When setting up an experiment is complex, agents can automate the process to make it faster and more reliable.

Agentic systems have some discretion in the parameters they sent to tooling, but there are cases, such as experimentation, when you need 100% adherence to a set of parameters.

This post advocates for a simplifying a complex network of states into simple states that correlate with user expectations.

This post shows using Azure Container Instances for job processing such as data generation and ingestion.

This post will discuss multiple use-cases for Azure Event Hub that hopefully help you think about how to get creative in your own solutions.

Our team used AI tools to write code, documentation, indexes, etc. extensively during our last engagement. This post will talk about what we used and how we used it.