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Your Agent Didn’t Fail. Your Harness Did.

Conference Context

Session Description

AI agents do not fail only because the model is wrong. Many production failures happen in the harness around the model: state is not persisted, two runs mutate the same session, a tool call never returns, an approval loses scope, or an internal success never becomes user-visible proof. This talk uses OpenClaw as a public case study to examine real harness failure modes and extract a reusable production model for AI engineers. We will look at how events enter an agent system, how session state is rehydrated, why single-writer lanes and throttles matter, and why tool execution needs scoped approvals and auditable receipts. The core idea is simple: a model proposes, the harness commits, and the receipt proves it. Attendees will leave with a practical 'run receipt' audit they can apply to their own agents: what woke it up, which state did it inherit, what authority did it use, what executed, and what evidence survived.

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Synthesized Breakdown

Your Agent Didn’t Fail. Your Harness Did. ## Conference Context - Date/time: 2026-06-29 · 11:10am-11:30am - Track/room: Claws & Personal Agents · Track 1 - Speaker(s): Vinoth Govindarajan - Session type/status: session · confirmed - Track: Claws & Personal Agents - Room: Track 1 - Session type: session - Status: confirmed ## Session Description AI agents do not fail only because the model is wrong. Many production failures happen in the harness around the model: state is not persisted, two runs mutate the same session, a tool call never returns, an approval loses scope, or an internal success never becomes user-visible proof.

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