https://ianarawjo.medium.com/what-ai-engineers-can-learn-from-qualitative-research-methods-in-hci-5b29b9b7465a What AI engineers can learn from qualitative research methods in HCIIan ArawjoJan 9, 2025 “Meet inductive coding and grounded theory, the new bread-and-butter of LLMOps”
What I Read: Data Pipeline Smoke Tests
https://dagster.io/blog/smoke-test-data-pipeline The Unreasonable Effectiveness of Data Pipeline Smoke TestsSandy RyzaOctober 19, 2022 “Data practitioners waste time writing unit tests to catch bugs they could have caught with smoke tests.”
What I Read: Data Observability vs. Data Testing
https://towardsdatascience.com/data-observability-vs-data-testing-everything-you-need-to-know-6f3d7193b388?gi=6618bd7121fd Data Observability vs. Data Testing: Everything You Need to KnowYou already test your data. Do you need data observability, too?Lior GavishFeb 12 “In any data system, there are two
What I Read: Building Robust Machine Learning Systems
https://medium.com/swlh/deepminds-three-pillars-for-building-robust-machine-learning-systems-a9679e56250a DeepMind’s Three Pillars for Building Robust Machine Learning SystemsSpecification Testing, Robust Training and Formal Verification are three elements that the AI powerhouse believe hold the essence of robust machine