The hardest part of building software is not coding, it's requirements
Why replacing programmers with AI won’t be so easy.
Why replacing programmers with AI won’t be so easy.
Developers love automating solutions to their problems, and with the rise of generative AI, this concept is likely to be applied to both the creation, maintenance, and the improvement of code at an entirely new level.
Everyone who says "tech debt" assumes they know what we’re all talking about, but their individual definitions differ quite a bit.
Is there a connection between programming and ADHD? And could it be that people with ADHD are particularly well-suited to programming careers?
With all the advancements in software development, apps could be much better. Why aren't they?
What matters isn’t just whether you use it, but how.
Plenty of workers prefer flexibility, regardless of what the research says.
Text embeddings are key to LLMs and convert text into vector coordinates.
A business wouldn’t take its product development for granted, so why would you neglect the OSS community that’s fundamental to the project’s very existence?
AI systems obey the golden rule: garbage in, garbage out, Want good results, feed it good data.
The opportunities for edge computing are huge—but so are the memory requirements.
Both new talent and late-career developers are more likely to be looking.
The core challenge posed by generative AI right now is that unlike conventional applications, LLMs have no “delete” button.
Retrieval augmented generation (RAG) is a strategy that helps address both LLM hallucinations and out-of-date training data.
Being an effective coder with a code generation tool still requires you to be an effective coder without one.
For AI tools to be useful to your team, they have to fit into your existing workflows.
If we can make operational data easier to manage and easier to access through simple, standardized APIs, everyone can transform their companies into sustainable data-driven organizations.
What exactly is a vector database? And how does it relate to generative AI?
Highlighting one of the interesting discussions going on in our Collectives.
Go behind the scenes to learn how we designed our new search.
Semantic search and augmenting LLMs have sent everyone turning their text into vectors. But where do you store all that vector data?
The conventional metaphor for career success is a ladder, but there are a lot of problems with this narrative.
Stack Overflow for Teams' journey to the cloud started with a new name.
If you want the tech debt metaphor to really shine, get some numbers behind it.