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AI Engineering

Designed for practitioners building AI systems and applications in production this track explores novel architectures and system designs, from innovative approaches to RAG and agent pipelines to real-world case studies backed by production metrics.

AI Engineering (Day 1 Midday)

Wednesday 3rd June 2026

  1. Evaluation Precedes Evolution: Rubrics as the Load-Bearing Infrastructure of Self-Improving Agents Tanya Dixit Forward Deployed Engineer Google
  2. Beyond Forgetful Bots: Architectural Patterns for Persistent, Proactive Claw-Style AI Agents Navan Tirupathi CTO , Architecture and AI Expert Arivminds
  3. Shipping Sandboxed Workers for Notion Agents Adam Hudson Software Engineer Notion
  4. Close your agentic loop Moss Ebeling Head of AI Engineering Optiver Asia Pacific
  5. How Many Agents Are Too Many? The Hidden Cost of Multi-Agent Systems Anannya Roy Chowdhury GenAI Developer Advocate AWS
  6. Kill the God Agent Adesh Gairola Co-founder & CTO raxIT Labs
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AI Engineering (Day 1 Afternoon)

Wednesday 3rd June 2026

  1. Agent Observability: Monitoring and Understanding Agents at Internet Scale Daniel Nadasi Principal Engineer Google
  2. Our AI Hallucinated in Production: How We Fixed It With Evals Yicheng Guo Senior Machine Learning Engineer REA Group
  3. The Application Layer Is the New Research Lab Abdul Karim Applied AI Scientist
  4. Orbital Lasers vs For Loops: Economically Matching Models to Tasks Stephen Sennett AWS Community Hero & Lead Consultant at V2 AI V2 AI
  5. Your AI Can’t Engineer (Yet) Theodoros Galanos Generative AI Leader Aurecon
  6. Flue: The Agent Harness Framework Michael Hart Senior Principal Engineer Cloudflare
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AI Engineering (Day 2 Midday)

Thursday 4th June 2026

  1. Deploying AI at the Edge: Model Compression and Hardware-Aware Optimization Shivay Lamba Senior AI/ML Engineer Qualcomm
  2. When a Small Language Model Beat Our LLM in Production Avni Bhatt Sr Enterprise Architect
  3. Multi-Model Collaboration with Claude Code: How to Measure What Actually Works Jack Rudenko CTO MadAppGang
  4. Edge AI with Direct Device Control Jeremy Kelaher AI Enablement Architect SBS
  5. COBOL and AI: Building a Self-Serve Knowledge Layer for 2,000 Batch Jobs Matthew Gillard Principal V2 AI
  6. Legacy Software + Agentic Discovery Chris Rickard Founder & CEO Userdoc
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AI Engineering (Day 2 Afternoon)

Thursday 4th June 2026

  1. Why LLMs Fall for Stories (And 5 Production Patterns That Actually Stop Them) Mal Curtis Principal Software Engineer NVIDIA
  2. Hacking the Model: AI Red Teaming in Practice Pas Apicella Field CTO Snyk APJ
  3. Why Most AI De-Identification Fails in Production, And How We Built One Lawyers Actually Trust Moin Zaman Co-founder Smartnote
  4. Are Your AI Agents Secure? Defending the Privileged Agent Daizen Ikehara Principal Developer Advocate Auth0
  5. Your Agents Pass Every Benchmark—Then Memory Breaks Them in Production Ananya Roy AI Architect Databricks
  6. AI Agents Are Distributed Systems Lovee Jain Senior Software Engineer | Google Developer Expert | AWS Community Builder
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Conffab AI Engineer Melbourne 2026 Programme