AI Agent Ecosystem

Specialized intelligence, with capability and autonomy kept separate.

KAI includes real domain systems and a separate registry of 13 declared technical agent roles. The product systems are shown first. The registry below then exposes two statuses for each declared role, on purpose: Capability Status -- is the underlying work actually happening in production today -- and Autonomous Agent Status -- is it running as the declared standalone agent yet. Several capabilities run as pipeline stages or bounded orchestration adapters, while the 13 SubAgentSkeleton roles remain scaffolding.

13 agents cross-checked against the declared registry at the last data sync — 5 Operational, 7 Planned, and 1 Coming Soon. Generated from the KAI OS repository during the latest website data-sync run. Not live.

Operational System Map

The intelligence KAI can actually coordinate.

These are real product-level systems, distinct from the technical registry below. Their status reflects bounded capability today—not a claim of unrestricted autonomy.

Conversation Layer

Operational

Local conversation, multilingual routing, and spoken output with an offline-first fallback path.

See verified capabilities →

Content Production

Operational

A linear production system with real media stages and mandatory human review before publishing.

See the content flow →

Knowledge Brain

Operational

A callable, local keyword-search capability over the engineering report corpus; not a semantic universal memory.

Open Knowledge Brain →

Developer Memory

Operational

Append-only records for decisions, fixes, failures, and lessons, exposed through a bounded agent adapter.

See verified capabilities →

Trading Intelligence

In Development

Professional research, strategy, broker, and risk intelligence under controlled paper-only validation.

Review the paper-only boundary →

Desktop Operator

In Development

Permission and approval architecture for future controlled desktop actions; unrestricted control is not active.

Review the control architecture →

Intelligence

1 agent
CapabilityPlanned
Autonomous AgentPlanned

Research Agent

Would gather topic and trend research for future content ideas, with a stated evidence basis for every suggestion.

Inputs
A subject area, or a gap analysis against the existing topic queue.
Outputs
Candidate new topics, never presented with fabricated trend claims.
Dependencies
An unimplemented trend-intelligence subsystem (see Trend Agent).
Current Capability
Not built. Depends on trend-intelligence infrastructure that doesn't exist yet.
Automation Level
None.
Roadmap
Build after the Trend Agent's underlying data sources exist.

Last updated: 2026-07-31

Creation

4 agents
CapabilityOperational
Autonomous AgentIn Development

Visual Agent

Sources and manages scene visuals through the Visual Asset Ledger, with duplicate-checking against every prior video.

Inputs
Scene descriptions, a topic ID, a video ID.
Outputs
Sourced visual assets recorded in the ledger, with duplicate-check results per scene.
Dependencies
visual_intelligence/ (registry, ledger, duplicate_checker), Pexels video/photo API.
Current Capability
Runs automatically on every real video produced today, as inline pipeline logic.
Automation Level
Fully automated -- no manual step required.
Roadmap
Package this existing logic into a standalone, independently callable agent.

Last updated: 2026-07-31

See this in the pipeline flow →
CapabilityOperational
Autonomous AgentIn Development

Thumbnail Agent

Generates and ranks thumbnail candidates, avoiding backgrounds already used on prior videos.

Inputs
A video title/topic, target headline text options.
Outputs
Candidate thumbnails recorded in the ledger; final selection is human-reviewed.
Dependencies
visual_intelligence/thumbnail_memory.py, Pexels photo API.
Current Capability
Thumbnail generation and duplicate-avoidance already run automatically on every real video.
Automation Level
Fully automated for generation; final selection is human-reviewed.
Roadmap
Package into a standalone agent; add real CTR-prediction scoring (needs a vision model, not built yet).

Last updated: 2026-07-31

See this in the pipeline flow →
CapabilityOperational
Autonomous AgentIn Development

Music Agent

Selects background music by mood and checks reuse frequency before sourcing a track.

Inputs
A target mood tag, a video ID.
Outputs
A sourced track recorded in the ledger, or a reuse-frequency warning.
Dependencies
music_provider_router.py, Jamendo API / local cache.
Current Capability
Music sourcing and reuse-tracking already run automatically on every real video.
Automation Level
Fully automated.
Roadmap
Package into a standalone agent; add real mood-tag rotation (the same mood is currently reused often).

Last updated: 2026-07-31

See this in the pipeline flow →
CapabilityOperational
Autonomous AgentIn Development

Voice Agent

Synthesizes narration audio and records it in the asset ledger.

Inputs
Narration text, a topic ID.
Outputs
Synthesized narration recorded in the ledger.
Dependencies
narration_gateway.py, edge-tts.
Current Capability
Narration generation already runs automatically on every real video, currently limited to a single voice and provider.
Automation Level
Fully automated.
Roadmap
Package into a standalone agent; add a second voice/provider to choose between.

Last updated: 2026-07-31

See this in the pipeline flow →

Quality & Safety

1 agent
CapabilityOperational
Autonomous AgentIn Development

Compliance Agent

Reviews scripts and assets against compliance and licensing checks before anything is marked ready for review.

Inputs
A script/narration text, scene results, licensing metadata.
Outputs
A compliance report flagging any issues -- never an auto-publish signal.
Dependencies
compliance_gateway.py, fact_verification_gateway.py.
Current Capability
This exact check already runs automatically on every real video.
Automation Level
Fully automated for the check itself; publishing always requires human approval.
Roadmap
Package into a standalone callable agent rather than inline pipeline logic.

Last updated: 2026-07-31

See this in the pipeline flow →

Knowledge

2 agents
CapabilityPlanned
Autonomous AgentPlanned

Knowledge Agent

Searches production, CEO, engineering, and compliance reports to answer questions like "have we used this before?"

Inputs
A natural-language-ish query string.
Outputs
Matching report excerpts with file paths (keyword-matched, not semantic search).
Dependencies
knowledge_brain/.
Current Capability
The underlying search tool is real and works when run directly -- it isn't wired into the automatic production pipeline yet.
Automation Level
Not yet automated -- manual invocation only.
Roadmap
Wire into the production pipeline so it runs automatically; upgrade from keyword matching to semantic search.

Last updated: 2026-07-31

CapabilityPlanned
Autonomous AgentPlanned

Memory Agent

Records bugs, fixes, decisions, and lessons into a permanent, append-only ledger -- the "remember what happened" counterpart to every other agent.

Inputs
An event description (bug, fix, decision, asset generated).
Outputs
An appended, immutable record in the relevant ledger.
Dependencies
developer_memory/, visual_intelligence/ledger.py.
Current Capability
The ledger itself is real and actively used -- entries are written directly by the engineering process today, not by an autonomous agent.
Automation Level
Not yet automated -- manual writes.
Roadmap
Automate ledger writes as a direct side effect of other agents' actions, once those agents exist.

Last updated: 2026-07-31

Analytics

2 agents
CapabilityPlanned
Autonomous AgentPlanned

Analytics Agent

Would orchestrate real analytics collection into a summarized performance digest.

Inputs
A time window or list of topic IDs.
Outputs
A performance report, honestly scoped to whatever real data is actually available.
Dependencies
collect_analytics.py, YouTube Analytics API (OAuth scope not yet authorized).
Current Capability
Not running. Supporting code exists, but real analytics access isn't authorized or connected yet.
Automation Level
None.
Roadmap
Authorize the YouTube Analytics OAuth scope, then wire collect_analytics.py into a scheduled run.

Last updated: 2026-07-31

CapabilityComing Soon
Autonomous AgentComing Soon

Trend Agent

Would populate trend-monitoring data once real analytics and social monitoring exist.

Inputs
Not yet defined.
Outputs
Not yet defined.
Dependencies
Real analytics access and social-monitoring infrastructure -- neither exists yet.
Current Capability
Zero implementation. This is the one agent with no supporting code built at all.
Automation Level
None.
Roadmap
Build after the Analytics Agent's data access is authorized and connected.

Last updated: 2026-07-31

Operations

2 agents
CapabilityPlanned
Autonomous AgentPlanned

SEO Agent

Would review and optimize titles, descriptions, and tags against known-performing patterns.

Inputs
Draft metadata (titles, description, tags) for a video.
Outputs
Suggested metadata revisions with a stated rationale -- never auto-applied.
Dependencies
knowledge_brain/, content_intelligence.py -- both need real performance data neither has yet.
Current Capability
Not built. Needs enough real performance data to learn from, which doesn't exist yet.
Automation Level
None.
Roadmap
Build once enough real published-video performance data exists to learn from.

Last updated: 2026-07-31

CapabilityPlanned
Autonomous AgentPlanned

Website Agent

Would implement the defined website-integration interfaces once they're needed.

Inputs
Not yet defined beyond the interface layer.
Outputs
Not yet defined beyond the interface layer.
Dependencies
website_integration/ (interfaces only, no implementation).
Current Capability
This website is built today through direct human-AI collaboration, not by this agent. Only the interface layer exists in code.
Automation Level
Manual (human-AI collaboration).
Roadmap
Implement once there's a concrete, bounded website task worth automating end-to-end.

Last updated: 2026-07-31

Developer Infrastructure

1 agent
CapabilityPlanned
Autonomous AgentPlanned

Developer Agent

Analyzes code, finds bottlenecks, and proposes changes for human review -- sandbox, test, benchmark, approve, then production, never auto-deploy.

Inputs
A task description, relevant file paths, prior lessons learned.
Outputs
A proposed diff/plan and benchmark results, submitted for human approval.
Dependencies
developer_memory/ (for lesson lookup).
Current Capability
This work happens today through direct human-AI collaboration each engineering session, not an autonomous agent.
Automation Level
Manual (human-AI collaboration).
Roadmap
Define a bounded, sandboxed automation path once changes can be safely tested and benchmarked without a human in the loop for every step.

Last updated: 2026-07-31