@ArizePhoenix: Phoenix now lets you compose evaluation strategies in code. Most eval tooling hands you a fixed menu of judge templates…

Phoenix now lets you compose evaluation strategies in code. Most eval tooling hands you a fixed menu of judge templates. Real evaluation is rarely that tidy. Code Evaluators enable you to build evaluation criteria the way you want. You write a Python or TypeScript evaluate() function in the Phoenix UI — no SDK, no local runtime, no deploy step — and Phoenix runs it server-side, recording labels and scores as annotations on every experiment run. Because it's just code, you control the whole strategy: • Composite scoring: blend sub-scores (LLM judgment + deterministic rules) into one weighted metric • Embedding-based evaluation: cosine similarity over embeddings instead of brittle string matching • LLM juries: poll multiple models and combine verdicts into a weighted consensus Sandboxed Code evaluators unlock the idea of agents as a judge as well. We're excited where this is heading.