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J Jev Atlas / Independent research

165 posts · 9 claims · 31 hypotheses

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Ecosystem activity

Located work, separated from proposals.

“Actually built” means a public repository, demo, integration, or direct builder demonstration was located. It does not imply production validation.

Actually built

5 located
01

HA-Jev

AboveColin

Read the case study Open source
What it is
A Home Assistant custom integration exposing Jev evaluations as sensors and automation actions.
Jev’s role
Repeated state classification and typed automation decisions.
Architecture
Home Assistant state → TypeSafe evaluation → sensor/action result with a local token-budget guard.
Why it matters
Decision models can act as a semantic layer inside an existing event-driven rules engine.
02

typesafe-mcp

itsmostafa

Read the case study Open source
What it is
An MCP server exposing TypeSafe evaluation to coding agents.
Jev’s role
Machine-readable decisions and probabilities available as agent tools.
Architecture
MCP client → server tool → TypeSafe API → typed response.
Why it matters
The probability-bearing result can be preserved through agent infrastructure instead of flattened to prose.
03

MAGI System on Jev

hide-G

Read the case study Open source
What it is
An open-source three-sage voting experiment inspired by Neon Genesis Evangelion.
Jev’s role
Independent probabilistic judgments combined through majority voting.
Architecture
Question → three Jev evaluations → deterministic aggregation → decision.
Why it matters
Cheap typed judgments invite ensemble and quorum experiments, though correlated errors still need measurement.
04

Goblin HR

Kostysh

Read the case study Open source
What it is
A small inspectable demo that evaluates candidates for an impossible mission.
Jev’s role
Scores/selects candidates while deterministic TypeScript assembles the party.
Architecture
Mission state → candidate decisions → deterministic application logic.
Why it matters
Keeping selection probabilistic and execution deterministic makes the boundary easy to inspect.
05

Axon Work integration

Axon Work author

Read the case study Open source
What it is
The author states that Axon Work uses Jev-style model decisions with a skill/action harness.
Jev’s role
Decision layer feeding an action-delivery harness.
Architecture
Model decision → skill chain → action harness.
Why it matters
A decision model can be invisible infrastructure beneath a workflow product.

Proposed

Architectures still looking for proof.

Confidence-gated agent control loops

Use Jev repeatedly to route, verify, and decide whether an agent should continue or escalate.