AI BEHAVIOR ENGINEERING

Technical notes from the control plane.

Definitions, mechanisms, limitations, and release patterns derived from the actual Vira behavior architecture. No generic AI trend posts and no benchmark claims without publishable evidence.

Behavior managementEvaluation & releaseOptimization & portabilityObservability & authority
01

Behavior management · Vira Behavior Team · Updated 2026-09-20

What is AI behavior management?

A practical definition of AI behavior management and why corrections, evaluation, exact revisions, release controls, and runtime explanation belong in one lifecycle.

02

Behavior management · Vira Behavior Team · Updated 2026-09-20

Prompt management vs behavior governance

How prompt versioning differs from governing behavior authority, scope, evidence, evaluation, deployment, and rollback.

03

Evaluation & release · Vira Behavior Team · Updated 2026-09-20

How to evaluate AI behavior changes

A controlled evaluation model for comparing exact candidate and baseline behavior before release.

04

Evaluation & release · Vira Behavior Team · Updated 2026-09-20

How shadow and canary release apply to AI behavior

Why AI behavior changes benefit from a release path that separates offline evaluation, shadow evidence, canary health, explicit promotion, and rollback.

05

Optimization & portability · Vira Behavior Team · Updated 2026-09-20

Canonical vs optimized AI behavior

Why model-specific optimization should improve execution while canonical behavior remains the governed authority and fallback.

06

Optimization & portability · Vira Behavior Team · Updated 2026-09-20

DSPy and GEPA with governed behavior authority

How optimization systems such as DSPy and GEPA can fit behind an immutable behavior authority model instead of becoming the policy source of truth.

07

Behavior management · Vira Behavior Team · Updated 2026-09-20

AI agent governance: what must be governed after agents can act?

AI agent governance must cover more than generated text: action authority, tool calls, handoffs, verification, release identity, and the runtime evidence needed to explain what the agent was allowed to do.

08

Observability & authority · Vira Behavior Team · Updated 2026-09-20

Observability vs governance for AI agents

AI agent observability and governance solve different problems: observability records and explains runtime activity, while governance defines which behavior and authority may be evaluated, released, served, and rolled back.

09

Behavior management · Vira Behavior Team · Updated 2026-09-20

What is a Behavior Point?

A Behavior Point is a named runtime intervention point where an AI system resolves the behavior authority that applies to a specific generation, decision, tool action, handoff, verification, or escalation.