AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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LLM agents solve complex tasks by iteratively changing files, invoking local tools, and interacting with remote services, which modifies state across their local environment and remote services. Today, agents and users must manage these changes explicitly, whether reverting exploratory actions or recovering from errone...
Evaluation with standard filesystem benchmarks and real-world workloads shows that ShieldZFS provides strong integrity and freshness guarantees with performance comparable to state-of-the-art filesystems.
This work presents AOSpec, a lossless framework that co-speculates actions and observations across the full agent-environment loop, and outperforms every practical baseline, reducing mean end-to-end latency by 11.8-32.5% and p99 latency by up to 42.8%.
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