APIs and deployment · practised
APIs and deployment
Turning AI workflows into deployable Python services and APIs with clear contracts, container boundaries, cloud delivery, and operational fallbacks.
Austin works with Python, Flask, FastAPI, Docker, REST APIs, service integration, cloud deployment, and rapid prototyping.
Public evidence includes the separately deployed AI Austin service and the static-first site architecture that isolates dynamic workloads behind Cloud Run.
Evidence relationships
Where this practice shows up.
An anonymized enterprise service using Google ADK and Google AI capabilities to search, generate, and process icons against internal design guidance.
Project · activeEnterprise image-generation platformAn anonymized enterprise case study in turning Google Imagen generation and editing capabilities into a globally adopted creative workflow.
Project · completeLLM SEO and RAG servicesTwo enterprise proofs of concept exploring governed content generation, webpage auditing, quality scoring, and BigQuery-powered retrieval.
NoteGiving a 2017 MacBook Pro a Second Life with OmarchyHow I turned an almost-decade-old Touch Bar MacBook into a lightweight Linux and AI-development machine—and what the first installation taught me about EFI, hardware dependencies, and using the computer you already own.