Part 4 of a series on building agents with the Microsoft Work IQ API. Part 1 introduced Work IQ, Part 2 built a conversational A2A client, and Part 3 gave a custom agent Microsoft 365 capabilities through MCP. The first three agents in this series were useful only while they were running. Part 2 remembered a conversation through contextId. Part 3 could read and change Microsoft 365 data through MCP. Stop either process, however, and…
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, start there. This one builds directly on top of that code. Memory alone is useful. It just doesn’t go very far on its own. Knowing a user prefers bullet-point summaries or works in finance is helpful context, but it doesn’t change what the…
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 cost considerations for enterprise adoption. This part is the build: connecting a SharePoint site, wiring the tool into a .NET agent, and testing it end to end. Prerequisites Before diving into implementation, ensure you have the following ready: Set up…