PRACTICAL AI FIELD GUIDES
Guides for building useful, reliable AI experiences
Explore practical articles on AI agents, RAG, integrations, security, and operations. Browse by topic or search for the question you need answered.
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AI Agents
Design useful agents, choose the right level of autonomy, and plan safe human handoffs.
RAG & Data
Make business knowledge searchable with sound retrieval, evaluation, and data practices.
Integrations
Connect assistants to websites, APIs, CRMs, and the tools your team already uses.
Security & Privacy
Set trust boundaries, protect customer data, and design safer AI workflows.
Industry & Applications
See how AI assistants fit real customer and operational workflows.
Evaluation & Operations
Measure quality, monitor production behaviour, and keep improving over time.
Latest articles
Explore new ideas and practical guidance from the ChatNexus library.
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AI Agent Development: Prototype, Pilot or Production?
A practical guide to deciding whether an AI agent is ready for a prototype, a controlled pilot, or production use. Read guide
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Human Approval Patterns for Autonomous Workflows
How to design useful approval checkpoints for AI workflows, including risk classification, review context, secure execution, expiry, and measurement. Read guide
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Testing Tool Calls, Handoffs and Agent Workflows
A practical test plan for agent extraction, retrieval, tool calls, handoffs, recovery, safety, latency, and regression control. Read guide
3 min read -
Are AI Agent Swarms Ready for Production?
A grounded look at when multi-agent swarms help, where they fail, and how to evaluate coordination, provenance, cost, and safety before production use. Read guide
3 min read -
Agent Handoffs: Router, Supervisor or Specialist?
A practical guide to choosing routing, supervisor, and specialist patterns for multi-step AI workflows without adding unnecessary complexity. Read guide
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AI Workflow Automation: From Trigger to Human Approval
How to design AI workflow automation with bounded actions, meaningful approval steps, recovery paths, and measurable business outcomes. Read guide
3 min read -
RAG Chatbot vs AI Agent: Which Does a Business Need?
A practical comparison of RAG chatbots and AI agents, including when to use each, when to combine them, and how to choose a safe first workflow. Read guide
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AI Agent Incident Response: What to Do When an Agent Misbehaves
When an AI agent misbehaves, the first priority is to limit impact and preserve evidence. A calm incident process is more useful than trying to make the agent… Read guide
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RAG Evaluation Datasets for Business Questions
A RAG evaluation dataset is a curated set of questions, expected evidence, acceptable answers, and known failure cases. It gives a team something stable to test when sources,… Read guide
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AI Agent Registries and Capability Discovery
An agent registry is a directory of agents and the capabilities they advertise. It can help a system find a specialist, but discovery is not proof of trust,… Read guide
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MCP and A2A Together: A Reference Architecture
MCP and A2A solve different coordination problems. MCP gives an agent a structured way to use tools, resources, and prompts. A2A helps agents communicate about work. A useful… Read guide
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A2A Tasks, Messages and Artifacts in Plain Language
A2A describes how one agent can discover and communicate with another agent. The basic objects are easier to understand when they are treated as parts of a business… Read guide
2 min read