voice agents should know you even before your first interaction
Summary
Developer built a Pipecat plugin integrating Onairos preference model to preload user profiles before voice agent interactions, reducing time-to-useful from 3 minutes to 1:30 by eliminating warmup discovery questions.
Similar Articles
i was tired of voice onboarding, so made it faster.
The author developed a portable user preference profile system that integrates with ElevenLabs and Pipecat agents, allowing voice assistants to remember user styles and interests across different platforms to skip redundant onboarding.
should agents ask for user context up front or learn it slowly?
A discussion on how AI agents should handle user context: upfront disclosure or gradual learning, with various existing approaches like project memory and chat summaries found lacking.
I tested 5 AI voice agent platforms in 2026 on real calls — here’s my honest ranking
A personal ranking of five AI voice agent platforms (LuMay, Vapi, Retell AI, Pipecat, LiveKit Agents) based on production reliability, latency, voice quality, and scalability after 60+ hours of testing.
@liveink: Every AI tool just waits for you to type a prompt. For the last year we built the opposite: an assistant that already d…
Liveink announces a proactive AI assistant that performs tasks before the user prompts it, demonstrated in a real family setting.
Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents
ProAct is a proactive agent architecture that leverages idle-time computation to anticipate user needs, improving task completion efficiency and accuracy. It introduces ProActEval, a benchmark spanning 200 scenarios across 40 domains, and achieves significant gains over reactive baselines: 14.8% reduction in required turns, 11.7% decrease in user effort, and 28.1% cut in hallucination rates.