AI Training Academies • AI for Engineering Leaders

Lead Responsible AI Adoption

A 5-day executive program for tech leads, architects, and engineering managers. Governance, IP and licensing, responsible AI adoption, team standards, honest productivity measurement, and a practical AI rollout strategy.

5
Training Days
1
Week
1–2
Weeks Flexible

Schedule options: Full-time (1 week, Mon–Fri) · Half-days (~2 weeks) · Custom cadence

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AI Tools Evaluated (lighter lab usage)
Claude CodeClaude Code
GitHub CopilotGitHub Copilot
IDEs & Editors
VS CodeVS Code
CursorCursor
WindsurfWindsurf
Visual StudioVisual Studio
JetBrains IDEsJetBrains
ZedZed

Make Informed AI Investment Decisions With Confidence

This is not a tool tutorial. It is an executive-level strategy and governance program designed for leaders who need to make real decisions: which tools to invest in, what policies to establish, how to measure genuine productivity gains, and how to roll out AI adoption without creating unacceptable legal or security risk.

  • Executive Audience
    Policy, strategy, and decision frameworks—not syntax
  • Deliverables Included
    Leaves with policy templates and a rollout plan
  • Lighter Labs
    Hands-on exposure to tools, not deep engineering practice
  • Flexible Scheduling
    Full days, half-days, or custom cadence
  • Online or On-Site
    Delivered wherever your leadership group works
  • Session Recordings
    Share with broader leadership (online delivery)
Days 1–2: Landscape and Governance

Tool evaluation and procurement, governance, IP, licensing, data privacy

Days 3–4: Team Standards and Measurement

CLAUDE.md and prompt libraries, eval frameworks, productivity measurement, security policy

Day 5: Rollout Strategy

Stakeholder alignment, change management, phased rollout plan, success metrics

Program Curriculum

One focused week covering AI governance, team standards, measurement, and a practical rollout plan.

Days1–2

AI Landscape, Evaluation, and Governance

2 full-days · 14 training hours

Develop a rigorous framework for evaluating and procuring AI coding tools. Understand the legal landscape for IP, data privacy, and responsible AI adoption in engineering organizations.

Topics

  • Frontier model capabilities: what they can and can't do
  • Tool evaluation frameworks: Copilot, Cursor, Claude, Windsurf
  • Procurement and vendor risk assessment
  • AI-generated code: copyright, licensing, indemnity
  • Data privacy and training data policies
  • Regulatory landscape: EU AI Act, sector-specific rules
  • Acceptable-use policy template workshop

Workshop Deliverable

Draft an acceptable-use policy and a tool evaluation scorecard tailored to the organization's risk tolerance and stack.

Days3–4

Team Standards, Evals, and Measurement

2 full-days · 14 training hours

Build the team infrastructure for sustained AI productivity: instruction files, prompt libraries, evaluation frameworks, and honest productivity measurement that distinguishes real gains from AI-generated noise.

Topics

  • CLAUDE.md and copilot-instructions authoring
  • Shared prompt library design and governance
  • Spec-driven development with GitHub Spec Kit as a team workflow standard
  • LLM evaluation frameworks: what to measure
  • Productivity measurement: baselines and anti-patterns
  • Code review policy for AI-assisted teams
  • Security controls: secret scanning, injection prevention
  • Junior engineer impact: risks and safeguards

Workshop Deliverable

Draft a team AI standards document including instruction file templates, code review gates, and a productivity measurement framework.

Day5

Rollout Strategy and Change Management

1 full-day · 7 training hours

Turn strategy into action: a phased rollout plan tailored to the organization, stakeholder communication frameworks, success metrics, and a plan for sustaining AI capability over time.

Topics

  • Stakeholder communication: exec, legal, engineering
  • Phased rollout: pilot, expand, embed
  • Change management for developer workflows
  • Success metrics and review cadences
  • Sustaining capability: training calendars, champions
  • Vendor roadmap monitoring and re-evaluation triggers

Capstone Deliverable

Complete a phased AI rollout plan for the organization, with communication templates, success metrics, and a 90-day action checklist.

Part of the Stackable Certificate Path

This program is designed to run concurrently with—or before—broader engineering-org programs:

AI for Engineering Leaders
5 days · this program
+
AI-Powered Software Engineer
15 days · broad org
+
Agentic Coding Mastery
10 days · senior champions

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