Practical notes on AI engineering, software delivery, and system design.
A place for implementation notes, architecture trade-offs, and write-ups about tools, models, and shipping real systems.
Latest articles
How I move an AI demo toward production
The practical steps behind turning a prompt-driven prototype into something maintainable, observable, and safe to ship.
Open articleChoosing an AI stack without overengineering it
A compact framework for picking providers, orchestration tools, and hosting without adding unnecessary complexity.
Open articleGuardrails I use when AI touches a real product
A privacy-safe look at evaluation points, constraints, and review gates that keep AI behavior predictable.
Open articleAI topics
AI engineering
LLM integration, prompt design, evaluation, and the delivery concerns that show up in production.
Software delivery
CI/CD, release discipline, observability, and practical habits for stable iteration.
Cloud and platform
Architecture trade-offs, service composition, and reliable platform choices.
Safety and quality
Guardrails, testing, and controls that help AI-enabled systems behave predictably.