Let's market D: tell us how you're using it

[Laeeth Isharc via Digitalmars-d]

On Sunday, 3 April 2016 at 09:12:05 UTC, Joakim wrote:
> I though Laeeth had a good suggestion on how to market D a 
> couple months ago, as the current front-page pitch may be too 
> general for some chunk of readers:
>
> "A set of 'channels' for different use cases might be helpful.  
> Eg bioinformatics, numerical computing, web, etc.  Both for 
> tutorials and setting out the advantages."
>
> I'd organize it by adding a usage page to dlang.org with a list 
> of popular channels like that, with a paragraph of info for 
> each and links to the wiki with more info about use in that 
> field. The usage page would have some links from the front page 
> pitch.
>
> As such, we need to collect info on how you all are using D 
> now.  If you are using D in some field like that, please 
> describe what you're doing and we'll add it to the website.

Not exactly what I had in mind longer term (combination of shiny 
appealing thing that gets the idea across quickly would 
compliment grittier unpolished stories), but here is a start:


https://wiki.dlang.org/User_narratives_on_switching_to_D

When you're at the periphery for the time being, you have to give 
some thought to what your advantages are, what problems other 
people have, and how you can get them to see how you can solve 
it.  But of course first of all you may need them to help 
perceive and articulate that they have a problem - amidst the fog 
of life, that's not always as clear as it sounds when described 
after the fact by a writer like Michael Lewis (Big Short, Liar's 
Poker).

And I think given where D is its much more likely to be 
recognised as the right tool for many jobs by hearing how someone 
else - that's a real person not a symbol - had a problem that is 
kind of just like yours but was able to make use of this workshop 
(as Walter describes it) to ease their pain and do things that 
never were quite easy enough to tackle before.

You have to make the best of what you got.  People are very 
helpful here - its not just John Colvin rewriting someone's 
ported Python code, and Adam Ruppe solving someone else's obscure 
linking problem (by doing so he is responsible for what is likely 
D's first adoption by a hedge fund - Andy Smith's old shop) as 
well as 10 questions a day on irc.  On the other hand, people 
arent shy about describing what they don't like, and that's 
ultimately a positive because it means you have a community that 
is more concerned about quality than being agreeable for the sake 
of it. And, as Andrei says, be honest till it hurts, is a great 
way to move towards excellence.   From a marketing point of view 
then, it's better to make a clean breast also of the areas where 
D isn't where we would want it to be - yet.  By doing so it's 
then much easier to put things into proper context and shape the 
narrative.  When I started with the language it really wasn't 
clear to me that it was suitable for using in production, and if 
you read social media then you might still come away with that 
impression.  Clarity may be the best answer to fear,  
uncertainty, and doubt.

And delivering on what you say you will is a great way to build 
trust.  If you come to D thinking your python code when ported 
directly will automatically be 200x faster (I exaggerate for 
effect) then when it's only a few times as fast you will be 
disappointed.  So then its better to explain that, and why, and 
that for processing large amounts of data the GC isn't great, but 
at the same time you really don't need to make such a fuss about 
it - D is not Java, and its easy to avoid the major infelicities 
and here are some examples of what you can do.

Anyway, we aren't going to draw users by means of shiny marketing 
primarily.  The latter does matter because if you are in an 
organisation and take a social, political, and commercial disk by 
doing something different, then its much easier for you if others 
who check it out take a quick superficial look (because 
heuristics in the face of attention and time starvation), but you 
most of all want to appeal to the guys who want to believe anyway 
and just need to have some help in understanding that this can be 
the case.

People in similar lines of work often have similar problems.  So 
then its very interesting if you are doing finance or 
econometrics work to be shot instantly not just to Bachmeier's 
work (different things, but opening up R libraries is huge), but 
also to hear in practical concrete terms what he uses it for and 
what the benefit is.

Similarly if rapid prototyping is important - which ought to be 
the case for many - then Walter's Worp experience is very 
powerful.  Yes,it's the language creator who is also a very good, 
performance oriented programmer (and would he have achieved a 
comparable speedup had he been working in Perl ? ;) but a story 
doesn't need to be objectively indubitable even to a sceptical 
observer to get the point across.  You will find an account of 
that if you watch lots of YouTube videos or happen to stumble 
across the Wired article, but in general the people in 
organisations with the power to make decisions don't  - except at 
the very top - have so much time to do this.

If I recall correctly plasticity is mentioned on the front page, 
but it's not made super clear what that means and the benefits 
arent made vivid if you arent a!ready aware of them.  I don't 
think there is a link to a summary of Walter's mention of it in 
relation to the practical experience of developing Worp or 
Andrei's recapitulation of the experience - and no nice little 
summary that gets me interested enough to watch the whole talk.

Similarly there is no one place go learn about how people are 
using it in bioinformatics - there was even an academic paper on 
the benefits, but I don't think you would find that easily from 
the front page.  (The audience for the channels isnt limited to 
only people in that sector, as I guess if you process a lot of 
string data, probably you take  peek at what the bioinformatics 
guys are doing).  And how many prominent clicks does it take to 
go from the front page to an understanding of who Sociomantic 
are, what they do, at what scale, and how much they save vs their 
competitors by using D rather than the alternatives.  Or again, 
AdRoll is a python shop - they have given talks about their use 
of python at scale.  But their data scientists use D.  That's 
funny - Guido says python is fast enough.  Why do they use a 
language with a smaller ecosystem and worse tooling than the 
obvious alternatives ?  What has been their experience in 
practice, warts and all ?  Maybe they don't want to talk about 
it, but has someone approached them and asked if they would like 
to ?  I would do it myself - I did write some wiki  content, but 
I just don't have the time, and will try to help longer term in 
other ways.  But it wouldn't take much work to make some progress 
- so much low hanging fruit, and initially its perhaps more about 
creativity and coming up with a plan than it is sheer grind work.

Beginnings are often modest, and one doesn't need to drink the 
ocean in one gulp - just working away at it will work wonders, I 
think.

Laeeth.