Build suite
Stage 3 of the pipeline. Build turns an approved mapping into a built, tested Fabric table with a pull request, driven from a work-item ticket. It is the original, production-hardened suite: a 14-step end-to-end workflow with two self-correction loops, where a debug engineer agent diagnoses failures and drives retries until the table builds, its data-quality tests pass, and the PR is opened.
The agents
| Agent | Role |
|---|---|
MappingParser | mapping doc (MD) → structured spec |
ConfigGenerator | spec → delta-gen YAML |
PipelineValidator | validates the YAML / schema |
DebugEngineer | diagnoses failures, drives the self-correction loops |
Executor | runs the template notebook in Fabric |
Observer | reads build/DQ outcomes |
Reconciler | gold reconciliation against a spec |
ADOIntegrator | commit, tests, PR |
Architect, DeltaGenDeveloper, PluginDeveloper, Coordinator | design review, engine/plugin dev, orchestration |
Deterministic helpers handle the plumbing around them — workspace pooling, artefact upload, lakehouse SQL, reconciliation — so the agents only make the judgement calls.
How a table ships
A ticket names the table and layer. The mapping is parsed into a structured spec, the spec becomes declarative Delta-Gen YAML, the YAML is validated and executed as a notebook run in Fabric, data-quality tests compiled from the same YAML are run against the built table, and the result is committed, tested and raised as a pull request. Failures at any step route through the debug engineer's self-correction loop rather than aborting the run. Alternative workflows reuse the same agents for smaller jobs: a new-table fast path, bug fixes, and plugin development for the engine itself.