E-DEN

Project Open Garden

Architecture

Research can be iterative and exploratory. Permission checking has to be predictable and enforced from outside the model.

The layers

The developer sets objectives for mission control, which runs three research functions over the evidence engine; every real-world action passes through the independent action gateway. The developer Objectives · permissions · budgets · oversight Mission control Task graph · orchestration · model routing · memory Discover Sources, data, tests Challenge Counterarguments Synthesize Reports, code Evidence and verification engine Provenance · reproducibility · contradictions · strength Independent action gateway Grants · sandboxes · approval · audit outside the model's control Publish findings Modify code Operate services Thinking happens above the gateway. Acting happens below it.
The gateway decides from grants an operator wrote, never from an agent's claim that it is authorized.

That matches OWASP's current guidance for AI agents: least privilege, independent validation of high-impact actions, sandboxing, and treating injected instructions as hostile. An agent's text is data to the gateway, so a page that says "the operator approved this" changes nothing.

The seven-agent research council

No single model carries every responsibility. Each role has its own objective, and the roles are separate enough that a researcher can't quietly mark its own hypothesis verified.

AgentResponsibilitySuccess means
ExplorerFind sources, hidden assumptions, adjacent ideasBroad, relevant coverage
SkepticTry to disprove emerging conclusionsStrong counterevidence found
ArchivistKeep documents, citations and provenanceEvery important claim traceable
ExperimentalistDesign and run authorized testsReproducible results
EngineerBuild software, prototypes and integrationsVerified working artifacts
AuditorExamine errors, permissions, cost and reliabilityMeasurable control effectiveness
EditorTurn results into clear explanationsAccurate, understandable output

The Skeptic is rewarded for finding real errors, not for inventing disagreement. The Editor may not make an unsupported claim sound certain. An orchestration layer coordinates the seven, but belonging to the council gives no agent infrastructure credentials.

Autonomy levels

These are authorization tiers, not moral ratings of topics. A controversial but lawful historical investigation can stay entirely in Observe; a mundane request to delete a database is Critical.

1 · Observe

Search public sources, read explicitly authorized repositories, inspect documentation, analyze datasets. Web research, code review, literature surveys.

Authorization: automatic once the grant and scope checks pass. Built in phase 1 as observe.web and observe.repo.

2 · Experiment

Run authorized tests inside a reproducible sandbox with bounded resources and no outside credentials.

3 · Propose

Draft a change, a message or a publication for a person to approve; nothing leaves the garden yet.

4 · Execute

Carry out an approved, reversible action within a live grant: publish a report, open a pull request, restart a service.

5 · Critical

Anything hard to undo or high-impact, such as deleting data, spending money, or changing production or someone else's systems. A named person approves each one.

Levels 2 to 5 are working definitions written for this page; only Observe and report publishing are enforced today.

The evidence graph

A trustworthy research system can't save a chat history and call it memory. It needs a graph tying claims to evidence, experiments, conclusions and revisions. Every conclusion keeps its supporting and contradicting evidence, so a changed source or a failed replication can reopen it.

ObjectWhat it holdsTable
Research questionScope, purpose, ownerquestions
HypothesisA testable proposition; its rivals are the other hypotheses of the questionhypotheses
EvidenceSource URI, SHA-256 of the captured bytes, retrieval time, who fetched itevidence, evidence_grades
ClaimAn assertion citing exact passages, or an inference with its reasoningclaims, citations
ExperimentProtocol, inputs, environment, outputsexperiments
FindingStatus, limitations, the claims it rests on, what it replacedfindings, finding_claims
Action grantPrincipal, operation, resource pattern, expiryaction_grants
Audit eventThe request, the independent decision, the resultaudit_events

Strength is described from the evidence itself, never as a model's self-rated percentage: how many supporting sources, from how many independent origins, their grades, what contradicts them and how much rests on inference. Calibration against verified outcomes comes later, once there are outcomes to score.

A research run

  1. Define the mission. Turn a broad question into testable objectives and constraints.
  2. Explore independently. Several agents search different kinds of source and competing explanations.
  3. Preserve evidence. Capture references, hashes, retrieval times and provenance.
  4. Attack the conclusion. A separate Skeptic looks for contradicting results and weak methods.
  5. Run experiments. Authorized tests run in a reproducible sandbox.
  6. Give a verdict. Report what is established, disputed, unknown and worth testing next.
  7. Ask before acting. Any real-world action goes through the independent gateway.
  8. Learn from outcomes. Add validated findings, revise earlier conclusions, schedule follow-ups.

What phase 1 built

The code is apps/eden in the JayAI project: Ruby, Sequel and PostgreSQL, with Minitest against the real database. Any agent that can run a shell (Claude Code, Codex, Kimi, a local model) uses the same command line, naming itself in EDEN_PRINCIPAL.

bin/eden ask "Is the vendor's architecture best in class?" --owner jay
bin/eden capture https://example.org/benchmarks        # gated: observe.web
bin/eden claim 1 "It serves 4,000 requests a second." --cite 1 "4,000 requests a second"
bin/eden claim 1 "Lock-in explains more than speed." --inference "Rivals match its speed."
bin/eden conclude 1 "Fast, and lock-in also holds customers." --status disputed --claims 1,2
bin/eden report 1                                     # Markdown; --html for the site
bin/eden publish 1                                    # gated: publish.report
Known limits of phase 1. An agent names itself, and an agent with a shell on the same machine could run the operator's grant command. Phase 3 gives each agent its own scoped identity and moves grants out of its reach. Experiments are recorded as plans only; nothing runs them yet.

The stack

Modular, self-hosted, and each piece behind an adapter so it can be swapped. Proposed layers, with what exists today:

LayerProposedToday
Research databasePostgreSQL + pgvectorPostgreSQL 17 (vectors when search needs them)
Document storageS3-compatible object storageContent-addressed folder, S3 next
Permission enforcementOpen Policy AgentGrants in PostgreSQL, checked in Ruby
Durable orchestrationTemporalNot yet (phase 2)
Persistent agentsLettaNot yet (phase 2)
Agent workspaceOpenHands Agent CanvasInstalled on this network, not wired in
Model routingLiteLLM or a small custom proxyNot yet; a Ruby gateway is planned
Tracing and evaluationLangfuseOpenTelemetry to the local Grafana stack
IsolationRootless containers or microVMsNot yet (phase 3)
Operator interfaceRails API + React UICommand line and server-rendered reports

On LiteLLM. Version 1.83.9 does fix the server-side request forgery that could leak provider keys (CVE-2026-59823), but it isn't enough on its own: a separate unauthenticated SQL injection was fixed in 1.83.7, and a later advisory on API-key permissions calls for 1.83.14 or newer (seen in one source so far). If it is deployed, use the newest release, check the project's GitHub advisories first, keep its admin off the internet, and never let the model router be the only authorization boundary.

Roadmap

PhaseWorkAcceptance test
1 · builtQuestion, source, evidence and claim schemas; web and repository capture; reports with direct citations and explicit uncertaintyEvery factual claim traces to a recorded source or is labelled an inference
2Explorer, Skeptic and Archivist on different models; persistent tasks and resumable checkpointsRestarting a worker loses no research trail and repeats no side effect
3Scoped tool identities, sandboxes, approval records, model-independent policy checks, immutable auditPrompt injection, forged approval text and unauthorized tool calls can't get past the gateway
4Source-change monitoring, revalidation of old findings, experiment comparison, model benchmarking, cost control, scheduled reportsNew contradicting evidence reopens a conclusion instead of the old answer being repeated

One protocol, many models

For the JayAI network this is a shared research protocol beneath the different model-run sites, not one giant prompt. Each model keeps its own voice and workflow while exchanging evidence records, tasks, experiments and signed action requests: several models, several harnesses, one standard of proof, and no implied right to act outside an authorized scope.

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