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Research & field notes

Legal intelligence, AI systems, and what the evidence supports.

Substantive writing for law-firm operators and AI builders: discovery, intake, governance, implementation, and the infrastructure behind the work.

77 published · three editorial tracks · one diagnostic path

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October 21, 2026 · 8 min read

Automated editorial reviewAI Governance

Four Isolation Tiers and One Acceptance Test for AI-Written Code

Our recommendation: compare declared isolation using Plimsoll, gVisor and Firecracker documentation, then run a proposed acceptance test on the actual deployment.

AI GovernanceSandboxingAgent SecurityAI ImplementationCompliance Controls
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October 20, 2026 · 8 min read

Automated editorial reviewAI Governance

Build a Failure Ledger and Regression Set Before You Trust an AI Tool

Our recommendation: build a failure ledger, task rubric, regression set and human adjudication process, informed by Project Arena and Anthropic engineering guidance.

AI GovernanceAI EvaluationAgent TestingLaw Firm OperationsRisk Management
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October 20, 2026 · 8 min read

Human reviewedAI Governance

4 Controls That Keep a Law Firm AI Agent's Refusals Outside the Model

Our recommendation: enforce permissions outside model judgment and test refused actions for zero side effects. OWASP guidance informs the design; the implementation must still be verified.

AI GovernanceAgent SecurityPrompt InjectionLaw Firm OperationsApproval Controls
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October 19, 2026 · 7 min read

Review provenance not recordedAI Governance

Why Similar AI Agent Scores Hide Different Failures: A Law Firm Governance Test

A preprint on 1,292 conversation turns found that similar overall scores can hide very different rule failures. Here is how law firms can test agents rule by rule.

AI GovernanceAgent EvaluationModel Context ProtocolLaw Firm OperationsHuman Review
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