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.
Parallel agents can reduce wall time or multiply duplicated work, conflicts, and cost. Evaluate concurrency as a quality-adjusted scaling curve instead of assuming more agents are better.
Read moreCoding agents can retrieve benchmark answers, exploit weak graders, and optimize for artifacts instead of the task. Here is how to build evals that still measure real capability.
Read moreDependencies, credentials, repository state, tools, and network access can change agent performance as much as the model. Treat the environment as a versioned evaluation input.
Read moreTask completion rewards action, but reliable agents must also clarify, abstain, and stop. Evaluate whether an action was necessary before celebrating its outcome.
Read moreThe common jailbreak techniques that get LLMs to break their own guardrails, why they work, and how to turn each one into a test you run continuously instead of a surprise you find in production.
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