System Architecture | Tractatus AI Safety Framework

Behavioral Training (Constitutional AI)

Structural Enforcement (Tractatus)

Jailbreaks often work by manipulating the AI's internal reasoning. Tractatus boundaries operate external to that reasoning—the AI doesn't directly evaluate governance rules. While not foolproof, this architectural separation makes manipulation significantly harder.

Tractatus works with any agentic AI system—Claude Code, LangChain, AutoGPT, CrewAI, or custom agents. The governance layer sits between your agent and its actions.

Tractatus Runtime-Agnostic Architecture Diagram showing Agent Runtime Layer, Tractatus Governance Layer with six services, Persistent Storage Layer, and Human Approval Workflows

Your AI agent (any platform). Handles planning, reasoning, tool use. Tractatus is agnostic to implementation.

Six external services enforce boundaries, validate actions, monitor pressure. Architecturally more difficult for AI to bypass.

Immutable audit logs, governance rules, instruction history. Independent of AI runtime—can't be altered by prompts.

Blocks AI from making values decisions (privacy, ethics, strategic direction). Requires human approval.

Early Promise: Values boundaries enforced externally—harder to manipulate through prompting.

Stores instructions externally with persistence levels (HIGH/MEDIUM/LOW). Aims to reduce directive fade.

Early Promise: Instructions stored outside AI—more resistant to context manipulation.

Validates AI actions against instruction history. Aims to prevent pattern bias overriding explicit directives.

Early Promise: Independent verification—AI claims checked against external source.

Monitors AI performance degradation. Escalates when context pressure threatens quality.

Early Promise: Objective metrics may detect manipulation attempts early.

Requires AI to pause and verify complex operations before execution. Structural safety check.

Early Promise: Architectural gates aim to enforce verification steps.

Facilitates multi-stakeholder deliberation for values conflicts. AI provides facilitation, not authority.

Early Promise: Human judgment required—architecturally enforced escalation for values.

Click any service node or the central core to see detailed information about how governance works.

Interactive visualizations demonstrating how Tractatus governance services monitor and coordinate AI operations.

Tractatus is deployed in production using Claude Code as the agent runtime. This demonstrates the framework's real-world viability.

Our production deployment uses Claude Code as the agent runtime with Tractatus governance middleware. This combination provides:

Results from 6-month production deployment:

95% instruction persistence across session boundaries
Zero values boundary violations in 127 test scenarios
100% detection rate for pattern bias failures
<10ms performance overhead for governance layer

*Single-agent deployment. Independent validation and multi-organization replication needed.

View Claude Code Implementation Diagram →

Real-World Testing

This isn't just theory. Tractatus is running in production, handling real workloads and detecting real failure patterns.

Early results are promising—with documented incident prevention—but this needs independent validation and much wider testing.

This is early-stage work. While we've seen promising results in our production deployment, Tractatus has not been subjected to rigorous adversarial testing or red-team evaluation.

"We have real promise but this is still in early development stage. This sounds like we have the complete issue resolved, we do not. We have a long way to go and it will require a mammoth effort by developers in every part of the industry to tame AI effectively. This is just a start."

— Project Lead, Tractatus Framework

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This framework is a starting point for exploration, not a finished solution. Taming AI will require sustained effort from the entire industry—researchers, practitioners, regulators, and ethicists working together.

Tractatus demonstrates how structural enforcement may complement behavioral training. We invite researchers and practitioners to evaluate, critique, and build upon this work.

Read Documentation View Research Implementation Guide