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eve

1 post about eve. Every summary links to the original.

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Twilio
Building a Multi-Channel AI Agent with Twilio Conversations and eve
Building a multi-channel AI agent that remembers customers across SMS and WhatsApp is challenging because most projects require a custom memory layer; Twilio Conversations and Vercel’s eve solve this by cleanly separating short-term and long-term memory. eve holds the per-conversation transcript, while Twilio’s Memory Store persists extracted facts across sessions using automatic observation extraction from Conversation Intelligence. The tutorial walks through provisioning an Orchestrator Configuration that stitches SMS and WhatsApp into one thread, wiring a dynamic instruction that merges both memory sources, and using ngrok for local webhook tunneling. The resulting agent remembers customer context across channels and sessions, allows model swapping in one line via the AI SDK, and extends cleanly to voice and RCS without bespoke persistence code. The full sample project is on GitHub at IObert/twilio-conversations-eve-agent, and the tutorial includes provisioning steps using curl, environment variable setup, and local testing with pnpm dev.

The best engineering reads, once a week.

Topic

1 post about eve. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

Twilio
Building a Multi-Channel AI Agent with Twilio Conversations and eve
Building a multi-channel AI agent that remembers customers across SMS and WhatsApp is challenging because most projects require a custom memory layer; Twilio Conversations and Vercel’s eve solve this by cleanly separating short-term and long-term memory. eve holds the per-conversation transcript, while Twilio’s Memory Store persists extracted facts across sessions using automatic observation extraction from Conversation Intelligence. The tutorial walks through provisioning an Orchestrator Configuration that stitches SMS and WhatsApp into one thread, wiring a dynamic instruction that merges both memory sources, and using ngrok for local webhook tunneling. The resulting agent remembers customer context across channels and sessions, allows model swapping in one line via the AI SDK, and extends cleanly to voice and RCS without bespoke persistence code. The full sample project is on GitHub at IObert/twilio-conversations-eve-agent, and the tutorial includes provisioning steps using curl, environment variable setup, and local testing with pnpm dev.

The best engineering reads, once a week.