AI Platform and Security · Module 1 · Foundations

Introduction to AI Platform and Security

The lesson establishes why an AI platform is an architectural and security problem rather than a model-selection question. Participants work through the four properties of AI systems that classical practice does not address, the book's definitions of AI Architecture and the AI platform, the table where governance requirements become platform capabilities, and the two fictional organisations. They finish by drafting a platform onboarding declaration of the kind Nordvik Region keeps for its staff assistant.

Lesson 1 of 25Chapter 160 minutes

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Learning objectives

After the lesson the participant can:

Key concepts

AI Architecture
The practice of designing, governing and operating AI systems, meaning their data, models, prompts, orchestration and surrounding controls, as codified, version-controlled, evidence-producing architecture, so that behaviour, risk, cost and legal position stay under the organisation's control throughout the lifecycle.
The AI platform
The shared, centrally operated set of capabilities on which an organisation's AI systems are built, run and observed, together with the controls that constrain them. It is a product with an owner, and its purpose is to make the safe path the easy one.
Controls outside the model
Because a large language model receives instructions and data through the same channel, any text it reads can act as a command. The platform therefore controls what retrieval may return, which tools may be called under whose authority, and what checks an output must clear.
Platform onboarding declaration
A file in the repository stating a system's purpose, legal position, components, data boundary and evidence. The onboarding pipeline provisions no gateway route until the declaration is complete.
Three tensions
Speed against control, autonomy against accountability and innovation against sovereignty, named in AI Governance, Chapter 1. This book meets each as a platform question: pipeline gates, identities with stop paths and logs, and routing, hosting and exit decisions per workload.

Interactive exercises

Do them here and get feedback at once. Choose a card and then where it belongs, or drag it.

Interactive exercise 1 · Match

Four properties and a fifth pressure

Match each property of AI systems named in the chapter with the response the platform gives to it.

Interactive exercise 2 · Scenario

A wider purpose for the staff assistant

Apply the onboarding declaration of Nordvik Region's staff assistant to a request from the business.

Teaching plan

10 minThe teacher opens with the model-selection question and asks participants where the incidents and audit findings in their own estates came from: the model, or what it was allowed to see and do.
15 minWalk through the four properties and the platform response to each, then Table 1.1 on what governance asks and what the platform provides.
10 minParticipants compare Nordvik Region and Hansa Mutual in pairs: legal regimes, buy or build, usage modes in use, and what each contrast means for the platform.
20 minExercise: draft an onboarding declaration, then exchange drafts and check whether the prohibited uses and the review trigger would stop a silent widening of purpose.
5 minClose with the three tensions and a preview of the usage modes as the red thread of the course.

Discussion

  1. Which of the four properties causes most difficulty in your organisation today, and which platform capability is missing for it?
  2. The book says the platform should make the approved route faster than the unofficial one. Where is the unofficial route faster in your organisation, and why?
  3. Nordvik Region steers its AI through contracts and Hansa Mutual through its own platform. Which situation is closer to yours, and what leverage does that give you?

Written exercise

Exercise · 20 minutes

Draft a platform onboarding declaration

Choose a lower-risk AI system in your own organisation, or use Nordvik Region's staff assistant as the model. Write its onboarding declaration with the fields the chapter's example uses: intended purpose, prohibited uses, usage mode, AI Act role for the compound system and for the general-purpose AI model, risk classification with a review trigger, components, data boundary with residency and key custody, security settings for egress and agent tools, and evidence with retention. Then name the two fields that would force a review if someone later widened what the system does.

Deliverable: A one-page onboarding declaration in structured form, with the two fields that guard against silent extension marked and explained.

Self-test

Choose an answer to see whether it is right, or open the answer below each question.

  1. Why does the chapter say the platform must place its controls outside the model rather than rely on a filter?

    Show the answer

    B. Because instructions and data share one channel, and no filter can list every wording that might steer the model
    An LLM receives instructions and data through the same channel, so any text it reads can act as a command. A filter cannot list every wording, so controls sit on retrieval, tools and output checks.

  2. According to the chapter, where do AI Governance and AI Platform and Security meet?

    Show the answer

    D. At the evidence the platform produces
    Governance decides what must be true of an AI system; the platform enforces those decisions and produces proof of enforcement. The two volumes meet at the evidence.

  3. In the onboarding declaration of Nordvik Region's staff assistant, what does the setting that allows no agent tools achieve?

    Show the answer

    A. A proposal to let the assistant file letters becomes a reviewed change to the declaration
    The chapter explains that the field turns any proposal to give the assistant an action, such as filing letters, into a reviewed change to the file.