I’ve built a mock application using AI with dummy data, but I’m now stuck on how to turn it into a production-grade application. I’m looking for guidance on the steps, best practices, or key areas I should focus on to make it ready for real-world use. Any help would be appreciated.
I keep seeing ads for Weave, an 'AI-powered engineering intelligence' platform that claims to measure 'normalized units of work' and separate human vs AI contributions.
This sounds like an absolute nightmare for engineering culture. Normalizing work into a single metric is exactly how you get developers to optimize for the metric instead of building good software. It feels like the ultimate surveillance tool disguised as 'AI insights'. Does anyone actually use this? Does it do anything other than erode trust between management and ICs by tracking every single move?
Our org rolled out GetDX a few quarters ago to measure 'developer experience'. At first, it seemed okay, but now the survey fatigue is real. We are constantly being asked to fill out qualitative surveys, and honestly, people are just clicking through them to get back to work, which makes the data completely unreliable.
Also, since Atlassian acquired them, I am really worried about vendor lock-in and future pricing changes. The telemetry data they pull also seems to struggle with our more complex, heterogeneous enterprise systems. Are there alternatives that do not rely so heavily on constant developer surveys to figure out what is blocking us?