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£299 programme

Mai Studies Original · Artificial Intelligence & Data

Build an Agentic AI Operations Console

Buyers are no longer asking whether to use AI agents; they are asking who the agent is, what it is allowed to touch, what it did, and what it cost. That is the product you build here, in six stages, writing code in the page with instant checks and a marked deliverable at each stage. The project output is owned by Mai Studies and may be licensed or sold; you keep the right to show your own work in your portfolio.

12 weeks 90 guided hours Advanced
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No account needed to buy. Pay with your card and we create your student account from the email you enter, with this programme ready inside it for twelve months.

Build an Agentic AI Operations Console course artwork

What you will achieve

  • Give every agent a verifiable identity and a registry record
  • Write a policy engine that decides which tools an agent may call
  • Turn a goal into an ordered, inspectable plan of steps
  • Record an audit trail an auditor can follow without reading code
  • Enforce spend, rate and behaviour limits before a call is made

Entry guidance

  • — Comfortable writing JavaScript functions
  • — Basic understanding of how an API call works
  • — Around seven hours a week for twelve weeks

Original Mai Studies learning material. This is a professional completion programme, not a regulated qualification or university accreditation.

Programme syllabus

6 applied modules

Lessons
12
Assessed tasks
6
Practice questions
72
Timed mock papers
2
01

Stage 1: Agent identity and the registry

Give every agent a record that says who it is and who owns it.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Agent identity and the registry — notes35 min study · 3 learning objectives · practical activity

    Give every agent a record that says who it is and who owns it.

  2. 2. Agent identity and the registry — build it35 min study · 3 learning objectives · practical activity

    Build the registry with validation, register two agents, and write down the fields you would refuse to make optional and why.

  • Stage 1 deliverable: Agent identity and the registry — marked out of 100, pass at 80%
02

Stage 2: Tool permissions and the policy engine

Decide, before the call, whether the agent may do this.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Tool permissions and the policy engine — notes35 min study · 3 learning objectives · practical activity

    Decide, before the call, whether the agent may do this.

  2. 2. Tool permissions and the policy engine — build it35 min study · 3 learning objectives · practical activity

    Build the policy check, then write the deny-by-default argument you would use with a manager who wants an agent given blanket access for speed.

  • Stage 2 deliverable: Tool permissions and the policy engine — marked out of 100, pass at 80%
03

Stage 3: Planning: turning a goal into inspectable steps

Make the agent show its work before it does any of it.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Planning: turning a goal into inspectable steps — notes35 min study · 3 learning objectives · practical activity

    Make the agent show its work before it does any of it.

  2. 2. Planning: turning a goal into inspectable steps — build it34 min study · 3 learning objectives · practical activity

    Build the ordering and pause logic, then write the escalation rule: which steps stop for a human, and who that human is.

  • Stage 3 deliverable: Planning: turning a goal into inspectable steps — marked out of 100, pass at 80%
04

Stage 4: The audit trail an auditor can actually read

Record what happened in a form that survives a dispute.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. The audit trail an auditor can actually read — notes36 min study · 3 learning objectives · practical activity

    Record what happened in a form that survives a dispute.

  2. 2. The audit trail an auditor can actually read — build it35 min study · 3 learning objectives · practical activity

    Build the append-only trail with chained entries, then produce a readable history of one task for a non-technical reader.

  • Stage 4 deliverable: The audit trail an auditor can actually read — marked out of 100, pass at 80%
05

Stage 5: Spend, rate and behaviour guardrails

Stop the expensive mistake before it is made.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. Spend, rate and behaviour guardrails — notes39 min study · 3 learning objectives · practical activity

    Stop the expensive mistake before it is made.

  2. 2. Spend, rate and behaviour guardrails — build it35 min study · 3 learning objectives · practical activity

    Build the budget and rate checks, then set the numbers: your defaults for a routine agent and your argument for them.

  • Stage 5 deliverable: Spend, rate and behaviour guardrails — marked out of 100, pass at 80%
06

Stage 6: The operator console and handover

Make the system usable by the person on shift at 3am.

2 lessons · 12 practice questions · 1 assessed task

  1. 1. The operator console and handover — notes37 min study · 3 learning objectives · practical activity

    Make the system usable by the person on shift at 3am.

  2. 2. The operator console and handover — build it34 min study · 3 learning objectives · practical activity

    Assemble the console summary, implement safe pause and resume, and have someone unfamiliar follow your runbook.

  • Stage 6 deliverable: The operator console and handover — marked out of 100, pass at 80%

Timed mock papers

  • Build an Agentic AI Operations Console: timed mock paper 1 — 180 minutes, 30 objective questions plus written and computational tasks
  • Build an Agentic AI Operations Console: timed mock paper 2 — 180 minutes, 30 objective questions plus written and computational tasks

Lesson pages, assessed tasks and mock papers open the moment you join this programme. Teaching material is studied online; the notes you write are yours to download.

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