Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
From the blog
Build a Supervisor meta-agent that monitors worker agents, performs quality checks, triggers automatic retries, and escalates failures — ensuring reliable multi-agent system output.
Protect your AI agent systems from supply chain attacks by implementing dependency scanning, tool artifact verification, signed packages, software bill of materials (SBOM), and continuous vulnerability monitoring.
Learn how to build an AI symptom triage agent that assesses urgency, recommends care levels, and routes patients appropriately — with proper liability disclaimers and clinical protocol adherence.
Learn how to use large language models to generate, filter, and validate synthetic training data for fine-tuning smaller models, with techniques for ensuring quality, diversity, and deduplication.
Synthetic data generation has become a core methodology for training competitive AI models. Learn how leading labs create synthetic training data, maintain quality controls, and avoid model collapse.
Learn proven patterns for writing effective system prompts — from persona design and behavioral constraints to output formatting instructions that produce consistent, high-quality LLM responses.
With 38% of organizations citing lack of AI expertise as their top barrier, this guide covers practical strategies for recruiting, upskilling, and structuring AI teams to move from pilot to production.
A practical guide to defining, measuring, and improving task completion rate for AI agents, including handling partial completions, multi-step tasks, and ambiguous success criteria.
Set up background task queues for AI agent workloads using Celery, RQ, and Dramatiq. Learn worker patterns, retry policies, and result backends for reliable agent job processing.
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