When building applications that use the Anthropic API, every model version bump (e.g. claude-sonnet-4-5-20250929 → claude-sonnet-4-6) requires finding and updating every hardcoded model string across the codebase. This creates maintenance overhead and causes silent failures when old model IDs are retired.
Request: Provide stable aliases that always resolve to the current recommended model per tier, similar to how OpenAI handles gpt-4o-latest:
claude-opus-latest
claude-sonnet-latest
claude-haiku-latest
These aliases would resolve server-side to the current production model, so applications stay functional across model updates without code changes.
Precedent: OpenAI, Google (Gemini), and AWS Bedrock all offer similar "latest" or "stable" pointer aliases.
Workaround we're currently using: A single shared constant in the codebase (AI_MODEL = "claude-sonnet-4-6") — one file to update instead of many. But a server-side alias would eliminate the update entirely.
When building applications that use the Anthropic API, every model version bump (e.g. claude-sonnet-4-5-20250929 → claude-sonnet-4-6) requires finding and updating every hardcoded model string across the codebase. This creates maintenance overhead and causes silent failures when old model IDs are retired.
Request: Provide stable aliases that always resolve to the current recommended model per tier, similar to how OpenAI handles gpt-4o-latest:
claude-opus-latest
claude-sonnet-latest
claude-haiku-latest
These aliases would resolve server-side to the current production model, so applications stay functional across model updates without code changes.
Precedent: OpenAI, Google (Gemini), and AWS Bedrock all offer similar "latest" or "stable" pointer aliases.
Workaround we're currently using: A single shared constant in the codebase (AI_MODEL = "claude-sonnet-4-6") — one file to update instead of many. But a server-side alias would eliminate the update entirely.