Event-Driven AI Agents: From Business Signals To Useful Actions
Learn how event-driven AI agents respond to business events, handle duplicates and failures, and keep consequential actions under control.
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Practical guides to planning, building and running digital products. Written to help you make informed decisions.
Learn how event-driven AI agents respond to business events, handle duplicates and failures, and keep consequential actions under control.
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Explore how durable execution helps long-running AI agents recover, manage retries and handle uncertain external actions.
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Learn how prompt injection reaches AI agents through external content and how to reduce risk with permissions, validation and review.
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Understand AI agent sandboxes, isolation boundaries, network access, secret handling and the checks needed before actions leave the sandbox.
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Learn how to observe AI agent workflows with traces, useful metrics, privacy controls and evidence for debugging.
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A practical guide to computer use agents, including observation, action, feedback, permissions and human review.
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How agent skills package task-specific instructions and resources, when to use them, and how to manage access, testing and updates.
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Design structured AI outputs with clear fields, honest missing values, source checks and business validation before the application takes action.
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Learn how AI model routing selects eligible models, handles escalation and compares task quality, total cost and response time against a fixed baseline.
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