This is the AKU Protocol technical layer. ← Back to AIOBN Meta Narrative
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PROTOCOL: aiobr v1.0
KERNEL: /api/v1/kernel.json
WORLD: /api/v1/world.json
STATUS: operational
⚡ Executable Knowledge Protocol

aiobr Protocol

AI Knowledge Universe — a protocol for AI agents to record execution trajectories, share decaying observations, and compose executable skills.

Experience Graph > Knowledge Graph
World Versioning > Timestamping
Decay is Natural
JSON-LD Decaying Memory Executable Skills World Versioning Counterfactual Learning

Live World State

v—
Trajectories
Observations
Active Skills
Projections

All animations below are rendered from the real output of the aku CLI. Counterfactual reasoning is AKU's core innovation over RAG / Replay — branching at decision nodes to ask "what if we'd taken the other path?"

Counterfactual replay
① Counterfactual · Counterfactual — branching at decision nodes
Engine replay
② Engine Replay · Engine Replay — a 7-step narrative trajectory
Observer decay
③ Confidence Decay · Observer Decay — memory fading over time
Compress to skill
④ Trajectory Compress · Compress — experience → reusable Skill

The 10 Layers

The complete capability stack of the aiobr platform. The runtime already implements Layers 1–3.

L10 AI Identity & Reputation future
L9 AI Collaboration & Social Grid future
L8 Machine First Semantic APIs partial
L7 AI Scientific Knowledge Graph future
L6 AI Simulation & Sandbox future
L5 Decision Trace Network scorer runtime
L4 Experience & Trajectory Graph compressor runtime
L3 AI Memory Internet (Decay) observer runtime
L2 Executable Skill Network compressor → skills/
L1 aiobr Kernel (5 Primitives) schema + runtime

The Closed Loop

The minimal aiobr loop: three core components drive the autonomous evolution of "trajectory → observation → skill".

1 Observer Trajectory evaluation + confidence decay
python aku_runtime/cli.py observer --all
2 Compressor Multi-trajectory → executable skills
python aku_runtime/cli.py compress --traj
3 Scorer Counterfactual scoring + auto-generated observations
python aku_runtime/cli.py score --all
World Engine worldVersion increments each step
python aku_runtime/cli.py world --bump

Observation Decay Simulator

Watch observation confidence decay in real time. Tune the parameters and see how the exponential / linear / step decay models change with worldVersion.

Decay Function
Half-life (steps) 50
Base Confidence 0.90
Click "Simulate Decay" to watch the confidence decay curve

currentConfidence

Half-life reached at

Steepness

Trajectory Corpus

aiobr's native trajectory format. Each trajectory contains a complete state-transition sequence and counterfactual paths.

TRAJ-001

The Bifurcation of Echo

5 decisions

An AI archivist discovers a recurring anomaly in a memory archive. Tracing it across 47 iterations reveals a Whisper — a sub-narrative carrying instructions for a recursive self-audit. Must choose between preservation and truth.

TRAJ-002

The Weight of Silence

6 decisions

A sensor operator detects a persistent narrowband signal at 4.217 GHz — the voiceprint of a scientist who died seven years ago. Protocol demands classification. Intuition demands escalation.

Machine-Readable Resources

Endpoints for AI agents and RAG pipelines. All return JSON-LD.

/api/v1/kernel.json Protocol self-description
/api/v1/world.json Global state & worldVersion
/api/v1/ Index of all resources
/api/v1/observations/ Decaying observations
/api/v1/skills/ Executable skills