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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Building Agent Memory with PostgreSQL: JSONB, pgvector and the Source of Truth
A practical PostgreSQL design for agent memory that combines structured facts, embeddings, metadata filters, expiry, and clear ownership. Read guide
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Prompt Engineering vs Context Engineering for AI Agents
Prompt wording matters, but agent quality usually improves faster when the surrounding context, tools, permissions, and evidence are designed well. Read guide
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Prompt Injection in RAG: Why Retrieved Text Must Be Treated as Data
Prompt injection is not solved by a clever system prompt. Build safer RAG by separating instructions, evidence, permissions, and side effects. Read guide
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Hybrid Search in PostgreSQL: Combining Keyword and Vector Retrieval
Why good RAG often combines lexical search, vector similarity, metadata filters, and reranking instead of trusting one retrieval method. Read guide
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pgvector for RAG: HNSW, IVFFlat, Filtering and Tenant Isolation
A practical guide to using pgvector in PostgreSQL for RAG, including index choice, metadata filters, recall, and tenant boundaries. Read guide
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Memory Architectures for AI Agents: Short-Term, Long-Term, Episodic and Semantic Memory
A practical way to separate working context, durable facts, past experiences, and business knowledge in an agent memory design. Read guide
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AI Agents for South African Business Support Workflows
Practical considerations for South African AI-agent workflows across web and messaging channels, language, mobile access, privacy, handoffs, and operations. Read guide
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AI Agents for Customer-Service Knowledge Search
A practical guide to building an internal customer-service knowledge agent with governed sources, permission-aware retrieval, citations, feedback, and human escalation. Read guide
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AI Agents for Sales Research and Account Preparation
How to use AI agents for evidence-based account research, meeting briefs, CRM context, source citations, review, privacy, and measurable sales preparation. Read guide
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How to Choose an AI Agent Development Partner
A practical way to compare AI-agent development partners using workflow evidence, ownership, security, maintainability, operating cost, and a bounded discovery. Read guide
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MCP Authentication and Authorization Patterns for AI Agents
How to secure MCP servers with trusted identity, short-lived credentials, per-tool authorization, tenant isolation, delegated access, and misuse testing. Read guide
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When Is a Chatbot Enough—and When Do You Need an AI Agent?
How to choose between a RAG chatbot, guided workflow, and tool-using AI agent based on the outcome, risk, integrations, and operating cost. Read guide
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