The Signal

Everything that matters in AI, with our take.

Updated through the day. Every headline links straight to the source. The two lines underneath are ours.

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arXiv cs.AIPaper3d ago

TurnCost: Turns, Not Observations: Cache-Aware Loop Engineering for Coding Agents

If you're optimizing coding agents for cost, you've been gaming the wrong thing. The paper shows compression and cheaper model routing are addressing rare edge cases, not typical loops. The real insight is that prefix caching is doing most of the work, which means your agent architecture should be designed around cache reuse, not token minimization. Revisit your agent scaffolding with this model in mind.

agents infra cost-optimization

OpenAI NewsArticle7d ago

Asana cuts model costs 76x in browser tests with GPT-6.1 Sol

A 76x cost reduction is real. This shows what happens when models are purpose-built for specific agent tasks instead of forced through a general capability model. The OpenAI move here is strategic: specialized models for agent subtasks fragment the market and raise switching costs. For builders: if you're running browser agents at scale, cost-optimize by task type rather than using one model for everything.

agents openai cost-optimization

arXiv cs.CLPaper25d ago

AgentRouter: Heterogeneous Model Routing for Cost-Optimal Multi-Step Agentic Workflows

This is the kind of work that changes agent economics in production. Routing every step to Claude or GPT-4 wastes 60-80% of compute budget on subtasks that 7B models handle fine. AgentRouter's approach is practical: a 12M-parameter classifier with <5ms overhead that learns which steps need frontier reasoning and which don't. For builders running multi-step agents, this is immediately actionable. For cost-conscious teams, this flips the economics of when agents become viable. Implementation matters less than the insight: heterogeneous routing is now table stakes.

agents routing cost-optimization inference