Build a Claude Agent SDK Agent: Step-by-Step Guide
Step-by-step: build a working agent with the Claude Agent SDK — setup, system prompt, tools, the run loop, permissions, and production guardrails.
7 min read
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AI Voice Agent Insights & Guides
Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Claude Agent SDK Architecture: How the Pieces Fit
How the Claude Agent SDK works internally — the agent loop, tool runtime, context manager, permissioning, and subagents, connected end to end.
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Accessibility Auditing with GPT Vision: Automated WCAG Compliance Checking
Use GPT Vision to perform automated accessibility audits that detect visual WCAG violations including contrast issues, missing labels, touch target sizes, and reading order problems — generating actionable compliance reports.
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Agent Governance and Oversight: Building Control Planes for Autonomous Agent Systems
Build comprehensive governance systems for autonomous AI agents including control plane dashboards, kill switches, audit trails, budget enforcement, and human escalation mechanisms with production-ready Python implementations.
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Agent Memory Sharing Strategies: Blackboard, Message Passing, and Shared Vector Stores
Compare three fundamental memory sharing architectures for multi-agent systems — blackboard, message passing, and shared vector stores — with implementation patterns, consistency considerations, and performance tradeoffs.
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Building an Agent Playground: Interactive Testing Environment for Prompt and Tool Development
Build a full-featured agent playground with a web UI that lets you test prompts live, tune parameters, compare model outputs side by side, and export working configurations for production deployment.
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Agent-to-Agent Protocol Design: Building Interoperable Multi-Agent Communication
Design robust communication protocols for multi-agent systems including message schemas, capability advertisement, negotiation protocols, and service discovery mechanisms with practical Python implementations.
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Agent World Models: Internal Simulations for Planning and Prediction
Explore how AI agents use internal world models to simulate future states, predict action consequences, and perform look-ahead planning — enabling smarter decisions without costly real-world trial and error.
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AI Agent for Automated Data Entry: Reading Source Documents and Filling Web Forms
Build an AI agent that reads source documents using OCR and vision models, maps extracted data to web form fields, fills forms automatically, and validates entries with intelligent error correction.
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