- Published
- Author
Amit
ncalTILs - Fueling Curiosity, One Insight at a Time
At Codemancers, we believe every day is an opportunity to grow. This section is where our team shares bite-sized discoveries, technical breakthroughs and fascinating nuggets of wisdom we've stumbled upon in our work.
- Published
- Author
- Amit
ncal
- Published
- Author
- Goromlagche
do not modify instance variables of a singleton class, not thread safe. furthermore no instance variables, only class variables.
- Published
- Author
- Iffyuva
Parameterize specs for fun https://github.com/HypothesisWorks/hypothesis
- Published
- Author
- Iffyuva
http://privacy.cis.upenn.edu/ - How to improve data sharing with privacy in mind.
- Published
- Author
- Atul
Kubernetes jobs can be configured with
ttlSecondsAfterFinished to clean up finished jobs automatically. - https://kubernetes.io/docs/concepts/workloads/controllers/jobs-run-to-completion/#clean-up-finished-jobs-automatically- Published
- Author
- Goromlagche
a small elisp snippet to generate class name for ruby files. can be modified for other langs too
https://gist.github.com/goromlagche/0c53ef2cbee35a14dee34e9029c71116
https://gist.github.com/goromlagche/0c53ef2cbee35a14dee34e9029c71116
- Published
- Author
- Iffyuva
https://github.com/sosedoff/pgweb : A great way to connect to postgres without opening port 5432 to general public.
We can even add this to Dockup, and boom everyone has access to postgres container and can fiddle directly
We can even add this to Dockup, and boom everyone has access to postgres container and can fiddle directly
Showing page 58 of 83
Your competitors are already using AI.
The question is how fast you want to unlock the value.
Don't know where to start?
AI is everywhere but it's unclear which investments will actually move your metrics and which are expensive experiments.
Your data isn't ready
Most AI projects fail at the data layer. Pipelines, quality, access all need work before LLMs can deliver value.
Internal teams are stretched
Your engineers are shipping product. They don't have capacity to also become AI specialists with production-grade experience.
Legacy systems block everything
Aging, undocumented codebases make AI integration slow, risky, and expensive. They need to move first.