
Ask HN: With such fast changes in technology, how do you update your skillset? - ak93
AI&#x2F;VR and slowly lot more. I am getting quite anxious if my skillset might go obsolete.
======
pjc50
To be honest, it isn't and I don't.

That sounds rather blunt, but most organisations _that aren 't startups_ don't
change technology quickly if at all. C++ has served me well for two decades; I
probably ought to adopt C++14 but on the other hand my current job requires
that the codebase build with a 2008 compiler.

I'm also extremely skeptical of the extent to which AI and VR are _new_ , as
opposed to incremental improvements to technology which takes it over an
adoption barrier. Have you seen the 80s VR headsets? SHRDLU? The "AI winter"?

If you're worried about this stuff then it's helpful to develop a level of
knowledge about it that's slightly higher than _Wired_ but lower than actual
implementation detail, in order to talk about it in interviews. You can then
pick this stuff up as you go. Machine learning in particular is maths-heavy,
matrix algebra in particular, and _that_ 's never going to go obsolete.

I also agree with the commentators who are saying that you should ignore the
latest flash-in-the-pan frameworks unless you really have to to get frontend
gigs.

~~~
riprowan
I completely agree with you.

I started in this field in 1992. I've seen the coming and goings of many
flash-in-the-pan technologies.

If you are a dev and are selling yourself on your skillset, ask yourself, "is
this sustainable?" The answer is "no." A fifty-year-old brain simply does not
absorb new technologies as fast as a 25-year-old-brain. If your plan is to
continually adopt new cutting edge technologies in order to stay marketable, I
politely submit you need to rethink your long term plan.

As an almost 50-year-old, I promise you that the world is not a gentle place
for older devs. Plan your exit into management, a related field, or some other
job altogether. If you expect to be a coder at age 50 you're going to be
disappointed.

As for me, I jettisoned the "technical skill set" war decades ago. I do not
sell myself on my technical skill set. I sell myself as the ultimate
generalist. This comes with its own set of problems. However, it has allowed
me to age more gracefully in my field, because I do not create the expectation
that my primary value-added is code generation.

~~~
jballanc
> Plan your exit into management, a related field, or some other job
> altogether. If you expect to be a coder at age 50 you're going to be
> disappointed.

I'd like to simultaneously disagree and agree with you. If you were a 50 year
old coder 10 years ago, then your only hope of remaining in the tech industry
would be to add "Manager" to your job title. If you are a 50 year old coder
today, that's still a sound direction to go, but increasingly becoming less
necessary. If you'll be a 50 year old coder 10 years from now...I think you'll
be ok.

Yes, at 50 you almost certainly cannot crank out as much code as you can at
20, but so what? As a coder it is important to understand that most problems
in technology are _not_ solved with more code, but less. That you will
generate less code at 50 should be seen as a benefit. The advantage you have
at 50 over someone who is fresh and new at 20 is that you can recognize that
there is very little that's happened in the last 30 years that is _genuinely_
new.

So, if you are 20, go ahead and spend your weekends on side projects learning
the latest frameworks. As you continue to do this over the years and decades,
shift to focusing more on patterns. By the time you reach 50, you might only
generate half as much code as your younger colleagues, but you should be able
to solve problems with a quarter of the code required, still making you twice
as efficient as them.

When coding was new, code was the only metric by which to measure coders, and
non-technical management types would view anyone who generated less code as
less valuable. If you're not writing 500 lines of code a day, the argument
goes, then you should be managing coders who can. But management and problem
solving are not a completely overlapping skill set. Some engineers make good
managers, but most do not.

Luckily, the more technically inclined individuals that populate the ranks of
company management, the more this is being recognized and the more these
companies are willing to hire the 50-year-old-coder-who-codes-less-but-solves-
more-problems.

~~~
bsenftner
I'm seeing a lot of mythic stereotypes here. I am a 52 year old full time
coder, and have been actively developing since taking a college pascal class
at age 11.

> If you were a 50 year old coder 10 years ago, then your only hope of
> remaining in the tech industry would be to add "Manager" to your job title.

People outside the startup bubble value delivering, regardless of age.
Developers outside the startup bubble work consistently in a few areas of
technology, they develop deep personal understandings with cookbook / solution
/ frameworks they personally authored enabling them to construct stable
solutions that expertly address the problems being addressed.

Essentially, if you remain a "coder" and you use your brain at all above
simply being a coder, you will become a software scientist. I never start
anything from scratch, as I have about a dozen application skeletons ready for
various specific purposes, plus similar libraries I wrote, plus a knowledge of
several large commercial SDKs, and developer experience in several major FOSS
applications. The work that I do now would give my 20 or 30 year old self a
heart attack with the large scope, number of complex technologies, and the
time frame I'm expected to deliver. But I've been writing code for 40 years
now, and I may bitch at my tools, but it will deliver, it will be well
written, fully documented, and so on because anything less just creates
technical debt.

If you like writing code, start acting like a scientist about it. Few
developers do, and in time you will accelerate away from your peers into a
truly enjoyable professional space very few seem to occupy.

~~~
morbidhawk
> I never start anything from scratch, as I have about a dozen application
> skeletons ready for various specific purposes, plus similar libraries I
> wrote, plus a knowledge of several large commercial SDKs, and developer
> experience in several major FOSS applications

I've had a project manager (very insightful guy) tell me something similar
before. He said "as you get more experienced you'll (ideally) write less code
and instead reuse code from libraries you've written in the past". I've always
wondered how that works for someone? I'm assuming certain projects will have
requirements where specific technologies would be used in the front-end and
persistent layers depending on the kind of project you are building and so
those wouldn't be as reusable but perhaps algorithms you've written before
might be reusable on the computational side of things. Like perhaps if you had
a library that handles very advanced moving cost calculations you could
ideally use that same library in different software forms (mobile, web,
desktop, command-line).

Edit: Git might be a good example of a library that can be reused a lot and
used within many kinds of applications (IE: inside web app, within IDE, from
command-line, desktop app, etc)

~~~
webmaven
Git is not a library, it's a program. There are, of course, libraries in many
languages for using git[0] from within many other kinds of applications.

Another example of a library would be libjpeg[1] for reading and writing the
jpeg image format and dealing with all the different ways the format can be
adjusted, which gets incorporated into many applications, for example
ImageMagick[2].

Basically, a library consists of code that is intended to be reused by calling
it from other code.

[0] It's astonishing how often this gets reinvented. Here are just Python
libraries:
[https://pypi.python.org/pypi?%3Aaction=search&term=git](https://pypi.python.org/pypi?%3Aaction=search&term=git)

[1]
[https://en.wikipedia.org/wiki/Libjpeg](https://en.wikipedia.org/wiki/Libjpeg)

[2]
[https://en.wikipedia.org/wiki/ImageMagick](https://en.wikipedia.org/wiki/ImageMagick)

~~~
morbidhawk
> It's astonishing how often this gets reinvented

Wow, I'd only heard of libgit2 before. I can't believe how many git-related
python packages there are. Yes git isn't a library, it's a program like you
said, good catch

------
throwaway6845
It may not be in the spirit of HN, but deliberately being 3 years behind on
the latest technologies is a really good way to stay employable without
driving yourself mad keeping up with the latest and greatest. After 3 years,
the flash-in-the-pans and the duds have been winnowed out and you can just
concentrate on the stuff which will earn you paying gigs.

~~~
oblib
I agree with that. I don't think it's counter to the spirit of HN. I build
apps for clients with the tools I know I'm proficient with but I play and hack
a lot too. Sometimes that leads to use with client software though more often
it doesn't, but learning is always good.

------
DanielBMarkham
Learn patterns and pop up the abstraction level.

There are only a few patterns in programming: imperative, OO, functional, etc.
Learn those.

There are only a few abstraction levels in problem solving: meta, business,
system, physical. Learn those.

There are only a few types of patterns in ML and Big Data. Looks like it's
time to learn those.

But the principle is the same. Learn the patterns of various _forms_ of
solutions, not actual languages or tech (they'll be required, of course, but
they're only a prop). Be able to move between these various patterns. Then
deep dive from time to time on various projects in each area.

We've passed the point where a person could keep up long ago. Now it's simply
about being both broad and deep at the same time. T-shaped people. If you want
to make a lot of money you can be that one guy who knows everything about some
tiny point -- but you'd better hope that point doesn't become obsolete in ten
or twenty years. I've seen this happen far too often in tech.

~~~
rubicon33
I've wrestled with this question virtually since the day I began coding
professionally:

Should I become an expert at one language/domain, or, should I constantly
learn new things and change roles?

I've done the latter, and I don't know yet if it will have been worth while. I
worry about being a "jack of all trades, master of none". Yet, as you point
out, a master of one trade had better hope it doesn't become obsolete in their
life time.

So my hope is that the investment in learning, and adapting, will pay off in
the long haul. I can write an iOS app, I can write an android app, I can code
a backend server in scala + akka, or I can write a backend server in PHP. Can
I do these things as well or as quickly as a master in each domain? Certainly
not.

~~~
d0m
You say "or" but it can be "and". Best is to be an expert in one, "and" having
a jack of all trades experience. I.e. you can specialize in front-end work
with framework X, but doesn't mean you can't have experience with optimizing
db queries. I think a big part of how to do that is just to stay curious and
learn new things for the fun, while having a go to language to get things done
efficiently.

~~~
webmaven
_> You say "or" but it can be "and". Best is to be an expert in one, "and"
having a jack of all trades experience._

Whether that is possible depends on the definition of "mastery" that you use,
and how broadly you construe "all".

TL/DR: Even generalists have become much more specialized over time.

Consider that "web design" circa 1996 used to include project management, end-
to-end development, PR, search engine placement, graphic design, copy
writing/editing, information architecture, browser testing, server
administration, domain registration, email configuration, etcetera, etcetera.

Over the past two decades, these tasks and many more besides have swollen to
bursting, splitting into entire subdisciplines (some of which have endured,
others not so much) and in some cases re-merging into new hybrids.

There is no way for anyone to maintain more than passing familiarity, much
less competency, with _every_ aspect of building and launching a non-trivial
website (much less a web application). At best, we'll wing it on personal
projects, or even skip major .

These days, what passes for a generalist is the "full-stack developer", which
pretty much leaves off everything that doesn't have to do with code, or
outsources tasks like design to 3rd-party services (eg. Netlify), libraries
(eg. Bootstrap), themes, and so on.

I expect this trend to continue and even accelerate, so don't drive yourself
nuts trying to keep up with the developments across everything you do today. I
guarantee that whatever you consider to be the set of skills a generalist
should understand now, it will get narrower over time (but not shorter), and
we will have as many kinds of generalist as there are specialists today.

I am pretty sure that the "serverless" trend will lead to a new breed of
"middleware developer" that works on various sorts of smart caching proxies,
for example.

My advice is to try and be strategic in the things you _drop_ and no longer
keep up with, and keep the things that you _do_ maintain competencies in
adjacent to each other and to one or two main areas of expertise.

------
twelve40
Have to do side projects. In my past life, I was getting sucked into becoming
a very conservative tech stack lifer at a huge, all-encompassing company. Most
people that surrounded me, even the good, hard-working ones, were 9-5 and
expressed surprise and hostility to learning anything outside of the company
bubble. Then one day a new, more active guy joined our team and whipped up a
complete REST-based service in a week. My mind=blown. I quit for the startups,
and moved on to using dozens of different stacks since and never looked back.
The best, most educating moments typically happened outside of work, when you
combine the patterns and observations from work with a different stack or a
smart outsider friend who chimes in on your daily struggles from a surprising
different angle.

Another enlightening moment for me was when I was working on a hobby machine
learning project, and shared my design concerns with a brilliant but very much
non-ML coworker, and all of a sudden that coworker laid out the whole design
in a pretty convincing detail, like he's been doing this work for years. After
the initial shock from his seemingly birth-given ML skills, I noticed that he
simply takes a lot of good online classes and goes through all the top ML
material on the web in his spare time, even though it was irrelevant to his
tech focus at the time. Well guess what, two years later he got promoted and
he's making that sweet data science money, and guess where he would have been
if he only focused on his old day-to-day instead.

------
xiaoma
My current strategy has a bit of complexity and might take an entire blog post
to explain clearly. The high level view is this:

Skills vary both in how much the market values them and in their durability.
There's often a trade-off between these two characteristics. For example, half
a year's worth of study in a foreign language or pure math is only somewhat
valuable to the market but that value doesn't tend to decrease over the years.
Learning AngularJS in 2013, on the other hand, was so highly valued by the job
market that it was a great way for junior programmers with no degree to break
into a software engineering career.

I believe it's best to generally focus most learning efforts on durable
skills, but occasionally when there's an opening, to flop and focus 100% on an
ephemeral skill that's highly valued and appears likely to be even more highly
valued in the near future. After capitalizing on the opportunity, return to
mostly focusing on durable skills.

------
itamarst
A lot of the technology on the bleeding edge will be gone in a couple of
years. AngularJS v1 used to be the next big thing, now it's obsolete. Who
knows if v2 will stick around.

So following the latest technology in _detail_ is unnecessary. Far more useful
is just having a broad sense of what tools are available out there; it takes
less time, and it's more useful since it gives you access to a broader set of
tools on-demand.

Beyond technology, the things that persist are much more fundamental skills:

1\. Ability to read a new code base, and ability to quickly learn a new
technology.

If you can do this you don't need to worry about new technologies since you
can always learn them as needed. E.g I just wrote a patch for a Ruby project
(Sinatra) at work even though I don't really know Ruby and never saw the
codebase before. It got accepted, too.

2\. Ability to figure out what the _real_ problem is, what the _real_ business
goal is. This makes you a really valuable employee.

Technology is just a tool. More fundamental skills are your real value.

More detailed write-up on how to keep up without giving up your life:
[https://codewithoutrules.com/2017/01/11/your-job-is-not-
your...](https://codewithoutrules.com/2017/01/11/your-job-is-not-your-life/)

~~~
cableshaft
While Angular 1 might be 'obselete', there's still a lot of corporations out
there with tons of Angular 1 code, and most of them are not going to be
upgrading anytime soon. Angular 2 is enough of a paradigm shift that it would
require rewriting those apps from scratch, pretty much, and there won't be a
business need to do so for another 5+ years for a lot of these companies.

We're still doing new apps in Angular 1 here, because everyone knows it, we
can reuse more code, we know most of its quirks and how to squeeze performance
out of it, and we can get the apps out the door a lot faster. Eventually we
will have a new project where we decide to use something more current, though.

~~~
itamarst
The point is not that Angular 1 is bad somehow.

The point is that trying to keep up with _all_ bleeding edge technology is a
waste of time, because it's constantly being replaced.

While at the same time you need to learn whatever technology you use at work,
which may _not_ be the latest-and-greatest.

------
Applejinx
Depends. I'm shepherding
[http://www.airwindows.com/](http://www.airwindows.com/) through a switch to
Patreon, by expressing new DSP ideas in a context of very, very old audio
plugin frameworks. The dev tools I'm using won't even work on current
computers. I code on a time capsule laptop and depend on the very simplified
plugin formats I've chosen (generic interface AU and VST) to remain
functional. They'd have to break the most fundamental interfaces to kill my
stuff (which doesn't make it impossible to do, just very user-hostile)

Don't confuse advances in technology with intentional churn generated by
vendors and platforms. The latter is a plague, and it doesn't only cost people
money, it costs them productivity. You may be getting confused and mistaking
skillset for toolset. Large companies will always be able to replace your
toolset and demand you learn a whole new one, because the more you do, the
more you'll be locked in to their toolset. If you can abstract out the
functions being implemented and express them in different ways, you can take
your skillset different places.

Whether you do that, depends on how good you are at finding niche markets. As
someone who's stayed in business for ten years selling GUI-less audio plugins
with no advertising and no DRM of any sort, I can tell you (1) niche markets
exist and they're loyal, and (2) they're small, which is what makes them
niche. :)

~~~
walterbell
_> Don't confuse advances in technology with intentional churn generated by
vendors and platforms. The latter is a plague, and it doesn't only cost people
money, it costs them productivity._

Do you think churn is intentional within a single vendor, e.g. to force
upgrades? Could churn be a by-product of competition between vendors, e.g. AWS
refactored most of enterprise computing into "low-end" services that steadily
improved, but were proprietary and increased lock-in.

 _> The dev tools I'm using won't even work on current computers. I code on a
time capsule laptop and depend on the very simplified plugin formats I've
chosen (generic interface AU and VST) to remain functional._

Is the time capsule laptop for old operating systems or old hardware? COuld
the old operating systems work in a virtual machine?

 _> They'd have to break the most fundamental interfaces to kill my stuff
(which doesn't make it impossible to do, just very user-hostile)_

Apple tried to get ride of files (!) entirely, but they are slowly making a
comeback on iOS, e.g. now you can insert an attachment within an email, with
the right application plugin. Social networks have done their best to replace
RSS push notifications with proprietary pubsub. WebDAV, CalDAV, CardDAV are
thankfully still supported by a few good apps.

 _> niche markets exist and they're loyal, and (2) they're small, which is
what makes them niche. _

How do you market your services/products within your niche?

~~~
Applejinx
Yes, I do. Forcing upgrades is just another way to force sales, and that's
competition. Churn happens.

The old laptop is just the most convenient sort of virtual machine. At some
point it'll be easier to run a virtual time capsule laptop… however, the
physical time capsule laptop is from a time before intense spyware, so there
are security issues as well.

As far as niches, Airwindows doesn't market at all. It's only word of mouth,
for ten years, with few exceptions (notably, Console2 got reviewed in Tape Op,
a trade magazine). This is personal: I loathe getting harassed by marketers so
much that I won't even email, much less advertise. I collected a list of the
'Kagi generation' customers who specifically said they wanted to be on a
mailing list and hear from me that way. And then I haven't emailed anything to
them for months and months :) So, effectively, my business is 'for people who
hate marketing so much that they want to do business with someone who will
absolutely leave them alone and not bug them'.

By definition this is a niche to starve in, but it's sincere. I really do hate
most everything about marketing, so I simply will not do it. Sometimes when I
have a notable post or product I leave out the patreon link on purpose :)

~~~
walterbell
Haha, new marketing category: product only available for purchase in a 24-hour
period that happens twice a year, or on a date decided by the roll of a dice
in a youtube video, or by solving a puzzle, or .. :)

~~~
Applejinx
But you're still saying 'purchase', and my market sector is completely
dominated by software piracy to the point where it's choking on sketchy and
unreliable DRM.

More like, 'new' marketing category: Trust Building Exercise. Attempt to give
everything possible away, and see if social pressure can cause a lot of people
to go 'yay!' and throw money. Hence the Patreon with literally no tiers above
1$, with at least half the patrons from 2$ to 10$ on their own volition.

The trouble with that (speaking as someone who has some notion of marketing
but chooses to undermine it) is, it's one of those power-law relationships
where basically you have to be me to do it :) without ten years of sorta
grassroots presence in the industry and a large number of successful products
that perform well as software, you can't do it. You can't simply start up and
have a Patreon work on those terms, even if your products are exactly as good,
and this is a problem.

Solving that would be a very big deal but it's a bit beyond me for now…

------
avip
3 steps program (specially crafted for the aged)

===============

0\. Assume any "new" thing is worse than the "old" alternative - until proven
otherwise.

1\. Critically filter out hype/PR.

2\. You're left with much less to learn.

3\. Invest "out-of-work" time in something really valuable.

~~~
d0m
Yep, totally agree. And I think the more experience you have, the easier it
gets to filter out the crap.

------
sapeien
It depends on what you already know, I think embedded development with systems
level languages and hardware know-how is a very durable skill.

On the other hand, some fields like web development have peaked a while ago, I
would argue that 2012 was the high watermark. I think it's a very precarious
choice of career right now. It has been steadily going downhill since the
introduction of trendy front-end frameworks that don't offer any value to the
end user (including React, Angular, et al). The culture stopped being about
making usable and accessible interfaces for people, and more about "component
architecture", "server-side rendering", "tree shaking", that solve problems
created by the very tools they are using.

That isn't to say that web development is dead, but I think that the future
will be more specialized around certain features of the platform such as
WebAssembly, WebRTC, WebGL, Web Audio, et al. And these will be more readily
picked up by people with more durable skills, than those who only know the
most popular front-end framework.

~~~
webmaven
_> The culture stopped being about making usable and accessible interfaces for
people, and more about "component architecture", "server-side rendering",
"tree shaking", that solve problems created by the very tools they are using._

Speaking as a confirmed cynic, that seems overly cynical. ;-)

The problems being solved by the web framework hamster wheel are those of
rising bars for usability and speed, with measurable in $$$ effects (ie. an
extra 1s delay could increase shopping-cart abandonment rate by 1.5%). Which
matters a lot more at web-scale.

So, these trendy frameworks are solving problems that most developers
shouldn't worry about (it is premature optimization) but that matter a great
deal to the companies that release them (Google: Angular and Polymer;
Facebook: React and Flux; etc.). OTOH, it is tempting to tap into of all the
engineering effort that goes into libraries like these. You just have to know
where to stop before sinking into the HammerFactoryFactory mire. ;-)

------
wheelerwj
Just like you have to fight feature creep in your products, you have to fight
"shiny new tool / language / framework" creep in your skillset. Become an
expert in your topic of choice and use the best tools to get it done quickly,
whether its 20 years old or two. If you spend too much time learning new tech,
you won't get it done quickly, but you shouldn't force an old tool to do
something just because you don't want to learn something new.

As for the anxiety, turn off HN every so often and just focus on being a good
engineer with your current tools. Nothing changes so fast that you can't go a
few months or even a year without being in the know. When it comes time to
stsrt a new project, spend a week researching the current tools and see how
they fit into your stack.

------
AnthonBerg
Understand the principles behind things. Most stuff is reinventing the wheels
of implementation of a much smaller base of theories.

------
krasicki
To give you some context, I'll answer this as a [largely] life-long
consultant. As such, I don't chase technology, I anticipate the trajectory of
job growth. I want the project that I decide to work on next to propel me to a
project that will likewise broaden and deepen the experience and skillset I
have to offer. <p>I also try not to get trapped into working for clients whose
only interest in my experience is to recreate one of the last things I did.
The easiest way to kill your value is to do the same thing over and over -
even twice is too much.

It's true technology progresses in dog years. When you are working you are not
learning outside that bubble. When you are between assignments you absolutely
must treat that time as a sabbatical to learn something/anything new.

By broadening your skillset through selective project engagement, you are
better off than Skippy who has worked on the same application with great job
security for 5 years - Skippy will not be someone you will re-encounter 10
years from now unless you are buying a used car and they happen to be the
sales person. The industry is self-selective this way. The complacent "I got
mine" mentality is toxic to longevity in the industry.

Let me also dispell the meme that sticking to a specialty is a desirable
thing. The fact of the matter is that the ocean of legacy code grows
exponentially and there is always a need for someone who knows a legacy
language or technology. this kind of career trajectory is as desirable as
cleaning out septic tanks. There's job security to be had and you'll hear
plenty of "Ho, ho, ho - I don't need no stinkin' new fangled whatever" to be
indispensible. My advice is not to be that guy/gal.

It is a much harder and a much richer experience to navigate a career in the
flow of technology than to get myopically paralyzed by a desire to featherbed
where you are today. But your question is "how" to keep up. IMO, the answer is
to skim lots of material and only dive in at the last most relevant moment.
The generalist is far more qualified that the specialist these days because
most companies cannot afford a prima donna - they need people who can perform
many jobs and serve many needs.

------
oelmekki
For me, the answer is side projects. I keep playing with new ideas, and use
new techs by the way.

It not only allows me to discover the tech, it's also especially important
because I refuse to make first contact with a tech by implementing it directly
in a production project meant to stay around for years. The most projects I've
used a new tech in before introducing it in my main project, the more
comfortable I am that I did not do gross mistakes.

For me, it's not the amount of time using a new tech that matters, it's the
amount of projects I used it in (because each time, I can try a different
architecture).

------
crdoconnor
I developed a checklist to spot technologies that are in an early stage of the
hype cycle and avoid them.

The following are signals that a technology is in and early part of the hype
cycle:

* It has the backing of a major corporation or a startup with a marketing budget.

* There are a lot of rave articles/blog posts about building relatively simple or small self contained applications using this technology.

* There is a small but vocal contingent of users who are passionately against the new technology. Their arguments often link to bugs on the bug tracker, cite edge cases that occur under heavy usage and indicate fundamental oversights in the design as well as assumptions (and often arrogance) on the part of the architects.

* The benefits cited are either A) vague or B) explicitly aimed at beginners.

* Arguments in favor often appeal to authority (e.g. "Google uses it" or "XYZ company use it in production"), popularity ("everybody's containerizing these days") or cite benefits which were already possible.

* A high ratio of talk to action: the technology is talked about on Hacker News a lot but there appears to be very little real life stuff developed with it and a lot of the talk involves jamming it in where it's not really necessary.

* Sometimes I experiment with a technology for an hour or two and I see if there's anything obviously wrong with it or if the criticisms are valid.

------
huherto
\- Be aware of new trends. You don't have to learn everything. But pickup and
try those that are promising to solve real problems in your current position.

\- You should be able to move back and forth between management and technical
positions. They are not mutually exclusive. You can a skill set that allows
you to do either. It gives you greater perspective and flexibility. One piece
of advice that I was given in college is that even if you are the Director of
IT you should leave small (non-critical) pieces of software for you to work
on. So you never lose touch.

\- Try to work for good companies. My definition of good companies are those
where you can be productive every day.

\- Some skills will be helpful all your life. I learned Unix in 1989 and have
used it almost every day.

\- Learn the fundamentals. Data structures, algorithms, relational theory,
structured programming, object oriented programming, functional programming,
networking, Operating systems, theory of computation, et al.

\- Understand the business domain in which you are working. That makes you
extra valuable for your current company.

\- Develop your soft skills. [http://www.skillsyouneed.com/general/soft-
skills.html](http://www.skillsyouneed.com/general/soft-skills.html)

------
jaibot
Focus on the fundamentals. How do you find the write tools and libraries? How
do you translate requirements into projects? How can you communicate with
other people effectively? How can you learn what you need to know when you
need to know it? How do you recognize sunk costs? What makes good code good
code, regardless of language? What compromises should you make, and when? How
do you ask the right questions?

------
swah
Learn to learn, and focus on your current client/task first instead of
technology. People still get paid to write Cobol.

------
mfukar
1\. Relevant skills don't change. Your abilities to reason on problems are
never becoming irrelevant.

2\. New technologies are adopted, doesn't mean old ones quickly disappear.
Sometimes not even slowly.

3\. Area focus. If my area of expertise is networking, what do I care about
VR? We can't be generalists any more than we could be 20 years ago.

4\. If you feel like being a generalist, understanding & internalising (basic)
principles is more important than being familiar with specific technologies

5\. Critical, transversal thinking. You can weed out heaps of new technologies
by understanding _how_ they fit in a system and the tradeoffs they require,
before you have to become intimately familiar with them. Base your approach on
tangible end-to-end measurements to understand how technologies might fit in a
system, and after that you'll have to keep up with a lot less than the various
FOTM

------
luisehk
Well, a critical eye is a must. Just keep away from the noise and pay
attention to what would really make an improvement on your current
framework/workflow.

For example, I still do my web development in Django or Flask because they do
the job, I'm pretty good at Python and most projects don't really need the
concurrency Go or Elixir offer.

One of the best recent additions to my skillset was Docker... a lot of people
say containers are not a must but they really made my life easier and allowed
me to do cool things for clients from different industries.

It doesn't sound as cool as doing machine learning, computer vision or natural
language processing, but don't let the AI/VR hype make you anxious, just focus
on what you really want to do.

------
drtse4
I'm more worried about people constantly believing that every new framework is
a major advancement for programming and that it's not just something that
could be learned in an afternoon (e.g. React). Or about people following the
latest hyped trend without learning anything and without producing much other
than more hype.

AI,ML and VR are all really interesting, but as we all know they are not
completely new and will not likely account for the majority of the future
jobs.

Fundamentals are what matter, most of these "new things" are just something
that you can learn with relatively limited effort if needed. Classic
programming skills, analytical skills or things like the ability to reason
about concurrency issues never go obsolete.

------
johanneskanybal
I learned the hard way about 10 years ago what happens when your current skill
set becomes obsolete, since then I've become very focused (and lucky) and only
take on really enjoyable and unique projects. That way it's easy to be exited
and do a good job during a project, communicate your passion in future
interviews and transfer that enthusiasm in your previous projects to potential
future employers.

The exact tech choices doesn't matter that much it's more of the overall
direction (in my case analytics, in a bunch of varied sub-fields).

Although the top comment has some merit I'd argue c/c++ is an outlier here
rather than the norm.

------
pseud0r
I learn new skills at the job, but at the same time I find that it's not
enough. What works best for me to really get into new areas and update my
skill set is to regularly take MOOCs and then try to find ways to use the new
skills at my job.

At the moment I'm taking this course in Deep Learning

[https://www.kadenze.com/courses/creative-applications-of-
dee...](https://www.kadenze.com/courses/creative-applications-of-deep-
learning-with-tensorflow/info)

------
raverbashing
Beware of those that make it more important to follow the latest trend than to
follow their business model (or that just go "what's a business model?!")

------
mbrodersen
A great quote from Lambert about what software development is:

1\. Decide what the program should do. 2\. Decide how the program should do
it. 3\. Implement these decisions in code.

Only the last part is actually coding.

In other words, as a software developer, you are _not_ paid to type. You are
paid to _think_. And the deeper your knowledge and experience, the better
tools you have to actually do that. So focus on learning step 1 and 2!

------
voycey
I think having a good core is more important than the "latest flashiest
framework" / "New Language" / "whatever" at the end of the day it will be your
experience that gets you out of the shit, not some new tool! However saying
that I think it is important to not let yourself go stale. I worked with a
company that had about 6 devs that were doing things seriously old school,
they had no interest in upgrading their skills and for someone who likes to
keep on top of the new features on languages it was painful to work with them.
In the end however, when they left that company they probably found pretty
quickly that they were unemployable!

For me personally, I find that I generally have free reign to test out "new
(to me) technologies and my experience helps me realise quickly if they are
going to be helpful or a bust!

Take any opportunity you can to do a "little project" in something that
interests you and then apply it to problems in your work!

------
oblib
Like pjc50, for the most part I don't. Last year was the exception.

I've been making web apps since 1998. Last year I learned how to use CouchDB
and PouchDB. Before that I used a flat file database and the built-in
filesystem to manage data. I used Perl on the backend with just a bit of JS on
the front end to run the apps.

I never did learn how to use MySQL/PHP. I looked at it, decided it was a butt
ugly way to make websites, and apps and admitted to myself that I wasn't
qualified to design secure SQL apps and didn't want to learn because that is a
career all by itself.

So I waited for something better to come along and last year CouchDB along
with PouchDB hit the mark so I spent the year learning and using them. It was
worth it. With those tools I am faster and better.

The years in-between were spent getting stuff done with the tools I was good
at using, not trying to learn how to use a zillion other tools to do the same
things.

I looked at a lot of newer tools again last year with an eye towards what was
"best". There is a lot of cool stuff out there that does some really jazzy
stuff, but in the end I decided to take another look at what was "easiest".

I ended up with CouchDB, PouchDB, and JQuery. Easy to learn and incredibly
rich APIs with lots of support and example code. There's more than enough in
those to learn and keep up with and if I need to add something I'll look for
easy ways to do that too.

The truth is, it takes time to be productive with any language or tool or
framework you use. It's a scatterbrained approach to try to build software
with something new every time you start a new job.

Right now there are tools being built that will make "AI/VR" easier to
implement. Wait for the tools.

------
Insanity
Well about the ones you have said in specific, AI/VR, I do not think they will
be a requirement for the majority of jobs in the software industry for quite
some time.

I believe that even though technology changes fast, the things you need to
change do not move as quickly but that probably depends on the company and
technology that company is using in the first place.

Where I am working, we are writing software mostly in Java, some analysis on
the data with Splunk and SQL for the database.

Sure enough I had to keep up with Java development but it is not _that_
rapidly. Nevermind the fact that the company only now is switching to Java 8.

That being said, I do like learning new things in the field but they are not
the "latest cool things", for example now I am learning Haskell by reading
books on it and doing excercises, the normal way to learn a new language
afaik.

I do tend to check out things that tickle my interest, lately I have made a
small app in Angular2/Dart because it sounded interesting, but by no means
have I learned to use them in-depth.

------
mbrodersen
Don't until you need to. If you are planning to leave your current job then
look at job offerings in the market and learn the tech needed to get one of
those jobs. And since the technology _underlying_ whatever tech is currently
fashionable hasn't changed the last 50 years, it will be relatively easy to
learn enough to get a job. The rest you learn on the job when solving specific
problems. I would _instead_ focus on learning the core tech that hasn't
changed for 50+ years. Including functional programming, logic programming,
how a computer fundamentally works (NAND gates) etc. What you learn from that
will never become obsolete. You just need to translate what you learn into
whatever the latest fashion framework/language call it and ignore the false
hype.

~~~
mbrodersen
For example: people who learned lisp years ago are now laughing about the hype
higher level functions (lambdas etc.) are getting. It is ancient technology.
Same when Java introduced garbage collection. Yet another ancient technology.
However my argument is not that you should learn lisp today to get a job. You
should learn it to understand the fundamental technologies that future
fashionable frameworks/languages will use. Same goes for type theory. Rust is
also using ancient technology (linear types) that you would already have known
about long before Rust showed up if you learned type theory. The next step
after Rush is of course dependent types.

------
AnimalMuppet
When I was in college, I majored in math and physics. Only two math classes
gave me trouble. One was Real Analysis. There were just too many theorems. I
couldn't remember them all, and then I couldn't figure out what to use to
solve the problems on the test.

Eventually I realized that, out of maybe fifty theorems, only maybe three were
used to prove all the others. So I memorized those three, and worked out
anything else I needed for the test on the fly.

You don't need to keep up with the Hotness Of The Week(TM). You need to know
the fundamentals well, and you need to be able to learn the rest _when you
need it_.

------
trelliscoded
3D graphics math is all trig and linear algebra, with some signal processing.
You don't have to know that stuff to use unity to build VR apps, but it helps.
Those skills will never, ever, be obsolete. Even deep learning is rooted in
linear algebra.

The technology churn in other spaces like front end development can be
mitigated by learning to read really fast. I don't have deep experience with
any one front end framework, but I can inhale the docs and source code pretty
fast when I need to get my hands dirty with one. Again, speed reading is a
skill that will never be obsolete.

------
bsvalley
I think you're mixing 2 things. First, what investors are investing in
(AI/VR), then what kind of jobs will tech companies offer in a near future. I
think the second one won't change, what will change will be the visions and
missions of the future companies. There will still be software development for
a while, even if you work for an "AI" company. These are just hot keywords in
2016/2017

------
garysieling
I wouldn't let AI & VR worry you- that type of growth in the field means new
types of jobs.

As far as updating my skillset, I watch conference talks, and I built a site
that has a big index of them:
[https://www.findlectures.com/?p=1&class1=Technology&type1=Co...](https://www.findlectures.com/?p=1&class1=Technology&type1=Conference&talk_type_l2_Conference=Software)

------
bbcbasic
I'm concentrating on learning stuff that fascinates me. This also happens to
be computer science skills that won't go out of date for a while. Some of it
discovered before silicon chips! Even if it won't directly help me in my job
today or getting a new job, it Will help my career in the long term by making
me a better thinker and programmer.

------
jankotek
Do not update it. Technology is actually painfully slow. Maybe you need to
change technology once in ten years (such as moving from C++ to Java).

~~~
webmaven
Whoa there, let's not go overboard. Implementing a decadal cadence for
switching would require budgeting for about a year of reduced earnings while
you build competency in the new platform/language/ecosystem (and the
associated client base).

------
daw___
If you have the possibility then try joining larger and younger teams at work.
Also: be constantly aware of the current state of technology. You can't have a
deep knowledge of everything but at least knowing which problems a new
technology solves helps a lot.

~~~
tobltobs
What is the advantage of larger and younger teams in regards to staying up to
date?

~~~
daw___
You are right, I did not expand on that. Larger teams bring in a potentially
wider set of skills, and your "next" is probably some younger developer's
"current" already.

------
aruaru
Side projects

------
golergka
Fundamentals.

I'm a game developer who have worked in 2d social/mobile lately and am now
getting into VR. Turns out, if you know how rendering pipeline works, it's not
such a foreign land after all.

~~~
big_paps
Can confirm fundamentals. The longer i work as a developer, the more i see the
importance to have a grip of the basics. For me this is mysql, linux, math
rather than new frameworks, languages and build tools.

------
vorotato
Don't hold on to the bleeding edge so tightly and you won't get cut. It's fine
to ride the wave, but don't forget to polish your less specific skills.

------
samblr
Asking this question might help - how could I have learnt what I have learnt
already in very less time. Writing down steps or rules could help narrow down
to current scenario.

------
zxcvvcxz
Here is how it's going for me. For background, over the last few months I've
very quickly become adept in deep learning, being able to understand current
research papers, read through textbooks, implement my own models with
Tensorflow and other libraries, and train real models on remote servers (e.g.
AWS). For reference, I have an engineering background but no formal schooling
passed an undergraduate degree.

The situation: my early-stage startup is fundraising right now, which can be
kind of a time sink. Lots of accelerator/grant/angel applications. There's a
good chance we hit our seed round, but also a good chance I'm unemployed next
quarter when/if runway runs out.

In either case, I decided that AI, specifically deep learning, would be
incredibly important to my career. The startup will need the expertise in the
future (so I'll have to understand how to hire people with it), and should I
need to find another job in a few months, this is a pretty cool field to learn
and I find the work enjoyable (previously was a data scientist but foused more
on vanilla regression and convex methods).

Therefore since November I've portioned out 20 hrs/week to the startup
focusing on its fundraising and BD needs, which leaves a whole lot of other
hours for skills development. Here has been roughly my curriculum:

\- Mathematics review, and basic neural networks. For this I went over
multivariable calculus and lin alg, which I've always been fairly strong, by
essentially trying to derive the backpropagation derivatives for simple
vanilla neural networks. Then make sure I understand derivatives and matrix
data organization for convolution, which is a key component of modern ML.
Sources: pencil and paper, and lots of Google to answer any of my questions.
Time: 1-2 weeks.

\- CS231n online course:
[http://cs231n.stanford.edu/](http://cs231n.stanford.edu/) Great summary of
modern methods in deep learning, plus more foundational level stuff. I read
through all the lecture content and made sure I could work through
derivations, because for me at least this cements technical understanding.
Some of them are sort of tedious, e.g. manual RNN backprop. Also this course
has great and simple software examples, I read through the code to make sure I
understood the numerical computation and data organization parts. I also ran a
few software examples and played around with parameters for fun (and
learning). Time: 1 month.

\- Reading research papers (and online lectures) on applications that interest
me. For this phase, I found 10 initial research papers that interested me. The
topics for myself included image classification (starting w/ classic 2012
Hinton paper), reinforcement learning, robotics applications, video
prediction. This step was harder, can be like learning a new language. Not
every paper is going to make sense at first. But go through enough of them and
you'll build up familiarity. Sources: can start by searching through
reddit.com/r/machinelearning Time: 2 weeks.

\- Learning software frameworks. From the above step I came up with my own
small sample problem related to stuff I read that I could test even on my weak
laptop (remember, training these big networks requires big computing power).
So in this step I started researching different frameworks, and settled on
starting a small project with Keras. Sources: google around for deep learning
libraries, read up on them, see what you like, and most importantly, have a
motivating sample problem that you wanna code up. Time: 2 weeks.

\- Harder problems, more software, more papers. This is where I'm at now, it's
sort of like an iterative research loop where I 1) come up with new problems I
want to solve, 2) learn more about the software I need to implement it, and 3)
search more prior work to gain insights on how I can solve the harder
problems. In particular, I've switched over to learning and using Tensorflow,
and also learning how to use AWS for stronger computing. So I had to dust off
some linux scripting and command line skills too. Like I said, this is fairly
iterative and probably closer to "modern research" where learning from my
(virtual) peers and experimentation and production are closely linked. Time:
from the last month to present.

Overall, in the last 3 months or so at about 30 hrs/week I've added an
extremely powerful new skillset to my arsenal that I've been meaning to do for
quite some time. I can understand 90% of all modern research in the field, and
create useful software to solve data-driven problems. Completely for free as
well, aside from the $0.81/hr I pay to AWS for training some networks
overnight. This is the type of thing I'd have wanted from a Master's (or even
PhD) program, but who wants to go back to school...

Hope this helps someone :) Remember, AI/ML is more approachable than most
people think, you just need to start with a solid mathematics background.
After that you'll be flying, the field is relatively quick to learn,
especially if you like learning through doing.

------
pryelluw
What is your current skillset? Maybe we can help guide you and ease the
anxiety.

------
MichaelBurge
I'm taking a couple courses from Udacity. They have both AI and VR courses.

