W4: Enterprise AI Architecture
Most enterprises are accumulating AI point solutions — a Copilot here, a RAG chatbot there, an agent experiment in someone's notebook — without any coherent architecture connecting them. The result is shadow AI, duplicated spend, ungoverned data flows, and a portfolio of pilots that never scale.
This two-day workshop is for the people responsible for making AI investments compound rather than fragment. It answers the question every senior technical leader is asking: how do we turn what we're already doing into a coherent system that scales, governs itself, and delivers measurable business value?
What we'll cover across two days:
Day 1 — The Architecture
→ The six-layer enterprise AI stack: what belongs where and what happens when a layer is missing
→ The AI Gateway: your most important infrastructure decision — routing, semantic caching, cost governance, PII redaction, observability
→ Gateway options: Kong, Bifrost, LiteLLM, Cloudflare — decision framework for each
→ MCP: the integration standard that replaces N×M custom connectors → The seven enterprise MCP server patterns
→ Multi-agent orchestration: supervisor, mesh, and hierarchical patterns — when to use each
→ The A2A protocol and why it matters for multi-agent systems
Day 2 — Governance, the Skill Factory, and Business Value
→ Governance as an architecture layer, not a policy document
→ Risk tiering: Tier 1 (productivity tools) through Tier 4 (autonomous high-stakes decisions)
→ Regulatory landscape: EU AI Act, ISO/IEC 42001, NIST AI RMF, Australian context
→ The AI Skill Factory operating model — what separates organisations that scale AI from those that don't
→ Connecting every architectural decision to Revenue, Cost, or Risk
→ The 95% pilot failure pattern — five architectural reasons and how to fix each
→ The 90-day architectural sprint: what to do first, what to defer, what to avoid
You'll leave with eight working documents — not slides:
→ Six-layer architecture mapped to your organisation
→ Gateway design (what to route, cache, and govern)
→ MCP server catalogue draft
→ Multi-agent topology with protocol labels
→ AI portfolio risk-tier matrix
→ AI Skill Factory operating model canvas
→ One-page value architecture (Revenue Cost Risk)
→ 90-day roadmap
Who this is for:
CTOs, Heads of Engineering, Solutions Architects, AI and Data Platform Leads, Technical PMs. This is not a developer workshop — it's an architecture and leadership workshop. Familiarity with AI concepts assumed; deep technical Python knowledge not required.
📅 Thursday 25 – Friday 26 June 2026
🕘 9:00am – 5:30pm both days
📍 Stone & Chalk, Tech Central, Haymarket
Maximum 15 participants — kept deliberately small so every exercise is specific to your organisation, not a generic template.
🎟 Early bird pricing closes 3 June — price increases after. 💬 DataEngBytes member? Use code DEB10 at checkout for 10% off.
Lunch and all workshop materials included both days.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🗓 PART OF AI MASTERY WEEK — 22–26 JUNE
Mon 22 → W1: Prompt Engineering Mastery
Tue 23 → W2: Mastering AI/LLM Evaluations
Wed 24 → W3: Building Practical AI Agents
Thu–Fri → W4: Enterprise AI Architecture ← you're here
🎁 Book all four and save 15%:
Most valuable combination for a leadership team: send your engineers to W1–W3, attend W4 yourself. The full picture, five days.
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Hosted by Peter Hanssens, founder of Cloud Shuttle and DataEngBytes — ANZ's largest data engineering community conference.