bRRAInSkills stacks · Expert
v2.0

Professional AI Software Engineer

Run a multi-team AI-assisted program where architecture, gates, team flow and memory stay consistent from kickoff to retro.

Level
Expert
Learning time
11 hours
Price
$1,999
Credential
Valid 3 years
Enroll on learn.brrain.io See the syllabus
What's new in v2.0

What changed in this edition.

  • A real integration course: six modules, five practice labs and a capstone built around one fictional program, Project Meridian. v1 had no lesson content.
  • Honest hours: duration and CPE now count only this course's own content; the four component courses are prerequisites counted separately.
  • The Consolidator is taught as the product component that merges workspace changes into the Vault, consistent with AI Coding with bRRAIn; human judgment enters through decisions and supersession.
  • MCP-first session method throughout (start_brain_session, record_decision, record_learning), with Nexus Plan and Memory as the shared view and the git variant as the alternative.
  • Current platform practice: per-project permissions, custom roles, governed agent access, the LLM Registry and Handler default, brrain upgrade and in-place pod upgrades.
  • A fresh integration-level exam bank with AI-conducted performance items, and a capstone rubric with four anchor exemplars.
  • Delivery claims now match the platform: online timed exam assembled per candidate, AI role-play labs, AI-scored capstone with human re-review on request.
Outcomes

What you will be able to do.

  • You will be able to set up governed program memory, access and a shared session method for a multi-team AI-assisted program before design starts.
  • You will be able to assign decision ownership between assistants and people consistently across code, team, release and architecture decisions.
  • You will be able to write architecture decisions whose invariants become release-train gates, seam ownership and rules assistants can check against.
  • You will be able to plan and run cross-team flags, migrations, rollback and evidence-based go/no-go decisions, including the brain pod as a dependency.
  • You will be able to apply zero-trust and data-handling controls to assistants and automation and assemble audit evidence a reviewer can verify.
  • You will be able to lead a cross-discipline blameless retro and promote recurring learnings into organizational standards.

Who it's for

  • Senior and staff engineers who hold the four component credentials and lead multi-team work
  • Tech leads responsible for how assistants, people and automation work together on a program
  • Engineering managers and architects who set AI-engineering practice across teams
  • Partner-firm engineers delivering AI-assisted engineering programs for clients

Not covered here

  • Re-teaching the four component disciplines (take the component courses)
  • Platform SDK and extension development (see SDK Developer)
  • Operating and administering a brain pod (see the bRRAInOps and bRRAInCare courses)
  • Model training or fine-tuning
Syllabus

6 modules, 41 lessons.

About 11 hours of learning. Open a module to see every lesson.

  1. Orientation and program memory 7 lessons · 1 h 40 min

    What the stacked credential certifies, the Project Meridian integration brief, and how to set up one governed home — console Project, per-project permissions, custom roles, POPE tags, NFR register and session method — before design starts. Maps the four disciplines onto the 9-stage Build Methodology.

    1. Module 1 pretest (diagnostic) Diagnostic pretest · 5 min
    2. What the stacked credential certifies Reading · 12 min
    3. The integration brief: Project Meridian Scenario · 15 min
    4. Setting up program memory: a worked example Worked example · 15 min
    5. The 9-stage Build Methodology across four disciplines Reading · 13 min
    6. Lab 1: Program kickoff with the sponsor AI role-play lab · 30 min
    7. Retrieval: 7 questions across the module Retrieval check · 10 min
  2. One loop, many contributors 7 lessons · 1 h 48 min

    The personal and team loops at program scale: the MCP-first session method with many writers and readers, AI-versus-human triage applied consistently across disciplines, what the Consolidator and Conflict Zone do and what only people catch, and cross-team hand-offs that transfer intent.

    1. Module 2 pretest (diagnostic) Diagnostic pretest · 5 min
    2. The session method at program scale Reading · 13 min
    3. AI-versus-human triage across disciplines Reading · 12 min
    4. Consolidation, conflicts and human judgment Reading · 14 min
    5. A cross-team hand-off chain: worked example Worked example · 14 min
    6. Lab 2: Two sessions, two answers AI role-play lab · 40 min
    7. Retrieval: 7 questions across the module Retrieval check · 10 min
  3. Architecture as the shared contract 7 lessons · 1 h 54 min

    ADRs written for four readers — architects, the release train, the teams and every assistant: invariants with gates and owners, implications for implementers, seam ownership made enforceable, drift that surfaces in other disciplines, and a full ADR taken from an AI draft to acceptance.

    1. Module 3 pretest (diagnostic) Diagnostic pretest · 5 min
    2. ADRs that drive gates Reading · 13 min
    3. Seams, ownership and access Reading · 13 min
    4. Scenario: drift that surfaces in another discipline Scenario · 14 min
    5. Worked example: one ADR, four disciplines Worked example · 14 min
    6. Lab 3: Shadow-mode design review AI role-play lab · 45 min
    7. Retrieval: 7 questions across the module Retrieval check · 10 min
  4. The release train that carries it all 7 lessons · 1 h 48 min

    Gates derived from decisions and traced both ways, flags and expand–migrate–contract changes across three teams, rollback that covers data and caches, the brain pod as a dependency with brrain upgrade and in-place upgrades, and an evidence-based cutover go/no-go.

    1. Module 4 pretest (diagnostic) Diagnostic pretest · 5 min
    2. Gates derived from decisions Reading · 13 min
    3. Flags and migrations across teams Reading · 13 min
    4. Rollback, and the platform as a dependency Reading · 13 min
    5. Scenario: the stage-3 go/no-go Scenario · 14 min
    6. Lab 4: Stage-4 go/no-go AI role-play lab · 40 min
    7. Retrieval: 7 questions across the module Retrieval check · 10 min
  5. Governance, security and the agent surface 6 lessons · 1 h 29 min

    Zero-trust for people, assistants and automation: roles, scopes, SSO mapping, tokens and governed paths; model, tool and data governance with the LLM Registry, the Handler, Tool Registry, Exchange MCP and Data Pipe; and the audit evidence chain a program leaves behind.

    1. Module 5 pretest (diagnostic) Diagnostic pretest · 5 min
    2. Zero-trust for AI-assisted engineering Reading · 12 min
    3. Governing models, tools and data on a program Reading · 13 min
    4. Audit evidence a program leaves behind: worked example Worked example · 14 min
    5. Lab 5: Agent access review with the security controller AI role-play lab · 35 min
    6. Retrieval: 7 questions across the module Retrieval check · 10 min
  6. Failure analysis, compounding and the capstone 7 lessons · 2 h 21 min

    Cross-discipline blameless retros that treat assistants as honest actors and fix controls on the seams, the promotion of recurring learnings into standards by recorded decision, capstone orientation, and the four-phase capstone.

    1. Module 6 pretest (diagnostic) Diagnostic pretest · 5 min
    2. The cross-discipline blameless retro Reading · 14 min
    3. Compounding: from program learnings to standards Reading · 13 min
    4. Capstone orientation: what is scored and how Reading · 14 min
    5. Lab 6: Facilitating the cross-discipline retro AI role-play lab · 40 min
    6. Retrieval: 7 questions across the module Retrieval check · 10 min
    7. Capstone: Project Meridian, dimensional-weight pricing 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 · Orientation and program memory

    AI role-play: program kickoff with the sponsor of Project Meridian (fictional); the learner gets a program memory and working plan approved

  • Lab 2 · One loop, many contributors

    AI role-play: a tech lead resolving two contradictory recorded decisions built on by two engineers' assistants

  • Lab 3 · Architecture as the shared contract

    AI role-play: design review of the shadow-mode ADR with the principal architect and the release manager

  • Lab 4 · The release train that carries it all

    AI role-play: stage-4 cutover go/no-go with the sponsor and the customer operations lead

  • Lab 5 · Governance, security and the agent surface

    AI role-play: security controller review of an access plan for two automated agents

  • Lab 6 · Failure analysis, compounding and the capstone

    AI role-play: facilitating a blameless cross-discipline retro with three leads who each blame a single actor

  • Lab 7 · Failure analysis, compounding and the capstone

    AI role-play across four phases of Project Meridian (architecture, agents and data, go/no-go, incident and retro) with the examiner playing five stakeholders; Capstone Integration Pack submitted in the lab

Capstone

Project Meridian: dimensional-weight pricing across four phases

AI role-play scored against the published rubric

Pass mark: 75%

Scored on

  • Program memory and session discipline15%
  • Architecture contract20%
  • Release-train integration20%
  • Team flow and AI–human ownership15%
  • Governance and data handling10%
  • Cross-discipline consistency10%
  • Retro and compounding10%
Exam and credential

One exam. A credential anyone can verify.

The exam

Items per form
66
Time allowed
180 min
Pass mark
75%
Performance tasks
6
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 the four component credentials current and the quarterly CE modules completed
Before and after

Where this course sits.

Prerequisites

  • AI Coding with bRRAIn (ai-coding-with-brrain) — current credential
  • AI Team Development (ai-team-development) — current credential
  • AI SDLC & Release Train (ai-sdlc-release-train) — current credential
  • AI Augmented Systems Architect (ai-augmented-systems-architect) — current credential
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: 66 items in 180 minutes, on a form assembled for you from the course's item bank. 6 of the items are performance tasks conducted by an AI examiner: you do the work rather than pick an answer. The pass mark is 75%.

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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Professional AI Software Engineer

Run a multi-team AI-assisted program where architecture, gates, team flow and memory stay consistent from kickoff to retro.

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