bRRAInSkills stacks · Practitioner
v2.0

AI SDLC & Release Train — Physical Delivery

Run construction, mining, manufacturing and civil projects as gated trains where AI prepares and named people commit.

Level
Practitioner
Learning time
18 hours
Price
$499
Credential
Valid 3 years
Enroll on learn.brrain.io See the syllabus
What's new in v2.0

What changed in this edition.

  • The train now lives in Nexus Plan: stage epics, gate milestones with named owners, finish-to-start dependencies, critical path and Auto-schedule.
  • New lessons on getting FAT reports, schedule exports and submittals into the vault with Mega-parser, and on accepting a parse before gating on it.
  • New lessons on sign-off authority (custom roles, per-project permissions, two-person approvals) and on the audit evidence chain with Robo Compliance sealed sessions.
  • Self-diagnosis now connects operational data through Data Pipe instead of copying it, with detectors tested for hits, misses and false alarms.
  • Decisions are recorded as they happen with the MCP session tools; the outdated memory-file workflow, model names and proctoring references were removed.
  • Labs are AI role-plays with demanding stakeholders, and the exam is a 120-minute LOFT form with 55 items and 4 AI-examined performance tasks.
Outcomes

What you will be able to do.

  • You will be able to lay out a physical project as a six-stage train in Nexus Plan with every gate owned by AI, a named human, or both.
  • You will be able to specify deterministic gates on verified, parsed inputs with testable rules and numeric pass conditions.
  • You will be able to design permit, release and commissioning sign-offs that a regulator, owner or court can rely on.
  • You will be able to write cutover runbooks in which every irreversible step has a resourced decommission path.
  • You will be able to plan phased rollouts whose halt criteria are measurable and cannot be waved away.
  • You will be able to connect operational data for AI self-diagnosis without giving AI authority over live equipment, and prove decisions with a verifiable evidence chain.

Who it's for

  • Project engineers and delivery managers responsible for physical-project cadence
  • Construction superintendents and commissioning engineers
  • Manufacturing process engineers running line ramps and equipment changes
  • Civil and mining project leads responsible for permit-to-commission flow
  • AI engineers embedded in physical-delivery teams

Not covered here

  • Software release trains (see AI SDLC & Release Train)
  • The personal AI coding loop (see AI Coding with bRRAIn — Industry)
  • Multi-discipline team flow (see AI Team Development — Field & Office)
  • Industry systems architecture (see AI Augmented Systems Architect — Industry)
Syllabus

8 modules, 66 lessons.

About 18 hours of learning. Open a module to see every lesson.

  1. Train Design for Physical Work 9 lessons · 2 h 30 min

    Why physical trains differ from software trains, the six-stage anatomy, the four gate-ownership axes, discipline overlays, the Build Methodology and session-method memory, and the train in Nexus Plan. Lab 1 designs and defends a six-stage train.

    1. Pretest: train design for physical work Diagnostic pretest · 5 min
    2. Why physical-delivery trains differ structurally from software Reading · 15 min
    3. The six-stage anatomy: intake, permit, procure, fab, install, commission Reading · 15 min
    4. The four AI-versus-human gate axes for physical work Reading · 15 min
    5. How the four disciplines overlay the same six stages Reading · 15 min
    6. The build methodology and the train's memory Reading · 15 min
    7. Nexus Plan as the train tracker Worked example · 15 min
    8. Lab 1: Design a six-stage train and defend its gate ownership AI role-play lab · 45 min
    9. Retrieval: 7 questions across the module Retrieval check · 10 min
  2. Deterministic AI Gates (Physical) 9 lessons · 2 h 30 min

    DRC and drawing-set checks, FAT data parsing, schedule validation, document completeness, and getting FAT reports, schedule exports and submittals into the vault with Mega-parser. Lab 2 specifies four gates from real-shaped inputs.

    1. Pretest: deterministic AI gates Diagnostic pretest · 5 min
    2. DRC and drawing-set checks: what AI catches and what it cannot Reading · 15 min
    3. FAT data parsing: tolerance bands, structured ingest, auto-pass criteria Reading · 15 min
    4. Schedule validation: work-package dependencies and long-lead detection Reading · 15 min
    5. Document completeness: required-doc lists, signature checks, version pinning Reading · 15 min
    6. Getting FAT reports, schedule exports and submittals into the vault Reading · 15 min
    7. Worked example: four deterministic gates on one civil package Worked example · 15 min
    8. Lab 2: Specify four deterministic gates from real-shaped inputs AI role-play lab · 45 min
    9. Retrieval: 7 questions across the module Retrieval check · 10 min
  3. Human-Owned Gates (Physical) 9 lessons · 2 h 30 min

    The three irreversibility classes, permit submission, IFC release, commissioning go/no-go, authority and two-person sign-off, and the sign-off record. Lab 3 designs a commissioning sign-off and its record.

    1. Pretest: human-owned gates Diagnostic pretest · 5 min
    2. Which gates must stay human: three irreversibility classes Reading · 15 min
    3. Permit-submission anatomy across disciplines Reading · 15 min
    4. Issued-For-Construction handoff and design-for-construction sign-off Reading · 15 min
    5. Commissioning go/no-go and the AI-prepared review package Reading · 15 min
    6. Recording the human sign-off: authority, two-person rules and evidence Reading · 15 min
    7. Scenario: the permit package that was complete and clean Scenario · 15 min
    8. Lab 3: Design the commissioning sign-off and its record AI role-play lab · 45 min
    9. Retrieval: 7 questions across the module Retrieval check · 10 min
  4. Deploy Choreography and Rollback 9 lessons · 2 h 30 min

    Staged install with explicit go/no-go, cutover patterns, decommission as physical rollback, attribution at every stage, a worked cutover runbook, and coordinating parallel packages. Lab 4 writes an equipment cutover with a real decommission path.

    1. Pretest: deploy choreography and rollback Diagnostic pretest · 5 min
    2. Staged install: explicit go/no-go between stages Reading · 15 min
    3. Cutover patterns: parallel-run, big-bang with fallback, phased, pilot-then-expand Reading · 15 min
    4. Decommission as physical rollback: design it from day one Reading · 15 min
    5. Attribution at every stage: who changed what, when and why Reading · 15 min
    6. Worked example: a cutover runbook with its decommission path Worked example · 15 min
    7. Coordinating parallel work packages with shared dependencies Reading · 15 min
    8. Lab 4: Equipment cutover with a real decommission path AI role-play lab · 45 min
    9. Retrieval: 7 questions across the module Retrieval check · 10 min
  5. Phased Rollout and Migrations 8 lessons · 2 h 15 min

    Pilot and first-of-a-kind phases, geographic phasing, equipment-swap patterns, halt criteria that are AI-checkable and human-irrevocable, and a worked three-phase rollout. Lab 5 plans a rollout whose halts hold under sponsor pressure.

    1. Pretest: phased rollout and migrations Diagnostic pretest · 5 min
    2. Pilot line and first-of-a-kind: what to learn, what to commit Reading · 15 min
    3. Geographic phasing: weather, labor and regulatory variance Reading · 15 min
    4. Equipment-swap migration patterns across disciplines Reading · 15 min
    5. Halt criteria: AI-checkable, human-irrevocable Reading · 15 min
    6. Worked example: a three-phase rollout with advance and halt criteria Worked example · 15 min
    7. Lab 5: Plan a three-phase rollout with halt criteria that hold AI role-play lab · 45 min
    8. Retrieval: 7 questions across the module Retrieval check · 10 min
  6. Observability, Zero-Trust and the Evidence Chain 9 lessons · 2 h 30 min

    Sensor telemetry and work-package status as observability, post-install regression detection, zero-trust boundaries for AI on physical paths, Data Pipe connections, and the audit evidence chain with Robo Compliance sealed sessions. Lab 6 designs self-diagnosis and evidence for a commissioned asset.

    1. Pretest: observability, zero-trust and evidence Diagnostic pretest · 5 min
    2. Sensor telemetry as observability: what AI can read and what it cannot Reading · 15 min
    3. Work-package status tracking: the granularity AI needs Reading · 15 min
    4. Post-install regression detection: vibration, alignment, throughput Reading · 15 min
    5. Zero-trust on physical-delivery paths: AI never commands live equipment Reading · 15 min
    6. The audit evidence chain: from gate record to sealed evidence Reading · 15 min
    7. Worked example: wiring self-diagnosis for a commissioned system Worked example · 15 min
    8. Lab 6: Self-diagnosis and the evidence chain for a commissioned asset AI role-play lab · 45 min
    9. Retrieval: 7 questions across the module Retrieval check · 10 min
  7. Retro, Close-Out and Capstone Preparation 7 lessons · 1 h 30 min

    The capstone brief and package, pacing and honest AI assistance, blameless retros with cause classes, close-out that compounds, and the four anchor exemplars.

    1. Pretest: retro, close-out and capstone preparation Diagnostic pretest · 5 min
    2. The capstone brief: what you are given and what you deliver Reading · 15 min
    3. Working the capstone: pacing, checkpoints and honest AI assistance Reading · 15 min
    4. Retro format: AI, human, environmental and mixed causes Reading · 15 min
    5. Closing out the train so the next project inherits it Reading · 15 min
    6. Anchor exemplars: what 92, 78, 71 and 54 look like Worked example · 15 min
    7. Retrieval: 7 questions across the module Retrieval check · 10 min
  8. Exam Readiness and Capstone 6 lessons · 1 h 45 min

    How the exam works, timing strategy, recurring traps, a final retrieval check, and the capstone lab.

    1. Pretest: exam readiness Diagnostic pretest · 5 min
    2. How the certification exam works Reading · 15 min
    3. Timing strategy: when to flag, when to commit Reading · 15 min
    4. Recurring traps in physical-delivery items Reading · 15 min
    5. Retrieval: 6 questions across the module Retrieval check · 10 min
    6. Capstone: a complete physical-delivery train for your discipline AI role-play lab · 45 min
Labs and capstone

Practice against someone who pushes back.

Labs run in your browser as AI role-plays. An AI plays the person on the other side of the scenario — with their own goals and objections — and your work is scored against the published rubric. There is nothing to install.

  • Lab 1 · Train Design for Physical Work

    Six-stage train design with gate ownership defended against a project director

  • Lab 2 · Deterministic AI Gates (Physical)

    Four deterministic gate specifications from real-shaped inputs, including a narrative acceptance criterion

  • Lab 3 · Human-Owned Gates (Physical)

    Commissioning sign-off design and decision record with a commissioning engineer

  • Lab 4 · Deploy Choreography and Rollback

    Equipment cutover runbook with paired decommission defended against an operations manager

  • Lab 5 · Phased Rollout and Migrations

    Three-phase rollout plan defended against a program sponsor

  • Lab 6 · Observability, Zero-Trust and the Evidence Chain

    Self-diagnosis and evidence-chain design for a commissioned asset, with five events to classify

  • Lab 7 · Exam Readiness and Capstone

    Complete physical-delivery train package for a discipline brief

Capstone

Capstone: a complete physical-delivery train for your discipline

Artefact submitted in the capstone lab, AI-scored against the published rubric

Pass mark: 72%

Scored on

  • Train design and gate ownership20%
  • Deterministic gate specifications15%
  • Human-owned gates and sign-off records15%
  • Deploy, cutover and decommission15%
  • Phased rollout or staged commissioning and halt criteria15%
  • Observability, zero-trust and evidence chain10%
  • Delivery memory and retro10%
Exam and credential

One exam. A credential anyone can verify.

The exam

Items per form
59
Time allowed
120 min
Pass mark
72%
Performance tasks
4
Attempts included
2
Wait between attempts
7 days
  • Online and timed, taken on learn.brrain.io.
  • Your form is assembled for you from the course's item bank, so no two candidates sit the same paper.
  • Performance tasks are conducted by an AI examiner: you work through a realistic scenario and are scored against a published rubric.

The credential

  • A verifiable digital badge in your name.
  • A public verification page at learn.brrain.io/verify, so an employer or client can confirm it.
  • Valid for 3 years.
  • Renewal: At 3 years, by passing the then-current exam with CE modules completed
Before and after

Where this course sits.

Stacks well with

Questions

Frequently asked.

Do I need to install anything for the labs?

No. Labs and the capstone run in your browser on learn.brrain.io as AI role-plays: an AI plays the person on the other side of the scenario, and your work is scored against the rubric published with the course.

How is the exam delivered?

Online and timed: 59 items in 120 minutes, on a form assembled for you from the course's item bank. 4 of the items are performance tasks conducted by an AI examiner: you do the work rather than pick an answer. The pass mark is 72%.

What if I don't pass first time?

You have 2 attempts, with a 7-day wait after an unsuccessful attempt. Further exam attempts can be bought for $299 each.

How long is the credential valid?

3 years. You receive a verifiable digital badge with a public verification page at learn.brrain.io/verify, so anyone can confirm it is genuine.

I hold the v1 credential. Is it still valid?

Yes. Credentials earned on v1 remain valid and verifiable at learn.brrain.io/verify. When you renew, you sit the then-current version of the exam.

Can my company enroll a team?

Yes. Firms can buy a certification bundle for $2,999 per firm per year — see the pricing page — or contact us to arrange enrollment for a larger group.

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AI SDLC & Release Train — Physical Delivery

Run construction, mining, manufacturing and civil projects as gated trains where AI prepares and named people commit.

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