"we did data analysis with Python, NLTK and R. The stack is on EC2 running Django with memcached and varnish serving up json and the frontend uses jQuery, underscore and backbone to render it"
We performed the data analysis using a combination of dynamic programming languages and synergistic components, running on a high availability multi tiered substrate framework while simultaneously utilizing a web space language to deliver content rich user content.
Nice reformulation. It would be right in some contexts ... but, to me (and I am not a programmer by trade nor do I work in the field), the original quote is explicit enough that I would trust the person saying it to know what they are talking about, whereas your reformulation would, in many contexts, sounds like what someone would say when they really have no clue (think "pointed-haired" boss).
Not knowing the meaning of the first formulation, I can still safely say that it was produced by someone who knows precisely what he's talking about. That breeds confidence.
The latter sounds like wall-to-wall bullshit. Not to say that the words don't have meaning, just that they're parked in that infuriating zone favored by people who would generally prefer that you didn't actually understand what they were saying.
If all this represents an especially clever or elegant solution, wonderful - talk about that in a way that makes the elegance clear. Or provide the hard information that the first formulation conveys, so that a trusted advisor can evaluate it. Just don't slip into the bullshit zone. Not if you want to maintain goodwill, trust, and confidence.
And for what it's worth, smart humans are very good at detecting the difference between actual technicalities, and bullshit. It's got little to do with the domain. It's got a lot to do with the demeanor and tone of the person speaking.
The first formulation makes me want to hire the guy. The second makes me want to fire the guy.
I'm not sure how you can "safely say ... [he] knows precisely what he's talking about" while admitting "not knowing the meaning." I think perceiving it as "breeding confidence" is precisely the reason why many business situations where experts' actions must be managed/approved by non-experts result in a flood of impressive-sounding jargon.
The deluge of specificity creates a posture of expertise; however,without knowing what the specifics mean you can't possibly evaluate it for truth. There are many equally impressively structured but semantically ridiculous statements, such as "We host our servers on NLTK, serving up EC2 to a browser frontend running varnish and memcached."
It's more subtle than that. Looking past the technical terms, the first formulation is very distilled, and cites a specific action. It's an elegant expression. The second one uses fluffery like "performed" instead of "did". And that's what sets off the BS detector.
Why do you perceive statement #1 to be factual?
If you have no domain expertise, you have no way to evaluate it. _DPS's example sounds -identical- to someone without domain knowledge, and yet is comically absurd.
But that example goes well beyond meaningless buzzword boasting into flat-out lying. This is a bit of a different problem and it's a lot easier to fact check factual statements, with or without domain knowledge.
It's almost a shibboleth, these reverse abstractions into understandable English. The more I hear someone jargon it up, the more I think they don't understand what they're talking about. "I like big data!"
And what is "content-rich content" anyway? The "translation" is still meaningless without domain-knowledge, but is now far less factual. I guess the content is now less content-rich!
If I read that without having read the original my eyes would glaze over with buzzword overload. So much lost information in the "generic" (or more correctly, vague) form. This is the sort of stuff I'd expect in a sales pitch, where I'm barely any better informed after having heard it, even for someone with domain knowledge in the area.
The original however is packed with specifics, most of which can be looked up if you're unfamiliar with (for instance I had no idea what NLTK was, but a single google search informs me it's a toolkit for natural language processing). They're not buzzwords, they're product names. It's clear and concise to someone with the domain knowledge.
We performed the data analysis using a combination of dynamic programming languages and synergistic components, running on a high availability multi tiered substrate framework while simultaneously utilizing a web space language to deliver content rich user content.