#subprocess-measurement

#subprocess-measurement

Generative AI is dissolving the economic logic that made standardized enterprise software the only practical choice for most companies. What replaces it will be shaped not just by the rapidly evolving capabilities of this new technology, but by leaders willing to ask a harder question: Which workflows do we actually need to own?

As agentic adoption of GitHub CLI grows, our team needs visibility into how features are being used in practice. We use this data to prioritize our work and evaluate whether features are meeting real user needs.

"The CPU number in Task Manager is a moving little obituary for the immediate past," explained former Microsoft engineer Dave Plummer, "Not what happened at the moment that your eyeballs landed on the row."

In the fintech industry we can link latency directly to profit and money. If I have lower latency than the competition, I can get to the better deals, I can make the better deals.

Which Algorithm Is This? If you step back, this maps almost perfectly to the Top K Frequent Elements problem.We usually solve it for integers in a list. Here, the "elements" are audience profiles age and body-type combinations. First, define what an audience profile looks like: case class Profile(age: Int, height: Int, weight: Int) What we want is a function like this:

One thing I always do when I prompt a coding agent is to tell it to ask me any questions that it might have about what I've asked it to do. (I need to add this to my default system prompt...) And, holy mackerel, if it doesn't ask good questions. It almost always asks me things that I should have thought of myself.

Manual database deployment means longer release times. Database specialists have to spend several working days prior to release writing and testing scripts which in itself leads to prolonged deployment cycles and less time for testing. As a result, applications are not released on time and customers are not receiving the latest updates and bug fixes. Manual work inevitably results in errors, which cause problems and bottlenecks.