Dan Shiebler

I’ve spent a lot of time leading large and small engineering teams over the last decade. Through this experince I’ve developed some opinions about what good leadership looks like. My central leadership tenets are: Set a Strategy Do Row-Level Inspection Set Clear Expectations Give Frequent Feedback Let Builders Build Set... [Read More]

Generative large language models (LLMs) like ChatGPT are like wild beasts. They are powerful but difficult to tame. One formidable challenge lies in the cost and latency associated with these models. Compared to traditional software solutions, LLMs can operate at a slower pace, incurring higher costs along the way. Instead... [Read More]

Generative large language models (LLMs) like ChatGPT will revolutionize the way we approach complex problems. Enormous amounts of custom labeled data are no longer required to train many specialized AI systems. LLMs make generalized problem-solving capabilities vastly more accessible. This has profound implications for software development, data science, and machine... [Read More]

ML models are collaboration bottlenecks. Suppose your team owns a binary classification model, and you have decided that increasing this model’s recall without reducing precision is very important for the business. You’ve put 5-10 engineers on the job. The Problem What should these engineers do? There are many ways to... [Read More]

One of the hallmarks of a great engineer is the ability to execute. An engineer who can execute gets things done. They crush tickets, pump out designs, spin up features, answer critical data questions, improve models, and prototype new ideas quicker than their peers. How to Execute Engineering projects are... [Read More]