Blog
Highlights from the Currai blog: the posts worth reading first.
A complete, code-first guide to turning OpenAI Realtime voice conversations and text-to-speech generations into readable Currai User Stories and correctly nested traces.
A step-by-step guide to importing completed Retell AI calls into Currai with signed call-ended webhooks—without adding capture code to the live voice agent.
A step-by-step guide to importing completed Vapi calls into Currai with an authenticated webhook—without adding capture code or sharing a Vapi private API key.
Browse implementation notes, observability guides, product decisions, and workflow ideas by topic.
Active observability turns production LLM traces into continuous signals for quality, cost, latency, prompts, tools, and evals before users report a problem.
Read moreAn agent can call the right tool and still fail the task — or complete the task despite a clumsy path. Here's how to score tool-calling and task completion as separate metrics, so a failure points to a fix.
Read moreTrace, span, generation — three nouns that cover everything an LLM app does. Understand the data model and your instrumentation stops being guesswork.
Read moreAgents loop, call tools, and call themselves — a single request can be dozens of model calls. Here's how to trace agent runs so you can see exactly where one went off the rails.
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