🆕 Executive & Manager Guide  ·  No Code Required

AI-SDLC:
The Executive Playbook

Everything technology leaders need to know — business case, ROI models, MCP servers, governance frameworks, and a 90-day adoption roadmap. No engineering background required.

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11
Strategic Modules
8–30%
Full-Cycle Productivity Gain
3-Year
ROI Models Included
90-Day
Adoption Roadmap
90%
of enterprise engineers will use AI coding assistants by 2028 (Gartner)
55%*
faster on AI-suitable tasks: code, tests, docs (GitHub Octoverse)
3×
ROI in year one for well-governed AI-SDLC programs (illustrative model)
ISO
42001:2023 — the international AI governance standard your org needs to know
Course Modules

What You'll Learn

Each module covers a strategic topic with real frameworks, business scenarios, and actionable decisions. Click any card to open the full module.

🚀
MODULE 00
The AI-SDLC Revolution
Why Software Development Will Never Be the Same
The strategic case for AI-SDLC — why teams that adopt it outperform those that don't, and what executives need to understand to lead the transition. Covers the productivity inflection point, the three pillars, and the cost of non-adoption.
6 sections  ·  No code required→
🤖
MODULE 01
AI Coding Agents
Your Developers' AI Pair Programmers
What AI coding agents are, how they work, and why they are the most significant productivity innovation in software development since version control. Includes what agents can and cannot do, plus a day-in-the-life scenario.
5 sections  ·  Business-level overview→
🔌
MODULE 02
MCP Servers
Why Developers Need AI with Business Context
Model Context Protocol — the open standard that gives AI coding agents secure, governed access to your enterprise tools: Jira, GitHub, databases, Slack, and cloud consoles. Covers security architecture, ROI, and which MCP servers to deploy first.
7 sections  ·  Includes security model→
📋
MODULE 03
OpenSpec & Spec-Driven Development
Governance for AI-Generated Code
OpenSpec is the governance layer that prevents AI coding agents from generating inconsistent, spec-divergent code. It enforces a Propose → Review → Apply → Verify workflow that gives executives visibility and control over what AI builds.
7 sections  ·  Governance focus→
💰
MODULE 04
ROI & Business Case
Quantifying the Value of AI-SDLC
The financial case for AI-SDLC investment — three-year TCO model for a 50-developer team, metrics to track post-adoption, and how to build and present the internal business case including a CFO conversation scenario.
5 sections  ·  TCO model included→
📊
MODULE 4B
Measuring AI Adoption
Beyond Lines of Code — What Actually Matters
Lines of code accepted is a vanity metric. This module covers the adoption measurement framework that actually predicts whether AI-SDLC is delivering — and why your data engineering and DevOps teams may show low code volume while being your highest-value adopters.
7 sections  ·  Includes benchmark table→
🛡️
MODULE 05
Governance & Risk
AI Compliance — ISO 42001, NIST AI RMF
The governance framework for responsible AI-assisted development — ISO/IEC 42001:2023, NIST AI Risk Management Framework, MCP security architecture for CISOs, and the human-in-the-loop principle that every AI policy needs.
6 sections  ·  CISO-ready content→
👥
MODULE 06
Managing AI-Enabled Teams
Leadership in the Age of AI-Assisted Development
How the manager's role changes in AI-SDLC organizations, which skills become more valuable (not less), how to avoid the "vibe coding" trap, and how to run the change management process that makes AI-SDLC succeed at scale.
7 sections  ·  Change management guide→
🗺️
MODULE 07
The AI Tool Landscape
Choosing the Right Tools for Your Team
The four categories of AI-SDLC tooling, how to choose between Claude Code and Gemini Code Assist, a procurement checklist for legal and security, and the build-vs-buy framework for custom AI tooling decisions.
5 sections  ·  Procurement checklist→
📅
MODULE 08
90-Day Roadmap
How to Get Started — Week by Week
The proven 90-day adoption plan for AI-SDLC — from executive alignment and pilot team selection through org-wide rollout and governance committee formation. Includes an AI-SDLC Readiness Self-Assessment and common pitfalls to avoid.
7 sections  ·  Week-by-week plan→
📚
REFERENCE
Sources & Glossary
Research References and Key Term Definitions
Research sources cited throughout this course with accuracy notes on key statistics, and a 14-term AI-SDLC glossary covering AI Coding Agent, MCP, OpenSpec, Spec Drift, Vibe Coding, DORA Metrics, SPACE Framework, and more.
2 sections  ·  14-term glossary→
Why This Matters

Four Decisions Every Leader Must Make

AI-SDLC is not a tool purchase — it is a transformation programme. These are the decisions that determine whether it succeeds.

⚡
Adopt or Fall Behind
Gartner projects 90% of enterprise engineers will use AI assistants by 2028. Competitors are already deploying. The question is no longer whether — it's how fast and how well-governed.
🔐
Context Without Compromise
AI agents are only as useful as the context they can access. MCP Servers give agents secure, audited access to your tools — without exposing credentials or bypassing your security policies.
📐
Governance from Day One
AI-generated code without governance leads to spec drift, inconsistency, and technical debt that compounds faster than any human team produced. OpenSpec and ISO 42001 frameworks prevent this from the start.
📏
Measure What Actually Matters
Lines of code accepted is the wrong metric for most teams. Data engineers, DevOps engineers, and security teams have low code volumes but high AI value. The right framework measures quality, speed, and outcome — not volume.
Getting Started

The 90-Day Adoption Plan

Three months from executive alignment to org-wide rollout.

📌
Month 1
Foundation
Executive alignment, tool selection, pilot team identified, governance policy drafted, first MCP servers deployed
🚀
Month 2
Pilot
Pilot team running full AI-SDLC cycle, metrics baseline established, OpenSpec spec.md authored, first wins documented
🌐
Month 3
Scale
Rollout to all teams, AI Governance Committee formed, adoption dashboard live, 90-day retrospective held
View Full Week-by-Week Plan →

Ready to Lead the Transition?

The full course includes business scenarios, CFO conversation scripts, a procurement checklist, readiness self-assessment, and all the frameworks you need to brief your board and ship your AI-SDLC programme.

Open Full Course → Jump to ROI Model →