Customer-Support Agent Memory and Conversation History Patterns
Customer-support agents that forget the user's last ticket lose trust fast. The hybrid history + facts memory pattern that retains context across reopened tickets.
Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
Latest analysis
Customer-support agents that forget the user's last ticket lose trust fast. The hybrid history + facts memory pattern that retains context across reopened tickets.
GQA and MLA cut KV-cache memory by huge factors. The 2026 implementations and the production tradeoffs that decide which one to use.
Production agents that surface uncertainty cleanly are dramatically more useful than confident-but-wrong ones. The 2026 uncertainty-design patterns.
LlamaCloud's managed parsing, indexing, and retrieval is now production-ready. The build-vs-buy math for a 5-person AI team weighing operational cost honestly.
Prompt engineering is fading. Context engineering — what to include in the model's window — is the 2026 architect's primary job.
Triage to specialist to return-to-orchestrator pattern explained with code. CallSphere's OpenAI Agents SDK handoffs vs Vapi Squads' linear chain.
A 12-factor framework for selecting an LLM for production use in 2026 — beyond benchmarks, into the operational dimensions that decide success.
Function-calling reliability is mostly a schema-design problem. The 2026 patterns for tool definitions that LLMs actually call correctly.
The three AI IDEs that dominate developer workflows in 2026 — benchmarked on agentic capability, codebase awareness, and developer productivity.
Get notified when we publish new articles on AI voice agents, automation, and industry insights. No spam, unsubscribe anytime.
Try our live demo -- no signup required. Talk to an AI voice agent right now.
© 2026 CallSphere Inc. All rights reserved.
Made within San Francisco