Workshop Syllabus
Six modules take your team from AI-Naive foundations all the way to multi-agent orchestration. Every engagement is private and assembled from this curriculum in real time — we pick the modules, labs, and discussions that matter most to your team. Below is the full module-by-module breakdown.
The Zenable AI Coding Maturity Model
Context Engineering
Set expectations through context files. Low barrier to entry, version controlled, reduces variability across developers and agents.
Skills, MCP & Spec-Driven Development
Multi-perspective automated review with specialized agents for security, QA, and best practices catching issues in parallel.
Hooks, Guardrails & Policy Enforcement
Deterministic guardrails that enforce policy in milliseconds: no hallucinations, fully reproducible, audit-ready evidence.
Observability & Measurement
You can’t improve what you can’t measure. Telemetry, dashboards, and data-driven guardrail effectiveness tracking.
Agents, Teams & Continuous Improvement
A feedback loop where each level informs the others. Incidents, audits, and policy changes drive guardrail evolution. Coverage grows from real risk.
Multi-Agent at Scale
You architect, agents execute. Hierarchical delegation with specialized agent teams coordinated toward shared goals.
Module 1: Foundations & Context Engineering
Start from zero and build a solid AI development foundation: maturity models, context engineering, safe IDE configuration, governance, and your first MCP connection.
- LectureThe AI Maturity Journey30m
- LectureContext Engineering: CLAUDE.md & Beyond30m
- BreakMorning Break15m
- DiscussionContext Window Management15m
- LecturePrompting Fundamentals20m
- LectureEnvironment Setup: settings.json & Permissions30m
- LectureRepository & CI/CD Governance25m
- LectureIDE Landscape & MCP Basics30m
- Hands-onHands-on: Configure Your Environment & Install Zenable MCP45m
- DiscussionQ&A: Foundations15m
Module 2: Skills, MCP & Spec-Driven Development
Level up from basic AI usage to structured workflows: reusable Skills, deeper MCP integration, and specification formats (Gherkin, EARS) that AI can execute precisely.
- LectureAI-Assisted: Doing Existing Jobs Faster30m
- BreakAfternoon Break15m
- Hands-onHands-on: Build a Custom Skill + Connect MCP30m
- LectureAI Problem-Solving Lifecycle30m
- LectureSpec-Driven Development30m
- Hands-onHands-on: Build a PRD and Execute30m
- DiscussionWrap-up: AI-Assisted15m
Module 3: Hooks, Guardrails & Policy Enforcement
Redesign workflows around AI with deterministic enforcement: hooks that intercept actions, policy-as-code that validates output, and parallel development with worktrees.
- LectureAI-Augmented: Workflows Redesigned Around AI30m
- BreakMorning Break15m
- Hands-onHands-on: Write Hooks That Enforce Guardrails30m
- LecturePolicy as Code30m
- LectureImplementation Guardrails30m
- LectureParallelism in AI Development30m
- Hands-onHands-on: Parallel Development with Policy Enforcement30m
- DiscussionQ&A: AI-Augmented Workflows15m
Module 4: Observability & Measurement
Add measurement to the loop: enable Claude Code telemetry, build dashboards, instrument guardrails, and learn which metrics actually matter (and which to never target).
- LectureData Driven AI: Measurement Closes the Loop30m
- LectureClaude Code Native Telemetry30m
- LabHands-on: Enable Telemetry & Build a Dashboard30m
- LectureMeasuring Guardrail Effectiveness30m
- LabHands-on: Instrument Your Hooks & Analyze Effectiveness30m
- LectureThe Metrics That Matter (and the Ones That Don't)25m
- DiscussionWrap-up: Data Driven AI15m
Module 5: Agents, Teams & Continuous Improvement
Architect your org with AI as a core participant: custom agents, agent teams, the continuous-improvement flywheel, and multi-perspective automated reviews.
- LectureAI-Native: AI as a Core Participant30m
- BreakAfternoon Break15m
- LectureAgent Teams30m
- Hands-onHands-on: Build a Multi-Agent Feature30m
- LectureThe Continuous Improvement Flywheel30m
- LectureAutomated Reviews & AI-Driven PR Review30m
- Hands-onHands-on: AI-Driven PR Review30m
- DiscussionWrap-up: AI-Native15m
Module 6: Orchestrated Agents at Scale
Go beyond agent teams to full orchestration: orchestrator architecture, the Mayor/Convoy hierarchy, the Loop House rhythms, and governing dozens of agents at once.
- LectureFrom Agents to Orchestrators30m
- LectureGastown Architecture30m
- BreakMorning Break15m
- LectureThe Loop House: Three Rhythms of Work30m
- DemoGastown CLI Demo30m
- LectureOrchestrator Landscape30m
- Hands-onHands-on: Orchestrator Session30m
- DiscussionFinal Q&A and Workshop Wrap-up15m
Ready to bring this to your team?
Every workshop is private, hands-on, and tailored. We'll help you pick the right modules and format.
Book a free consultation