AI Adoption & Agents
Before You Launch an AI Agent: Test the Workflow, Not Just the Answer
Continue workflow planning with a controlled test record that checks what the application does when the normal path breaks.
Parveen KRPublished 4 min read
Insights
Practical Insights on AI, Data & Microsoft Technologies
Guidance, technical explainers and practical approaches to help your organisation adopt technology and build the skills to use it effectively.
AI Adoption & Agents
Before You Build an AI Agent: Define the Business Workflow
A practical starting point for your first AI agent: define the business outcome, map the workflow, set information boundaries, and decide which actions need human review.
Parveen KRPublished 6 min read
AI Adoption & Agents
Copilot Studio Knowledge: Test What Each User Can Access
Test SharePoint-backed knowledge with representative users in the actual published experience, keeping authentication and document permission checks separate.
Parveen KRPublished 4 min read
AI Adoption & Agents
From Business Problem to Bounded Pilot: A Forward Deployed Engineering Approach
Define a practical discovery-to-handover exercise with clear exclusions, acceptance evidence and a receiving owner.
Parveen KRPublished 4 min read
AI Adoption & Agents
Dynamics 365 Customer Service: Design the Handoff Before Adding AI
Define case ownership, escalation and review before relying on generated summaries to carry customer context between teams.
Parveen KRPublished 4 min read
AI Adoption & Agents
Your RAG Answer Has a Citation. Is the Source Still Current?
Use a controlled document exercise to distinguish a traceable answer from an answer grounded in the current approved source.
Parveen KRPublished 4 min read
AI Adoption & Agents
Choosing Your First AI Workflow: Value, Feasibility and Ownership
Compare candidate workflows using real inputs, review effort and accountable ownership before committing to a pilot.
Parveen KRPublished 4 min read
AI Adoption & Agents
AI Readiness: The Work That Happens Before You Touch a Model
Organisations that struggle to get value from enterprise AI investments almost never fail because of model capability. They fail because the data is not ready, the teams are not aligned, and the governance layer does not exist. This post outlines the readiness work that precedes meaningful AI adoption.
Parveen KRPublished 3 min read
AI Adoption & Agents
RAG in Production: Architecture Decisions That Actually Matter
Retrieval-Augmented Generation (RAG) has become the dominant pattern for grounding enterprise LLM applications in proprietary data. Yet most organisations underestimate the architecture decisions required to move from a working demo to a production system that is accurate, cost-controlled, and auditable.
Parveen KRPublished 3 min read
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