ai-agents
7 posts — newest first.
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Observability for Agents: What You Instrument When the System Decides for Itself
A request either worked or didn't. An agent run can succeed on every span and still be wrong, slow and expensive. What the GenAI conventions ask you to record.
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Prompt Injection: Why Your Agent Believes the Wrong Text
An LLM sees one stream of tokens, not instructions and data. That is why prompt injection has no parser fix — and why provenance, not filtering, is the control.
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Token Exchange: Delegation Is Not Impersonation (RFC 8693)
When a service calls another service for a user, the token it carries decides whether your audit log says who acted. RFC 8693 makes that a design choice.
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Your AI agent can't tell a quiet system from a broken collector
Autonomous remediation gates on model confidence and never on whether the telemetry is trustworthy. Telemetry integrity belongs in the gate too.
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The Five Types of Agentic Memory (and When to Use Each)
Agentic memory is five things — working, episodic, semantic, procedural, entity — each with its own storage, eviction, and failure mode. A decision guide.
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OKF: The Missing Context Layer for AI Agents
The Open Knowledge Format gives agents a structured vocabulary for what data they're touching and where it came from — auditable, not blind, reasoning.
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What is an AI agent? A primer for cloud engineers
A primer on AI agents — the perceive-reason-act loop, what separates an agent from a one-shot LLM call, and the classical agent types SREs now operate.