The demo was impressive. In minutes, an AI agent turned raw CSV files into a data model and a Power BI report. Everyone nodded. Then came the question that stops every bit of euphoria: "And can we actually rely on this?"
That question is what this series is about. Because we did not just build an agent that operates Power BI and Microsoft Fabric — we built it so that you can trust its result. The method behind it is called loop engineering.
What we actually built
Not a single do-it-all agent, but a team of specialized agents with clear roles:
- The orchestrator — the single entry point. It accepts a goal, plans, coordinates, and manages progress. It writes no report code itself.
- The Power BI specialist — it plans, builds, and manages semantic models and reports via the open Power BI project format (PBIP/PBIR): data model (TMDL), DAX measures, layout, theme, design.
- The data-engineering worker — the executor for the rest of the Fabric world: Spark/notebooks, Warehouse/SQL, Eventhouse/KQL, eventstreams, dataflows, and migrations.
- The independent reviewer — a read-only review instance that signs off finished reports without changing anything itself.
On top of that come functional personas (for governance, data engineering, migration, app development, and data questions) and more than 30 reusable skills — from report design to semantic-model authoring.
Why this is necessary
An agent that builds nine out of ten reports correctly sounds good — until the tenth crashes on opening in Power BI Desktop with a cryptic error, or leaves a tenant ID in the artifact. Then every run has to be checked manually again, and the efficiency gain is gone.
The reason: classic agents keep their progress only in the volatile chat. They cannot reliably answer three questions: Where am I? What is provably done? What is still missing?
The way out: structure, not hope
Our approach does not bet on an even smarter model, but on a controlled loop around the model — with a fixed state, clear phases, separated roles, and hard quality gates. Over the next six articles I show each of these building blocks — concretely, on our Power BI / Fabric system.
Reliability is not luck. It is engineered.
How reliable are the AI agents you use today to build reports or data models? 👇
#PowerBI #MicrosoftFabric #ArtificialIntelligence #AIAgents #LoopEngineering #BusinessIntelligence
