Cloud + Prompt Engineering
Engineer-leveled prompts for designing and implementing complex cloud architectures — focused on Azure, the Python SDK, and production data platform work. Series 1 is in preparation.
Series 1 is in preparation. These packages are planned — prompts are not available yet.
Design complex cloud systems before writing code
Frames a full architecture pass — requirements, constraints, service selection, failure modes, and implementation sequencing for Azure workloads.
Use whenGreenfield platform design, migration planning, or architecture review before sprint work.
Generate typed, production-ready SDK integration code
Produces Azure SDK Python modules with auth, error handling, retries, logging, and test hooks — not tutorial snippets.
Use whenBootstrapping service integrations for Blob, Data Factory, Key Vault, or Resource Manager.
Design Azure Data Factory pipelines with operational rigor
Packages prompts for linked services, datasets, pipeline DAGs, triggers, and observability for ADF-centric data engineering.
Use whenBuilding or refactoring ADF pipelines for batch ingestion, transformation, or lakehouse loads.
Meta-prompts that improve your architecture prompts
Engineer-leveled templates for refining, decomposing, and stress-testing cloud design prompts before handing them to an LLM.
Use whenImproving prompt quality, splitting large architecture asks, or adding verification loops.