Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
From the blog
Build an AI agent that applies the scientific method to data analysis — generating hypotheses, designing experiments, performing statistical tests, drawing conclusions, and iterating on findings with rigorous methodology.
Step-by-step guide to installing Microsoft UFO, configuring API keys, setting up the configuration files, and running your first automated Windows task with natural language.
Learn what Microsoft UFO is, how its dual-agent architecture combines HostAgent and AppAgent with GPT-4V vision to translate natural language requests into Windows UI actions automatically.
Build an AI agent that reads documents, extracts named entities and their relationships, constructs a knowledge graph stored in Neo4j, and provides a natural language query interface over the graph.
Build an AI agent that performs structured legal reasoning — searching precedents, constructing multi-step arguments with evidence chains, generating counter-arguments, and producing balanced legal analysis.
Learn how to build AI agents with metacognitive capabilities — uncertainty estimation, confidence calibration, knowledge boundary detection, and know-when-to-ask patterns that make agents more reliable and honest.
Understand the MRKL (Modular Reasoning, Knowledge, and Language) architecture that combines LLMs with specialized expert modules, intelligent routing, and structured knowledge retrieval for building powerful AI systems.
Explore multi-agent reinforcement learning (MARL) concepts including reward shaping, cooperative versus competitive strategies, and policy gradient methods for agent teams with practical Python implementations.
Construct a multi-agent research system with four specialized agents — Scientist, Librarian, Analyst, and Writer — that collaborate on source discovery, analysis, and paper generation with complete Python code.
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