Discover how Stockland, one of Australia's largest diversified property groups, built an intelligent AI assistant on AWS that puts enterprise knowledge at everyone's fingertips. This session explores a multi-agent system powered by Amazon Bedrock & Strands SDK and embedded in Microsoft Teams, that enables teams to streamline vendor management, automate routine tasks and accelerate decision-making. Learn how Stockland built intelligent workflows that transform procurement data into actionable insights, reducing manual effort while improving accuracy and compliance.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Multi-agent system on Bedrock + Strands. Embedded in Microsoft Teams for vendor management, routine tasks, decision-making. Procurement data → actionable insights.
Why it matters
Property is logistics-heavy. Agents inside Teams put intelligence where work actually happens.
The hard parts
Teams bot integrations have UX constraints. Agents must be glanceable, not deep-dive.
Playbook moves
(1) Optimise for the 30-second interaction. (2) Anything longer should kick to a different surface. (3) Make handoffs to human owners explicit and easy.
The surprise
The biggest engagement driver in chat-based agents isn't capability — it's *response time*. Sub-second feels magical; 5+ seconds feels broken. Latency budget matters more than feature count for chat-embedded agents. Optimise inference time before adding tools.
---
Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
Live updates related to this session LIVE
Sourced via Parallel AI Monitor — continuous web watch on 21 topical streams. Updated .
- edu.google.com high confidence Multi-agent collaboration patterns
Learning Tools & Educational Solutions
Google introduced the A2A (Agent2Agent) protocol, a standardized communication framework designed to enable interoperability between AI agents across different frameworks, teams, and organizations. Launched as part of a broader agentic suite at Google Cloud Next 2026, it includes
- medium.com high confidence Decision lineage & audit trails for agents
The Context Graph Revolution: Why Enterprise AI ... - Medium
Daxn launched an AI agent governance system that provides a full audit trail and captures the complete multi-step journey for every agent action to ensure fast and explainable decisions.
- linkedin.com high confidence Multi-agent collaboration patterns
A2A Net
Google introduced the A2A (Agent2Agent) protocol, a standardized communication framework designed to enable interoperability between AI agents across different frameworks, teams, and organizations. Launched as part of a broader agentic suite at Google Cloud Next 2026, it includes
- developers.googleblog.com high confidence Multi-agent collaboration patterns
Announcing the Agent2Agent Protocol (A2A) - Google Developers ...
Google introduced the A2A (Agent2Agent) protocol, a standardized communication framework designed to enable interoperability between AI agents across different frameworks, teams, and organizations. Launched as part of a broader agentic suite at Google Cloud Next 2026, it includes
- union.ai high confidence Decision lineage & audit trails for agents
Agentic AI - Union.ai
New analysis of Gartner's 2026 predictions indicates that the Context Graph is the critical architectural gap that agents must fill to ensure reliable and scalable decision-making within enterprise settings.
External links matched to this session via topic relevance. The KB does not endorse third-party content; verify before citing.