Researchers measured token consumption of Claude Code and OpenCode on identical tasks and found Claude Code uses approximately 33,000 tokens for system prompts and tooling before the user's actual prompt, compared to OpenCode's 7,000 tokens. Claude Code also wrote cache tokens at up to 54 times the rate of OpenCode, with real production setups using 75,000-85,000 tokens before any user input, and subagent delegation multiplying costs further. The difference narrowed on newer models and when Claude Code batched multiple tool calls efficiently, but Claude Code's larger baseline overhead remains a significant factor in production agentic AI systems.
DeepMind developed a delegation framework that enables AI agents to safely hand off tasks to other AI agents and humans by incorporating task allocation, authority transfer, accountability, and trust mechanisms. The framework addresses limitations in existing methods that rely on simple heuristics and cannot dynamically adapt to environmental changes or handle unexpected failures. This approach establishes structured protocols for human-AI collaboration that could inform standards as AI agents take on increasingly complex autonomous work.
Allen Institute (AI2)·3 months ago·
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● 2 sources
Ai2's Skylight team built Shippy, an AI agent for maritime domain awareness that makes high-stakes operational decisions based on real-time satellite and vessel data. The system uses a modular architecture with a versioned Docker image containing the agent's persona and skills, a deterministic CLI interface to the Skylight API to prevent subtle bugs, and Mothership, a Kubernetes-based hosting platform that isolates each user's session and data with dedicated pods. The team developed a custom evaluation framework scored by subject-matter experts against live data, and Shippy will expand to control Skylight's map interface, route queries to smaller models, and maintain cross-thread memory for persistent user context.
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