AI Native DevCon 2026 London — all conference sessions as interactive skills
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This public transcript is intentionally redacted. The source talk included demonstrations and setup-oriented material for local agent isolation. The public version preserves the defensive concepts while removing operational commands, manifests, and sensitive-value handling mechanics.
Oleg Selajev discusses how to run local AI agents more safely. The talk is framed around the risk of giving autonomous tools broad access to a developer machine and then trusting prompt-level instructions to keep them safe.
More autonomous agents need stronger boundaries. A policy written in a prompt or instruction file is not the same as an enforced isolation boundary. The talk advocates disposable isolated environments, explicit sharing rules, constrained network behavior, and sensitive-value handling outside the agent-visible workspace.
The talk emphasizes that agents become risky when they can combine:
The more autonomy and permissions the agent has, the more important it is to enforce boundaries outside the model.
The public summary preserves these concepts:
Operational setup details are redacted.
The talk also frames sandboxing as a developer-experience problem. If isolated environments are too slow or empty, teams will bypass them. A practical rollout needs reusable configuration, pre-approved capabilities, policy defaults, and a clear path for vendors or platform teams to provide safe integrations.
Sandboxing reduces local-machine blast radius. It does not by itself solve application-level risks, such as an agent being granted broad access to communication tools. The safe lesson is to combine infrastructure isolation with product-level permissions and review.
This redacted bundle supports architecture review and policy planning. It does not provide commands, setup files, or sensitive-value routing recipes.
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