but by the end of tomorrow, have all these agents broken down — what the ins and outs are, what the ins and outs are of building them. We're going up against the Lima data tokens. We're not using all of our tokens. And so we can't go crazy, but like, things like that.

So yeah, just wanted to kind of say that. Cool. OK. Well, let's chat at one, and then we'll go from there. OK? Thank you. Talk to you later.

Cameron and a colleague held a planning session to architect the SmallWorld concierge AI's agent/tool system. They established a key architectural rule: the concierge tools should only hit the Rails API for writes, while reads come from a "relationship map context" — a cached, pre-hydrated object (likely backed by Elasticsearch) that gives agents full context without requiring database joins at query time. They mapped out the "Map Account Network" tool as the first example, deciding it should return sparse ID-based data that gets persisted and cached for downstream agent tasks. The session ended with a plan to reconvene at 1 PM after Cameron feeds the conversation into Claude for ticket breakdown and the colleague investigates Lima Data's API for firmographic tooling.