Altive — Governance for AI-Assisted Software Development

The VibeOps framework

VibeOps — Governance for AI-Assisted Software Development.

VibeOps is Altive’s framework for governing AI-assisted, or “vibe”, coding in regulated organisations. It turns informal AI usage into a deliberate, auditable practice, so you keep the speed of AI assistance while staying able to show how your code was produced.

The governing principle is simple: governed AI development is both faster and safer than the alternatives. Banning the tools does not remove the risk, it pushes usage into the shadows where you cannot see or audit it. Ignoring the tools lets unreviewed, sometimes insecure code accumulate unchecked. Governed usage brings AI development into the open, with evidence, without slowing your teams down.

BanDriftGovern

Banning fails. Drift is the risk. Governance is the answer.

The ADOPT methodology

How an Altive engagement moves you from shadow usage to evidence.

ADOPT is a five-phase sequence. Each phase builds on the last, ending with a governance capability your organisation owns outright.

  1. APhase 01

    Assess

    We start by understanding how AI coding is actually used across your teams today, the tools in play, where shadow adoption hides, and the risk that already sits in your codebase. The output is a clear, evidence-based picture of your current position rather than assumptions.

  2. DPhase 02

    Design

    We design governance that fits the way your engineers already build, mapping controls to your risk tiers and regulatory obligations. The aim is proportionate guardrails that enable delivery, not a heavyweight process that teams route around.

  3. OPhase 03

    Operate

    We put the governance into the flow developers already use, so it runs as part of normal delivery rather than as a separate gate. AI-assisted development continues at speed, now inside agreed boundaries that are visible and measurable.

  4. PPhase 04

    Prove

    Every stage emits linked audit evidence, so the path from prompt to production is traceable and examiner-ready by design. This is the phase that turns informal AI usage into something you can demonstrate to an auditor or regulator on request.

  5. TPhase 05

    Transfer

    We hand over a governance capability your organisation owns and can sustain without us. Roles, runbooks and ownership move to your teams, so the controls keep producing evidence long after the engagement ends.

Governed AI Development Maturity Model

Five levels, from unaware to self-sustaining.

Most organisations start lower than they expect. The ladder shows the outcome at each level, so you can see where you are and what good looks like. It is a teaser, not the full assessment.

  1. Level0
    Unaware

    AI coding is happening but unacknowledged. There is no view of where it is used, and no record of what it produced.

  2. Level1
    Defined

    Basic expectations exist on paper. Some policy is written down, but it is inconsistently applied and largely unverifiable.

  3. Level2
    Managed

    Governance is applied consistently across teams, with controls tied to risk and clear ownership of how AI assistance is used.

  4. Level3
    Evidenced

    AI-assisted changes carry linked audit evidence, so the path from prompt to production can be demonstrated on request.

  5. Level4
    Self-Sustaining

    Your organisation owns and continually improves the capability without external support, with evidence produced as a by-product of normal delivery.

Not sure where your organisation sits today?

Find out your level

How this maps to regulation

VibeOps supports alignment with the frameworks your examiners care about.

Governed AI development produces the visibility and evidence these frameworks expect. We map our governance to each, so your AI usage supports alignment rather than working against it.

DORA

Demonstrable governance and traceability over ICT and AI in the software lifecycle.

ISO 42001

A managed approach to AI use with defined controls, ownership and evidence.

ISO 27001

Information-security controls extended to AI-assisted development activity.

GDPR / FADP

Visibility and records that support accountability over how data is handled in AI workflows.

NIST AI RMF

Governing, mapping and measuring AI risk across the development flow.

OWASP LLM Top 10

Awareness of and controls around common LLM and AI-assisted coding risks.

Altive supports alignment with these frameworks and standards. We do not certify, audit or issue certifications, and we make no guarantee of compliance.