Skip to main content

Breeding lazy developers...

Andy Kramek asked back on February 19th (I've been badly missing my reading and Alex pointed me to it - since he's first on my alphabetical listing of Fox bloggers)

Are on-line technical forums breeding lazy developers

The discussion (found in the comments) is a good one but what it also illustrates is a lack of resources or pointing to resources about how to get started in certain issues. As our development environments get larger and more features, it's hard to know where to start. In addition, the help files are often written to say "here's what this does", not "how to do it". I fully agree with Andy's issue about using CREATE CURSOR from ARRAY. That's just crazy. But for those who are posting "How do I create this...", these should be used as great fodder for the various How To sites and I think everyone should be linking to them.

For example, Craig Boyd's posts about learning Visual FoxPro

Craig Bailey's Screencasts on the same

The great VFP Seminar series from VisionPace

I'm sure there are some more - but while developers may seem lazy when they don't RTFM or google for examples, it's also the case that searching between 12,000 articles in Google can be hard to separate the wheat from the chaff. Asking the "forums" may be a way of trying to filter it down.

I'm not saying anyone should be writing the code for anyone - but pointing them to places where they can find basic introductions is a great way to redirect them. Maybe every forum should have pinned topics that say "Before you post a "how do I" topic, go here first"


powered by performancing firefox

Comments

Popular posts from this blog

Elevating Project Specifications with Three Insightful ChatGPT Prompts

For developers and testers, ChatGPT, the freely accessible tool from OpenAI, is game-changing. If you want to learn a new programming language, ask for samples or have it convert your existing code. This can be done in Visual Studio Code (using GitHub CoPilot) or directly in the ChatGPT app or web site.  If you’re a tester, ChatGPT can write a test spec or actual test code (if you use Jest or Cypress) based on existing code, copied and pasted into the input area. But ChatGPT can be of huge value for analysts (whether system or business) who need to validate their needs. There’s often a disconnect between developers and analysts. Analysts complain that developers don’t build what they asked for or ask too many questions. Developers complain that analysts haven’t thought of obvious things. In these situations, ChatGPT can be a great intermediary. At its worst, it forces you to think about and then discount obvious issues. At best, it clarifies the needs into documented requirements. ...

Respect

Respect is something humans give to each other through personal connection. It’s the bond that forms when we recognize something—or someone—as significant, relatable, or worthy of care. This connection doesn’t have to be limited to people. There was an  article  recently that described the differing attitudes towards AI tools such as ChatGPT and Google Gemini (formerly Bard). Some people treat them like a standard search while others form a sort of personal relationship — being courteous, saying “please” and “thank you”. Occasionally, people share extra details unrelated to their question, like, ‘I’m going to a wedding. What flower goes well with a tuxedo?’ Does an AI “care” how you respond to it? Of course not — it reflects the patterns it’s trained on. Yet our interaction shapes how these tools evolve, and that influence is something we should take seriously. Most of us have all expressed frustration when an AI “hallucinates”. Real or not, the larger issue is that we have hi...

When A Machine Starts To Care

“Any sufficiently advanced technology is indistinguishable from magic.” Arthur C. Clarke (1962)  I first used that quote when I was starting out in the tech industry. Back then, it was a way to illustrate just how fast and powerful computers had become. Querying large datasets in seconds felt magical—at least to those who didn’t build them.  Today, we’re facing something even more extraordinary. Large Language Models (LLMs) can now carry on conversations that approach human-level fluency. Clarke’s quote applies again. And just as importantly, many researchers argue that LLMs meet—or at least brush up against—the criteria of the Turing Test.  We tend to criticize LLMs for their “hallucinations,” their sometimes-confident inaccuracies. But let’s be honest: we also complain when our friends misremember facts or recount things inaccurately. This doesn’t excuse LLMs—it simply highlights that the behavior isn’t entirely alien. In some ways, it mirrors our own cognitive limits....