World Congress 2026 Europe • Jul 9, 2026 • Session details

What 500+ Production Environments Taught Us About Shipping AI Agents

Liran Hason

AI agent demos are easy. Scaling them is brutal. Discover why 500 production environments required aggressive caching, model migrations, and a UI that thinks out loud.

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#1 about 2 min

Building an agentic observability system for telemetry data

An overview of an agentic system that queries logs, metrics, and traces to investigate production root causes.

#2 about 3 min

Moving an impressive AI agent demo into production environments

While building a compelling demo took only two weeks, reaching internal beta and design partners required six months of refinement.

#3 about 6 min

Treating language model upgrades as complex system migrations

Upgrading foundation models changes agent behavior unpredictably, requiring extensive evaluation and prompt fine-tuning before deployment.

#4 about 5 min

Optimizing AI infrastructure costs by maximizing token caching

Relying on agent SDK abstractions can hide inefficient prompt management, leading to low cache hit ratios and high context costs.

#5 about 5 min

Improving perceived latency by making agent reasoning visible

Streaming the agent's thought process and active tool calls provides continuous user feedback, effectively eliminating complaints about slow response times.

#6 about 3 min

Key learnings from scaling agents across production environments

Summarizing practical insights on model migrations, cost tracking through cache metrics, and the critical role of user experience in adoption.

#7 about 4 min

Evaluating and scoring models to ensure reliable prompt migrations

Designing comprehensive evaluation systems helps score agent success rates and guide prompt adjustments during foundational model transitions.

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2:04 min

Inspiration and challenges of scaling AI agent communication

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Introduction to building reliable AI agents in production

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Shifting developer workloads and realistic AI productivity gains

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Adapting observability strategies for long-running enterprise AI agents

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2:43 min

Deploying a web application through an AI agent workflow

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Resolving developer challenges in AI agent implementation

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