Normalized Telegram record

Claude Code separates model choice from effort

Anthropic exposes model selection and effort level as different controls for capability, token use, latency, and persistence.

Signal contract

Anthropic exposes model selection and effort level as different controls for capability, token use, latency, and persistence. Agent routing is becoming a multidimensional runtime decision rather than a single model dropdown, making task-aware cost controls more practical. Novelty: notable. Verification: source-inspected. This New Runtime record is an evidence-linked retrieval unit.

Source ledger

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2 public sources
#SourceRolePublic status
1claude.comsourceprimary receiptsource_urls
2code.claude.comsourcesupporting receiptsource_urls

Observation

Anthropic exposes model selection and effort level as different controls for capability, token use, latency, and persistence.

Why it matters

Agent routing is becoming a multidimensional runtime decision rather than a single model dropdown, making task-aware cost controls more practical.

Entities

Claude Code, Anthropic

Provenance

This public record is an English normalization of QWG AI Telegram message 2676. The complete original-language post remains the canonical raw message.

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Discovery graph / next reads

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  1. 01topicAgent economics - New RuntimeExplore the agent economics topic hub.
  2. 02topicCoding agents - New RuntimeExplore the coding agents topic hub.
  3. 03related materialA pricier model can be cheaper per completed taskShares agent economics and coding agents.
  4. 04related materialOpenCode makes the model a swappable dependencyShares coding agents and model routing.
  5. 05related materialDatabricks benchmarks coding agents on its own codebaseShares agent economics and coding agents.

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