📡 Signals

Atomic units of lived data. The foundation of pattern recognition and synthesis.

What is a Signal?

A signal is the atomic unit of lived data in Autonomy. It represents a single moment of documented reality — raw capture that forms the input layer for AI-powered pattern detection and synthesis.

Signals are not content. They're not posts. They're timestamped documentation, optionally geolocated, preserved with full structural fidelity.

Every signal belongs to a realm and has a type (the medium) and optional context (the intent).

Signal Types (Medium)

DOCUMENT

Text in any form — writing, notes, code, references. The most common signal type.

PHOTO

Visual capture. Images preserved with technical metadata when available.

TRANSMISSION

Audio or video recordings. YouTube videos. Podcast episodes. Processed via transcript.

CONVERSATION

Dialogue logs. AI chat transcripts. Co-created content from back-and-forth exchange.

Signal Context (Intent)

Context describes why a signal was created. It's optional but provides valuable metadata for synthesis and pattern recognition.

CAPTURE

Default — generic documentation, intent to be determined

NOTE

Quick capture, ephemeral thought

JOURNAL

Reflective writing, daily log

CODE

Technical artifact, implementation

REFERENCE

External source, citation

OBSERVATION

Field note, documented reality

ARTIFACT

Created work, finished piece

Signal Structure

Core Fields

signal_idUnique identifier (ULID format)

realm_idWhich realm this signal belongs to

signal_typeMedium: DOCUMENT, PHOTO, TRANSMISSION, CONVERSATION

signal_contextIntent: CAPTURE, NOTE, JOURNAL, CODE, REFERENCE, OBSERVATION, ARTIFACT

signal_titleBrief title

signal_summaryLonger summary or description

signal_authorWho created/captured this signal

signal_temperatureImportance (-1.0 to 1.0, default 0.0)

signal_statusACTIVE, PENDING, REJECTED, FAILED, or ARCHIVED

signal_visibilityPUBLIC, PRIVATE, SANCTUM, or SHARED

Analysis Fields

Surface and structural metadata extracted through analysis.

Surface Layer

signal_actionsArray of visible actions in the signal

signal_environmentContext at time of signal creation

signal_entitiesCategorized entities: people, places, infrastructure, organizations, concepts, media

signal_densityRecursion/complexity metric (-1.0 to 1.0)

Structural Layer

signal_energyEnergetic state (e.g., methodical, resolute, exhausted)

signal_stateLife/project state (e.g., infrastructure-building, crisis, integration)

signal_orientationDirectional facing (e.g., toward sovereignty, toward extraction)

signal_substrateStructural/conceptual foundation underlying the signal

signal_ontological_statesArray of being-states (e.g., sovereign, embedded, coherent)

signal_symbolic_elementsArray of recurring motifs/symbols (e.g., mirror, archive, trail)

signal_subsystemsArray of engaged subsystems (e.g., cognitive, infrastructural, relational)

signal_dominant_languageArray of key semantic patterns shaping the signal

Temporal Data

stamp_createdWhen the original content was captured/created

stamp_importedWhen signal was ingested into the system

stamp_updatedLast modification timestamp (auto-updated)

Geospatial Data (Optional)

signal_locationPostGIS Point (PostgreSQL) - GeoJSON format

signal_latitude / signal_longitudeDecimal coordinates (MySQL)

Type-Specific Data

signal_metadataTechnical/immutable facts about the signal

signal_payloadThe actual content data

DOCUMENT - Metadata & Payload

Metadata:

word_count - Number of words
character_count - Number of characters
language - Language code (e.g., 'en', 'es')
file_extension - File extension (e.g., '.md', '.txt')
encoding - Character encoding (e.g., 'utf-8')
mime_type - MIME type (e.g., 'text/plain')

Payload:

content - The actual text content
format - Rendering format: 'plain', 'markdown', or 'html'

PHOTO - Metadata & Payload

Metadata (EXIF & Properties):

camera - Camera model
lens - Lens information
iso - ISO sensitivity
aperture - Aperture value (e.g., 'f/1.5')
shutter_speed - Shutter speed (e.g., '1/120')
focal_length - Focal length in mm
width - Image width in pixels
height - Image height in pixels
file_size - File size in bytes
mime_type - MIME type (e.g., 'image/jpeg')
color_space - Color space (e.g., 'sRGB')
timestamp_original - Original capture timestamp from EXIF
gps_altitude - GPS altitude in meters

Payload:

file_path - Local path or cloud storage URL
thumbnail_path - Optimized thumbnail path
original_filename - Original filename when uploaded

TRANSMISSION - Metadata & Payload

Metadata:

source_type - 'audio', 'video', or 'other'
source_url - YouTube URL, file path, etc.
youtube_id - YouTube video ID (if applicable)
youtube_channel - YouTube channel name
youtube_published_at - YouTube publish timestamp
youtube_thumbnail - YouTube thumbnail URL
timestamps - Array of topic markers: [{topic, timestamp}]
duration - Duration in seconds
bitrate - Bitrate in kbps
sample_rate - Sample rate in Hz
channels - Audio channels (1=mono, 2=stereo)
codec - Codec (e.g., 'h264', 'aac')
file_size - File size in bytes
mime_type - MIME type (e.g., 'video/mp4')
width - Video width in pixels
height - Video height in pixels
framerate - Framerate in fps
has_transcript - Boolean
transcript_method - 'ai', 'manual', or 'imported'

Payload:

file_path - Local file or cloud storage URL
transcript - Plain text transcript
timed_transcript - Array of timestamped segments: [{text, start, end}]

CONVERSATION - Metadata & Payload

Metadata:

platform - 'claude', 'chatgpt', 'gemini', 'remnant', or 'other'
model - Model identifier (e.g., 'claude-sonnet-4')
message_count - Total number of messages
turn_count - Number of back-and-forth exchanges
duration_minutes - Estimated conversation duration
total_tokens - Total token count (if available)
started_at - First message timestamp
ended_at - Last message timestamp

Payload:

messages - Array of messages: [{role, content, timestamp, metadata}]
summary - Generated conversation summary
key_points - Array of extracted key insights

Additional Fields

signal_tagsArray of tags for categorization

signal_embeddingVector embedding (1536 dimensions) for semantic search

History & Annotations

signal_historyAudit trail: [{timestamp, fields_changed, previous_values, trigger, user_id}]

signal_annotationsUser notes and synthesis feedback: {user_notes[], synthesis_feedback[]}

Visibility Levels

PUBLIC

Anyone can view this signal (if they have access to the realm).

SANCTUM

Only users with SANCTUM role or higher can view.

PRIVATE

Only the realm owner can view this signal.

SHARED

Reserved for future multi-user realm features.

Analysis Layers

Signals capture two distinct layers of analysis: surface and structural.

Surface Layer

Observable, concrete elements of the signal. What's directly visible.

Actions - What's happening in the signal
Environment - Context at time of creation
Entities - People, places, infrastructure, concepts mentioned
Density - Measure of recursion and conceptual complexity

Structural Layer

Underlying patterns, states, and orientations. What the signal is, not just what it contains.

Energy - Energetic state (methodical, resolute, exhausted)
State - Life/project state (infrastructure-building, crisis, integration)
Orientation - Directional facing (toward sovereignty, toward manifestation)
Substrate - Foundational structure underlying the signal
Ontological States - Being-states (sovereign, embedded, coherent)
Symbolic Elements - Recurring motifs and symbols (mirror, trail, extraction)
Subsystems - Which subsystems are engaged (cognitive, relational, infrastructural)
Dominant Language - Semantic field shaping the signal

Signal Lifecycle

Capture — Signal is created with minimal data: type, context, raw payload
Analysis — Surface and structural layers are extracted and stored
Clustering — Can be grouped with related signals in clusters
Pattern Detection — Cross-signal analysis identifies longitudinal patterns
Synthesis — Higher-order insights generated at cluster level

Key Principles

Signals are input for pattern recognition

Not content for consumption. Raw documentation of lived reality that analysis processes to identify patterns and generate insights.

Every signal belongs to a realm

Signals don't exist in isolation. They're always part of a realm, ensuring clear ownership and access control.

Analysis data can be manually edited

All analysis fields are editable. Changes are tracked in signal_history with trigger type (user_edit, re_synthesis, etc.).

Location is metadata, not a signal type

Geographic coordinates attach to any signal. Places are clustering context, not signals themselves.

📡 Signals

What is a Signal?

Signal Types (Medium)

DOCUMENT

PHOTO

TRANSMISSION

CONVERSATION

Signal Context (Intent)

CAPTURE

NOTE

JOURNAL

CODE

REFERENCE

OBSERVATION

ARTIFACT

Signal Structure

Core Fields

Analysis Fields

Surface Layer

Structural Layer

Temporal Data

Geospatial Data (Optional)

Type-Specific Data

Additional Fields

History & Annotations

Visibility Levels

PUBLIC

SANCTUM

PRIVATE

SHARED

Analysis Layers

Surface Layer

Structural Layer

Signal Lifecycle

Key Principles

Signals are input for pattern recognition

Every signal belongs to a realm

Analysis data can be manually edited

Location is metadata, not a signal type

Related Concepts

🏰 Realms

🔗 Clusters

🔮 Synthesis

Get Started

Documentation