12 posts
This guide walks through the setup, MCP response parsing, long-lived Entra token refresh, per-user permission filtering, citation handling, and how to avoid conflicts between LangGraph’s planner and Foundry IQ’s agentic retrieval planner.
There's an awkward moment in every agentic data project. The agent works. It writes decent SQL, it reasons about schema, it proposes a migration that looks righ...
Most agents are billed for tools they don't use. Not once — on every single turn. The mechanics are simple enough that it's easy to miss. When you give a model ...
Why "search" isn't enough anymore A plain RAG pipeline — embed a query, hit a vector index, stuff the top-k chunks into a prompt — works fine for a single-turn ...
Most "RAG tutorials" stop at a single embedding query against a single index. That works for a demo and falls over the moment a real user asks something like "c...
Once your multi-agent system (Parts 6-8) is functionally solid, the question that comes up in every enterprise security review is the same: how do you know an a...
If you're building AI agents in 2026, you've probably bumped into at least one of these acronyms: MCP, A2A, AG-UI. Maybe all three. And if you're anything like ...
Once you've decided a workload belongs in Foundry Agent Service (Part 6), the next problem is orchestration mechanics: multiple agents that need to share state,...
If you've been building with AI agents, you've probably hit the same wall I did: your agent needs to do things — query databases, call APIs, check systems — but...
Explore the architectural shift toward agentic AI as 65% of enterprises prepare for deployment by 2027. Learn about multi-agent systems and infra readiness.
This is the decision that most often gets made by default (whichever tool the first prototype happened to use) rather than deliberately — and it's expensive to ...
The transition from large language models (LLMs) as simple chat interfaces to autonomous AI agents represents the most significant shift in enterprise software ...