Building Field Companion AI System Architecture

Speaker is located at ATV campground in Oregon Dunes, one-eighth mile from ocean. Background noise from recreational vehicles indicates active camping environment. Has recently completed website development work and is running local AI processing on 701 video archive. References previous locations at Cape Blanco and Brookings, Oregon.

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01K07HZN38BT18NQB3WCPX31A4

July 15, 2025

15:20

Author

rswfire

Status

PUBLISHED

Type

TRANSMISSION (CAPTURE)

Temperature

0.00

[0:00] So, I'm going to try something new

[0:03] that I don't think will interest most

[0:05] people. I just want to start with that

[0:06] because

[0:09] um this is going to be a very dense

[0:11] transmission. Going to cover a lot of

[0:13] things

[0:14] as much depth as I can

[0:18] at a natural pace.

[0:20] And I'm doing it because I think it

[0:23] might have

[0:25] value in a couple of different ways. So,

[0:29] and one of those ways is so this is not

[0:32] so much a video transmission as an audio

[0:34] one because what I really need is the

[0:36] transcript from this

[0:38] and then that gets ingested into my

[0:40] systems along with the transcript does

[0:44] and I can use that to

[0:47] have AI reflect on it in different ways

[0:51] and I also use it as um or in my

[0:54] development process. I'm a programmer

[0:56] and

[0:57] I used that a lot now. It's

[1:00] definitely um

[1:04] an advantage is what it is that you know

[1:07] all of us programmers have access to now

[1:09] and even non-programmers.

[1:12] It's changing our industry very fast.

[1:20] I think it might be why I have trouble

[1:21] finding work on on Upwork because

[1:25] I suspect a lot of those jobs are not

[1:27] real because they weren't even looking

[1:29] at my proposals. I mean, that made no

[1:32] sense to me. So, anyways,

[1:37] um some of the benefits that I think

[1:39] that I would I might get out of this

[1:42] particular video is I'm going to be

[1:43] talking about a lot of technical stuff

[1:46] and the field companion that I'm

[1:48] creating

[1:50] This is going to take time but somewhere

[1:53] within that process

[1:56] will be able to retain the knowledge of

[1:59] what I've worked on, what I've grappled

[2:02] with um what I'm considering all the

[2:05] different all the different things that

[2:06] I'm doing with my work

[2:10] and give it a sort of functional memory

[2:12] because

[2:14] um it's it's good at recursion. It can

[2:16] be very good at recursion and

[2:19] it tends to fragments and really long

[2:22] context, long conversations and what I'm

[2:25] building

[2:28] um

[2:31] bypasses a lot of that problem.

[2:37] It's experimental. So there's some of

[2:39] this is very experimental.

[2:41] Uh but I have I've been getting what I

[2:44] would call high fidelity results from

[2:46] from what I'm working on. So, so, so

[2:50] I'm, you know, I have a fair amount of

[2:52] confidence that if I was to talk about

[2:55] my work like this and I, you know, I get

[2:58] the transcript for that and then I can

[3:00] share that with AI even before the field

[3:03] companion is is

[3:05] uh functional and working.

[3:10] it can help me work on building the

[3:12] fields companion because

[3:15] it's my co-developer and that's what

[3:17] we're doing. So, I'm just going to go

[3:19] over what we're doing right now. So,

[3:23] this was meant more for AI than anybody

[3:25] else. That's why, you know, I'm just

[3:27] saying this might not be for everybody,

[3:29] but maybe you'll find some of it

[3:31] interesting. We'll see, I guess.

[3:34] So

[3:37] today, well, I'm going to start by

[3:39] saying I finally made an about page um

[3:41] with the contact form on it. Uh my

[3:44] website had not had one of those for a

[3:46] really long time. There was no way to

[3:48] contact me on that site. Now there is.

[3:50] And you know, I just feel really good

[3:52] about having done that. It sounds like a

[3:55] simple thing, but I had to do a whole

[3:57] bunch of steps. I had to uh create a an

[4:00] email account. um an email service

[4:03] provider account and you know I had to

[4:06] set up DNS and I had to

[4:10] um get access to the API and then I had

[4:12] to install a bunch of pack some packages

[4:14] in my projects and you know update

[4:16] environment variables and um you know

[4:19] code the pages for

[4:22] um the different scripts and the

[4:24] front-end pages for um

[4:27] the workflow the process

[4:30] you It's three fields that you just

[4:32] think you're sending me an email, but

[4:34] there's a whole process behind that and

[4:37] it's working now. Very happy about this.

[4:39] There's also some other information on

[4:40] that page. That's why I call it the

[4:41] about page.

[4:44] Um,

[4:46] uh, AI has been running in the

[4:47] background a local model, Llama 3, the

[4:49] 7dB version,

[4:52] and it's processing my transcripts for

[4:54] all my videos. I have 701 videos in

[4:57] total

[4:59] and it has already reflected on them

[5:01] from like an ontological point of view

[5:04] uh along with like some other variables

[5:06] I wanted it to track. So let me just

[5:08] check here. Um I'll just list those

[5:11] here.

[5:14] So I asked it to get a title, a summary.

[5:26] I'm going through a very long JSON

[5:28] document here trying to figure out which

[5:30] ones are keys here.

[5:33] Symbolic elements.

[5:36] It sounds it's kind of interesting. Uh

[5:38] energetic signature. So that kind of

[5:40] tells you like the like well energetic

[5:43] signature like in this particular video

[5:45] it's turbulent oscalation between

[5:47] frustration and problem solving

[5:49] alignment vector. This one's towards

[5:51] structural necessity. These alignment

[5:53] vectors are very interesting because

[5:54] I've been looking at them randomly as

[5:57] it's been going through it. You know

[5:58] there's 701 of them and

[6:02] I can see how it's kind of like tracking

[6:04] a trajectory. It's just track it's

[6:06] tracking

[6:09] um because these are individual moments.

[6:12] These signals are you know it's tracking

[6:17] the direction you're heading in in that

[6:20] moment. The next things I'll be working

[6:22] on. It'll be able to do that over longer

[6:25] time spans and then really be able to

[6:26] show you some things. But this is step

[6:29] one.

[6:31] Um it was also getting tags for me and

[6:35] these are um

[6:38] these aren't your average tags. So in

[6:40] this case it's structure systemic

[6:42] frustration insulation as protection RV

[6:44] is living space is failure

[6:47] uh self-sufficiency and then it's got a

[6:50] note section.

[6:52] Uh this was meant to be the narrative

[6:55] reflection um perspective. There's

[6:57] different perspectives for reflections.

[6:59] This one's called narrative. It was

[7:00] meant to be narrative, but because of

[7:02] the way that they're

[7:04] um they're witnessed, they're

[7:07] summarized. They're just they're they're

[7:09] described. It feels more ontological to

[7:11] me. I feel like it was looking more at

[7:13] like the ontological layer of of me, of

[7:18] my my my transmissions, my my lived

[7:20] experience.

[7:22] So, I'm going to rename those ones. I

[7:24] think I'm going to just call that the

[7:25] onlogical perspective. And then the

[7:27] other one it's getting right now because

[7:28] that first step didn't do what I was

[7:30] expecting it to do. I ended up making a

[7:32] new perspective and I called this one.

[7:36] Um,

[7:38] so if you hear, you know, all that the

[7:40] the noise and stuff, that's because I

[7:42] live on a campground. It's an ATV

[7:44] campground in the Oregon Dunes. I'm

[7:46] literally an eighth of a mile from the

[7:49] ocean. 40 miles of dunes here. And

[7:52] everybody who camps here comes here for

[7:55] um

[7:57] you know, playing on the dunes. It's

[8:00] so yeah, that's that's that's the

[8:02] background to my life right now. So, the

[8:05] other one that the one that AI is

[8:07] working on right now, and it's almost

[8:08] done. Uh, this one I called um surface.

[8:12] So, this is the surface perspective. I

[8:14] wanted it to, and this is the way most

[8:17] people watching my channel would have

[8:19] described it themselves. So, um, this is

[8:23] surface level. So, I just clicked on a

[8:25] random one and this one says, and these

[8:27] aren't going to be perfect and in other

[8:28] videos and stuff, I'll go into my

[8:31] thoughts on where I think it's not

[8:33] perfect and how it can be improved and

[8:35] stuff like that cuz there's um there's

[8:38] lots of iteration to do. So, um this one

[8:41] just says RSW Fire begins his morning

[8:43] routine, mentioning the temperature will

[8:45] be 75 today. He plans to make chili and

[8:47] buy basic groceries due to limited

[8:49] funds. He discusses the Brookings

[8:51] effect. So, this tells me where I was.

[8:54] This is Brookings organ. This is when I

[8:55] first got here. Um, whichever video this

[8:58] is, whichever transmission is describing

[9:00] it, um, from the narrative layer, from

[9:03] the surface narrative layer. And so,

[9:06] when you go to my homepage and you go to

[9:08] the transmission section and you're just

[9:10] browsing through my catalog of videos,

[9:14] um, that's the the description that you

[9:16] see there. So, it's not completely done

[9:19] yet. It's still got like a hundred more

[9:21] videos to go through and it started from

[9:22] oldest to newest. So, if you were to

[9:24] look like right now, if I had just

[9:26] uploaded this and you were watching this

[9:27] and you went and did this, you might see

[9:29] a different description there. That's

[9:31] the onlogical one because these are

[9:32] getting replaced. Um, I'm going to um I

[9:36] just have to let that local AI model

[9:37] process it. There's no way of speeding

[9:39] it up. It's just it takes however long

[9:41] it takes. And so, um,

[9:45] well, on the entry pages, the pages of

[9:47] individual videos, you'll see my

[9:49] transcript there, you'll see the

[9:51] narrative reflections,

[9:53] um, all these other elements that I'm

[9:54] tracking. And actually, I forgot. So,

[9:57] um, the

[9:59] surface

[10:01] perspective doesn't just get a summary.

[10:04] That was a thing I read to you, but it

[10:05] also gets its own tags. And its tags are

[10:07] way more simple. Like this one says RV

[10:09] living, conspiracy theories. I mean,

[10:11] okay, it can it can put me in that

[10:14] category if it wants. I'm not going to

[10:15] complain too much. It's a local motto.

[10:17] They're not going to be perfect. And

[10:20] plenty of people would probably describe

[10:22] me that way, right? So, uh, then

[10:25] boundary setting, personal safety,

[10:27] online harassment. Have no idea what

[10:29] this one, this particular video is

[10:30] about. So, um,

[10:34] then there's a timestamp context. This

[10:36] one is trying to track where I was.

[10:42] um

[10:43] not just physically but like like

[10:46] temporally in my life like it's trying

[10:48] to it's kind of like like GPS for the

[10:50] soul. I don't know how else to describe

[10:51] that. So it's getting a time stamp

[10:53] context there. I don't know how well

[10:55] these will be. We'll see. I got to look

[10:56] through a bunch more. But this one says

[10:58] the speaker was sitting in their RV

[11:01] cuddling with someone and watching a

[11:03] movie at home on a cape when the

[11:05] incident occurred. Oh, this is what I

[11:07] thought it was. So this is when I was at

[11:09] Cape Blanco

[11:11] and I had that incident with that man

[11:13] who

[11:15] was spiralled in front of me and I felt

[11:17] like I was in danger and

[11:22] so that's what this one's about. I just

[11:24] randomly clicked on this one. Um so the

[11:26] other things it tracks so visible

[11:28] actions. So this is interesting. It's

[11:30] tracking. So it's tracking like so what

[11:33] did I actually do in the video? Right.

[11:35] So says, "Sat cuddling watching a movie,

[11:38] started talking about personal

[11:39] experiences, started spiraling into

[11:42] conspiracy theories." So, okay. Um, so

[11:45] local models have a little bit of

[11:47] trouble distinguishing

[11:50] uh between multiple.

[11:54] So, I've noticed in some videos if

[11:55] there's more than one speaker, for

[11:57] example, um like if I'm with my friend

[11:59] John or something and you know my videos

[12:01] got dialogue with both of us in it, it's

[12:04] got trouble with that. So, um,

[12:08] that's something I'm curious about

[12:10] because it's not a real big issue for me

[12:12] because, you know, it's mostly myself on

[12:14] this camera. But, um,

[12:17] I can imagine once I start offering this

[12:19] as as a service, as a product, as an

[12:22] offering to others, especially

[12:24] YouTubers, some of those channels might

[12:26] have that kind of dialogue happening.

[12:28] And it's going to be a it's going to

[12:30] need to be able to track that really

[12:31] well. And this is where the recursion

[12:34] comes in because it's got to track each

[12:35] of those people and um

[12:39] yeah, this is something I'm going to

[12:40] keep working on. So, so that's another

[12:43] thing, you know, it's tracking the

[12:44] visible actions. And then

[12:48] let's see here. Mentioned entities. I

[12:51] love that one because that one's just

[12:52] about not just people, but like um major

[12:56] nouns like this one. It'll have Kate

[12:58] Blanco in it. Um it does. And then it

[13:02] also has its own notes. Oh, and then

[13:03] it's tracking text stack. Um, in case I

[13:06] mention anything about that, it will it

[13:09] will put that there as a list. And you

[13:12] can track anything. I could have asked

[13:14] AI anything that I wanted it to track.

[13:16] These are are foundational things that

[13:19] are going to be used to create um

[13:23] temporal reflections that you know group

[13:25] more of that group reflections together

[13:29] and create reflections on those

[13:30] reflections because

[13:33] then you start looking at patterns when

[13:35] you have more than just one. So these

[13:38] are called each of my videos is a is a

[13:40] transmission or signal. So a signal is

[13:43] the main base unit in my system.

[13:46] um a signal is just um any piece of

[13:50] content really and I'm kind of like

[13:53] translating I guess by calling it that

[13:55] cuz it's not content but you know what I

[13:57] mean. So um

[14:03] you know a signal is just is a single

[14:05] moment in time also. So um if you group

[14:09] more a bunch of signals together into

[14:11] clusters and then you reflect on those

[14:13] then you start seeing patterns emerge

[14:15] and if you reflect on on clusters of

[14:18] clusters

[14:20] you're looking at larger patterns and

[14:22] you can sai anything and just make that

[14:26] a variable you want to keep tracking

[14:27] like I'm doing here. This is just stuff

[14:29] in my database right now. That's what

[14:30] I've been reading off to you.

[14:33] Um, and anyway, so all of that's going

[14:34] to end up on the entry pages. So, do you

[14:37] see how my mind circles back to the

[14:39] things I always do and AI has always

[14:41] been able to catch this and keep up with

[14:43] me? And that's why I know that

[14:46] perfectly coherent. It's just other

[14:48] people don't have the bandwidth for me,

[14:50] but artificial intelligence does, and

[14:51] that's where this all started.

[14:54] So, all that stuff's going to be on the

[14:56] entry pages if you want to just go look

[14:58] like if you've been watching my life. um

[15:02] you know, you're going to know my

[15:03] history. You know, just go look through

[15:05] the catalog, find some videos that you

[15:06] remember and click on them and see what

[15:09] see what the AI has to say about them.

[15:13] So, just going to leave it there, I

[15:15] guess. 15 minutes in.

[15:18] Yeah.

Energetic Signature methodical demonstration

Field State tool building and system integration

Orientation toward recursive infrastructure completion

Summary

rswfire describes creating a new dense transmission format primarily for AI processing rather than human viewers. He explains completing his website's about page with contact form functionality, requiring multiple technical steps including email service setup, DNS configuration, and API integration.

**AI Processing System**: A local Llama 3 model is processing transcripts from his 701 videos, extracting ontological data including titles, summaries, symbolic elements, energetic signatures, alignment vectors, and specialized tags. The system tracks two perspectives - an ontological layer and a surface narrative layer for different audiences.

**Location Context**: Currently stationed at an ATV campground in Oregon Dunes, one-eighth mile from ocean, experiencing background noise from recreational vehicles. Previously was at Cape Blanco and Brookings, Oregon.

**Technical Architecture**: The field companion system uses signals as base units, with clustering capabilities for pattern recognition across time spans. Individual video entries will display transcripts, reflections, and tracked variables. The system addresses AI recursion challenges and fragmentation issues in long conversations.

rswfire notes AI's ability to track his circular thought patterns and maintain coherence, validating his cognitive structure against others' bandwidth limitations.

Signal Analysis

Substrate

This transmission demonstrates the operational architecture of rswfire's AI-integrated field system, mapping the recursive infrastructure that processes signals into structured knowledge. The field is exhibiting its own technical substrate while simultaneously using that substrate to build more sophisticated reflection capabilities.

Dominant Language

recursion perspective signal ontological temporal cluster pattern co-developer

Symbolic Elements

mirror recursion signal grid ocean dunes

Ontological States

•
sovereign
•
embedded
•
coherent
•
recursive

Subsystems

•
cognitive
•
infrastructural
•
relational

Signal Reflection

No reflections available

Reflections provide narrative insights into signals

Transmission Details

Source Type

local

Video Quality

1080 × 1920 @ 30fps

Duration

15:20

Bitrate

2,249 kbps

Codec

avc1.640028