Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
From the blog
Learn how prefix tuning and soft prompts let you customize LLM behavior by training small continuous vectors prepended to model inputs, achieving fine-tuning-level performance at a fraction of the cost.
Master the art of building high-quality fine-tuning datasets with practical techniques for data collection, cleaning, deduplication, format validation, and diversity analysis.
Build AI agents with honesty constraints, manipulation detection, and user protection mechanisms that prevent deceptive patterns while maintaining effectiveness.
Build type-safe AI agent APIs with Prisma ORM covering schema design for conversations and messages, client generation, relational queries, transactions, and migration workflows in TypeScript.
Implement privacy-preserving techniques in AI agent systems including differential privacy for data aggregation, federated learning for distributed model training, on-device processing, and compliance with GDPR and CCPA requirements.
Design proactive conversational AI agents that initiate helpful interactions at the right time, suggest relevant next actions, and respect user preferences around unsolicited outreach.
Build procedural memory systems that let AI agents record, store, replay, and optimize multi-step task procedures, enabling skill learning and execution improvement over time.
Deploy LangGraph agents to production using LangGraph Cloud with API endpoints, cron triggers, monitoring, scaling strategies, and operational best practices for stateful agent workflows.
Learn how to take a RAG pipeline from prototype to production with response caching, embedding caching, async retrieval, horizontal scaling, monitoring, and operational best practices.
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