Part 3 of a series on building agents with the Microsoft Work IQ API. Part 1 introduced Work IQ, and Part 2 built a conversational A2A client with multi-turn context and streaming. Over the last year, one problem has followed nearly every capability we added to our private AI application: tools multiply quickly. The first connector is manageable. So are the first few functions. Then the agent needs email, calendar, people, Teams, SharePoint and OneDrive.…
Part 2 of a series on building agents with the Microsoft Work IQ API. Part 1 explained the Work IQ model and made a first grounded call with raw HttpClient. The raw A2A call in Part 1 was useful for one reason: it showed exactly what crossed the wire. I could see the Work IQ token audience, the JSON-RPC method, the A2A version header and the response shape. That removed a lot of guesswork. It…
In Part 1, we built a Foundry agent with long-term memory that could remember user preferences, roles, and context across sessions without any custom embedding pipelines. If you haven’t read that post yet, I’d recommend starting there, as this one builds directly on top of that code. But here’s the thing: memory on its own is useful, but it’s not transformative. Knowing that a user prefers bullet-point summaries or works in the finance department is…
In Part 1, we explored the fundamental shift from manual SharePoint indexing to Azure AI Foundry’s SharePoint grounding tool. We covered the challenges of traditional approaches, the power of Microsoft 365 Copilot API, and the economic considerations for enterprise adoption. Now it’s time to get our hands dirty with the actual implementation. In this part, we’ll build a complete, production-ready SharePoint agent system. Prerequisites and Setup Before diving into implementation, ensure you have the following…
You know that feeling when you’ve spent weeks building a custom indexing pipeline for SharePoint content, complete with incremental updates, change tracking, and governance controls—only to discover that Microsoft just released a tool that does all of this automatically? Many companies these days store thousands of policy documents, procedures, and knowledge base articles scattered across multiple SharePoint sites. The existing solution required manually extracting content, chunking it into a vector store like Azure AI Search,…