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World Congress 2026 Europe - Virtual Stage • Jul 7, 2026 • Session details

From Black Box to Glass Box : Bedrock AgentCore Observability

Yasemin Aktürk

Why did your AI hallucinate? Discover how Bedrock Agent Core uses automated tracing to expose every reasoning step, turning complex LLM logic into a transparent glass box.

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#1 about 1 min

Introduction to Amazon Bedrock Agent Core capabilities

Agent Core provides production-ready building blocks to simplify the overall development and infrastructure of AI agents.

#2 about 3 min

How Agent Core runtime executes and tracks agent requests

Runtime infrastructure paths prompts through sandbox environments to safely execute tool calls and track latency.

#3 about 3 min

Retaining conversation context with short and long-term memory

Background models automatically extract and synchronize important facts across both active and historical conversation memory streams.

#4 about 2 min

Architecture overview of the demo customer support agent

The agent requires access to specific endpoints and environment tools to successfully fulfill customer support queries.

#5 about 4 min

Navigating the GenAI observability dashboard in Amazon CloudWatch

Centralized monitoring dashboards present detailed traces, event memory metrics, and token usage statistics for root cause analysis.

#6 about 5 min

Analyzing tool selection and execution within trace details

Trace trajectories demonstrate whether an agent routed user requests correctly while simultaneously tracking total token usage.

#7 about 2 min

Reviewing traces to uncover missed tool calls and inaccuracies

Trace logs expose factual inaccuracies when agents hallucinate answers instead of querying appropriate external data tools.

#8 about 3 min

Evaluating agent response accuracy and tool selection logic

Built-in correctness metrics score factual accuracy to help developers diagnose the root cause of hallucinated answers.

#9 about 2 min

Reviewing agent interactions completed without external tool execution

Execution steps verify that basic conversational queries successfully bypass external endpoints to lower overall tool usage.

Matching moments

1:01 min

Capturing AI session telemetry for deep usage insights

Brian Scanlan Brian Scanlan · WWC Europe 2026

1:27 min

Building observability to verify unexpected AI agent behavior

Adam Bird Adam Bird · WWC Europe 2026

2:55 min

Executing and analyzing the core AI agent sub-workflow

Max Tkacz Max Tkacz · WWC 2025

4:10 min

Architectural building blocks for enterprise agent development platforms

Dennis Zielke Dennis Zielke +1 · WWC 2025

2:42 min

Tracing agentic capabilities and step-by-step code execution

Jemiah Sius Jemiah Sius +1 · WWC Europe 2026

5:52 min

Evaluating unguided agent tools against context-aware investigation pipelines

Aram Hakobyan Aram Hakobyan +1 · WWC Europe 2026

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