The newest customer interaction is present, but retrieval still favors an older summary.
Agents need current channel preferences while the retrieval path must remain fast for every request.
Who you’d be doing this for
“Our agent saw the new preference in the profile, then sent the next message through the old channel anyway.”
Rodrigo Hernandez · Application Developer
Builds a customer-facing AI agent that retrieves profile and interaction context before responding.
What is at stake
Agents are retrieving older interaction summaries after a customer updates a preference. You must weigh a ranking correction against retrieval latency and safe rollout coverage.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- context freshness vs retrieval latency
- ranking correction vs integration filtering
- developer trust vs API stability
- fast rollout vs sampled evidence
Why Twilio
Customer Memory is judged by whether applications and AI agents receive current identity, interaction, and channel context when they ask for it.
Written with these in mind
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This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.