Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Learn how to build computer use agents that interact with browser and desktop applications by capturing screenshots, detecting UI elements, performing click and type actions, and verifying results through visual feedback loops.
Build an AI agent that handles employee clock-in/out, displays work schedules, manages timecard exceptions, and routes approval workflows — replacing clunky time tracking interfaces with conversational interactions.
AGI is the script-per-call hand-off. AMI is the firehose of events and commands. Both still ship in Asterisk 22 and both still matter for AI voice if you know where each one breaks at scale.
Build production-grade Grafana dashboards for AI agent systems that visualize conversation throughput, per-model costs, LLM latency percentiles, and tool usage patterns using Prometheus metrics.
Implement the Observer pattern with an event bus for AI agent systems — enabling decoupled, publish-subscribe communication between agents for flexible coordination.
A clear, code-driven explanation of the transformer architecture including self-attention, multi-head attention, positional encoding, and how encoder-decoder models work.
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.
Learn how to get reliable JSON output from Gemini using response_mime_type, JSON schemas, enum constraints, and validation. Build agents that produce machine-readable structured data every time.
Understand the ReAct (Reasoning + Acting) pattern that powers most modern AI agents, with a step-by-step breakdown of observation loops and a working Python implementation.
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