PromptLayer¶
New York–based platform for prompt management, eval, logging, and agent observability. Founded by jared-zoneraich. Self-described as "the workbench for AI engineering." Launched ~2022; processes millions of LLM requests per day.
Thesis¶
- Rigorous prompt engineering + rigorous agent development.
- Product/subject-matter experts in the loop — e.g. lawyers, not just engineers, when building AI-for-law.
- Batch runner as eval — screenshots in the talk show PromptLayer running headless claude-code across a dataset as an end-to-end test rig (cf. agent-smell).
- Eval primitives include LLM-as-judge assertions, code execution, back-testing against historical prod traffic.
Relationship to the wiki¶
PromptLayer's stance tracks the same harness-centric convergence the wiki has observed in harness-engineering, chris-shayan's Backbase work, and ryan-lopopolo's Symphony — treat prompts + tools as versioned artifacts, instrument the loop, evaluate in production.
Internal rule at the company: "If it takes less than an hour in Claude Code, just do it — don't prioritize." Engineering org restructured around this.