November 11, 2024 • 46 mins
Can creativity mean more for software than productivity? Do we need to let go of “hardcore developer stuff”? Will getting more people to major in computer science fix everything? Ashley and Cat chat with Change, Technically’s first guest star SUE SMITH about developer learning and the future of software teams as technology changes.
Credits
Sue Smith, guest
Ashley Juavinett, host + producer
Cat Hicks, host + producer
Danilo Campos, producer + editor
While not mentioned in the episode, we would be remiss if we did not link you to Sue's illustrated collections of HTTP status codes:
- Golden Girls variant
- Keanu Reeves variant
Cat mentioned this paper by Dr. Natasha Quadlin as an example of how the same achievement information can be interpreted very differently by biased viewers during hiring:
Quadlin, N. (2018). The mark of a woman’s record: Gender and academic performance in hiring. American sociological review, 83(2), 331-360.
https://journals.sagepub.com/doi/pdf/10.1177/0003122418762291
Dr. Quadlin has many fascinating projects on inequality and a book with Brian Powell tackling questions about inequality and college: https://www.russellsage.org/publications/who-should-pay
Learn more about Ashley:
Learn more about Cat:
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Sue (00:00):
some of the skills that have been undervalued
historically in softwareengineering are going to come at
the fore.
You know, you're not going to beable to just rely on writing
beautiful code.
Maybe we're going to need toexpect people to communicate and
collaborate and think about thebigger problems.
Cat (00:22):
I'm excited about today's episode, which is our very first
interview.
We have Sue Smith on the showand Sue has an incredible
background coming in to codingthrough some really unique
pathways and then using all ofthat experience and wisdom to
broaden the entry points forother people.
Ashley (00:43):
We're going to talk about the myth of the lone
genius.
We're going to do a lot ofreally weird thought experiments
about how we should bestructuring our teams.
And we're just so excited tohave Sue here as our first
guest.
Sue (00:53):
I was quite late coming to tech.
I was in my late 20s and I waslucky enough to be able to do a
master's course because at thattime the Scottish government was
funding any course to do withsoftware.
They talked about this highdropout rate on computer science
courses as though it was justlike this unavoidable fact that
(01:15):
there was nothing they could doto perhaps figure out how to
teach it more effectively.
The assumption was just it'seither for you or it's not.
You know, tough luck if it'snot.
Probably the people who itturned out it was for were the
ones who had perhaps had accessto a computer at home.
growing up as well, there's noroom for that complacency
(01:35):
anymore because there has been aton of research that has given
us tried and tested techniquesto teach people coding skills
that work.
So I don't know what thosecourses are like.
Now the course I was on actuallyhad a really high teaching
standard and the teaching staffwere very attentive and did
whatever they had to get peoplethrough it.
(01:57):
But in, within the field ingeneral, there just seemed to be
this assumption that we weregoing to inevitably have this
high dropout rate.
Cat (02:05):
If this is not too personal, Sue, how did that make
you feel?
Like you were a person changingyour own life trajectory and
what you were going to work on.
Did you buy into that?
Sue (02:16):
I was tempted to use the word spiteful.
But that would be extreme.
Cat (02:22):
go for it!
Sue (02:23):
they had this assumption that I come from an arts
background, and my degree was inEnglish and philosophy.
And so because my background wasin what they called a non
numeric discipline, there was anassumption that I would struggle
and that I would need access toall these remedial classes and
things like that.
Um, and not to toot my own horn,but that was an incorrect
(02:46):
assumption.
And I'm hopefully now thatthere's better understanding of
the fact that, especially forsoftware development, that that
has a lot in common withlinguistic skills, perhaps more
than it does with mathematicalskills.
And so I was actually in a goodposition to make the most of it.
And I was lucky because I foundthat Whatever an aptitude means,
(03:09):
and I have extreme ambivalenceto that term, but I did find
that I took to it quite easily,um, and I had found something I
was good at, which was great, aswell as it giving me access to
economic opportunity.
But I have a lot of ambivalenceabout that as well, because I
think that I have had theability to make something of the
(03:34):
opportunities that I've had,because of perhaps my being
neurotypical in having access tothe kind of education I had
access to, whereas other peopleprobably wouldn't have been able
to make of the opportunitieswhat I did.
But I would say that that's,that's in a nutshell why I work
(03:57):
in education now.
Because it annoyed the hell outof me that other people were not
getting that experience.
You know, it put my life on atrajectory that I couldn't have
imagined.
Just opportunity, the experienceof life that I have now, I would
never have imagined as a kid.
And it infuriates me that otherpeople don't have that
(04:19):
opportunity and that we gatekeepso severely in tech.
Even requiring people to havedegrees for, you know, Typical
software engineering jobs, whichis totally unnecessary.
And is an example of using theeducation to gatekeep
opportunity rather than toenable people to access it.
Cat (04:39):
The promise is real.
Like the promise of an entryinto power, the ability to do
things.
Like I remember, what code waslike, I genuinely did not know.
And when I was in college,realizing like, Oh, I had no
idea that some people had thislevel of being able to create
(05:00):
things like products and thingslike that.
I just had no idea how any ofthat
Ashley (05:04):
worked.
Sue (05:05):
interesting that you used the word create there because
the thing that struck me as wellcoming from an arts background
was that if anything, once Istarted having access to writing
code, I found it to be a morecreative job.
than perhaps creative writing orwhatever.
Um, and I think there'ssomething in that about having
constraints about how that cankind of stimulate creativity.
(05:29):
And actually the people whostruggled on the course I was
on, the thing that theystruggled with the most,
typically from coming fromscience backgrounds, was the
idea that there wasn't a correctanswer.
So they would give us a problemto solve, a set of requirements,
And then it was up to you, whatyou built, to satisfy those
requirements, but there werepeople who had a really hard
(05:51):
time with the idea that therewasn't, wasn't one right answer,
there wasn't a correct solution.
And of course the students fromthe arts backgrounds didn't have
an issue with that because thatwas normal to them.
Ashley (06:02):
That's something I see in my students too.
Cause I, you know, I primarilywork with biology students and
they're very familiar withclasses where there's one
answer, they memorize something.
There is like a biologicalpathway they're supposed to
know.
And that's it.
And they come into my classroomand they're like, wait, you're
saying I could write the loopthis way, or I could write it
(06:23):
this way, it was like, And forour purposes, they're
equivalent.
And I agree.
That's like something peoplestruggle with.
And I think also this pointabout coding for creativity is
something that.
My students actually love, and Ithink is like for many of them,
especially those who have someartsy inclination or creative
inclination, they come into theclass and I'm like, Whoa, I can
(06:45):
like create things.
And that's actually one of thereasons I would want to learn
how to code.
Like, great.
It'll get me a job later.
It helps me analyze data.
That's all good.
But like, I just made somethingand that's really, really fun.
And that's not something Iexpected.
We saw that in our research andI thought that was really,
really neat.
And I was like, well, I shouldbe selling this for the creative
Part of it, just as much as thecareer path opening part of it.
Sue (07:09):
It's a better motivator, isn't it?
Cat (07:11):
You were talking about the science of helping people stay
in difficult learning, you know,there is a science to it.
And part of that science iscaring about motivation, right?
And yeah.
So I'm thinking, like, Hey,there's actually a lot of
different possible goals astudent might have when they're
showing up or a person mighthave when they're showing up and
paying for a bootcamp orsomething.
(07:32):
And like, absolutely, there arethese big goals about jobs and,
you know, financialtrajectories, but there are also
these like immediate dailyexperiences.
Right.
And I think a lot of my work inpsychology has always been
around, who are we lettingpeople be like, what version of
themselves are we letting thembe?
Sue (07:50):
All of these ideas are super undervalued in the
industry.
You know, the work I do isbasically enabling people to use
developer products and tooling.
Um, and we have to explain thisover and over again, that you
can't make the learningexperience about your product,
that you have to make it about agoal that's meaningful to the
(08:12):
learner.
Because that's the only realmotivator that they're going to
have for you.
to use the thing and it'sespecially the case with the way
that we build software nowbecause it's so modular that we
plug all these littledependencies in together to
create something.
So if you have too heavy a focuson your little piece of the
puzzle you just alienate people.
(08:35):
You really have to center thelearner um in whatever context
they're in and what like yousaid whatever motivator they
have in this that's somethingthat's like super valuable to
people who are trying itperhaps.
Grow adoption for a developerproduct, but it's still really
poorly understood in theindustry.
Cat (08:53):
Yeah.
why is it hard for people to seethis connection?
Sue (08:56):
Economic dynamics, the systemic dynamics in a company
and how certain activities areresourced would, would be a
vague answer to that.
Um, you know, if you havesomeone whose job it is to to
teach people about a productthat's going to be tied to the
(09:17):
life cycle of how you build andrelease that product.
Um, and persuading people inthose kind of circumstances to
think more broadly than that isreally quite challenging because
the way that most organizationsare designed discourages that.
You're meant to stay in yourlane, aren't you?
(09:38):
You're meant to just documentthe thing you were supposed to
document and check that off thelist.
We have a kind of productionline mentality, I think a lot of
the time.
Um, and it's like, I'mpersonally trying to find a
sweet spot where I can enablepeople with technology learning
and add value to a businesswherever it is I happen to be
(10:01):
working.
I'm trying to find the, uh, thetrade off there.
Um, but even if all you careabout is like building adoption
for a product.
You just can't have the mindsetof focusing on your own little
piece of the puzzle because inpractice it's much more complex
than that.
You, we see it a lot, you see itin any developer product when
(10:24):
you look at like maybe theirdocumentation.
You can tell straight awaywhether the thinking along those
terms are not, whether theyunderstand that they're one
piece of a puzzle or not.
Cat (10:34):
Is there an example that comes to mind of like a place
that's really getting this, or atool that happened that came out
that's, that really understoodlike developers as learners or,
you know, and, and got thatright?
Sue (10:46):
I think when you, when you see it done well is where
someone has recognised thattheir tool integrates well with
another one but that's, that'susually quite challenging in
companies as well becausethere's always a kind of risk
aversion around teachingsomething that's beyond your
control.
I'll give you an example fromyears ago because nobody's
(11:09):
around who will care about itanymore.
I worked at a startup that itwas a no code mobile app
development platform and it wasbased on the OpenAPI
specification.
So OpenAPI is a way ofdocumenting an API and you can
use it to automate integration.
(11:29):
But, we found that gettingpeople to author the
specification was reallychallenging, but there was
another start up thatspecialised in that.
And so, one of the first thingsI did, rather than document our
own product, was document how touse this, this other product
with ours.
Cat (11:46):
Strategic.
Sue (11:47):
really cagey about that, because it's somebody else's
product, and you don't know whenit's going to change, or you
don't know if it's going to goaway and all that.
Um,
Cat (11:55):
Hmm
Sue (11:56):
ignoring the reality of dependency on other technology
is just, it's a dead end in, inweb development now because
there's no self containedtechnology anymore.
Ashley (12:09):
this really reminds me of like what I see happen in
open science sometimes, which islike someone makes a tool to do
a really specific thing.
And sometimes there's aconversation about the ecosystem
that the tool lives in, but alot of times people develop the
tool in isolation and thenthere's dependencies on even
like very common.
Python packages, let's say.
And as soon as those things fallthrough, it's like, now the tool
(12:31):
doesn't work and there's noconsideration for that.
So it's interesting to thinkabout these things happening in
industry too.
And like, in some of theseother, like what I would think
of as like more professionaloperations, but I guess this can
still happen.
Sue (12:43):
Yes.
Cat (12:44):
we're hearing out loud, like, you know, the non software
person being like, surely not,
Ashley (12:50):
Surely not.
Cat (12:51):
don't break out there.
Sue (12:53):
It's probably even worse because when you look, it's
going to boil down toincentivization, isn't it?
And you know, what is resourced?
And in industry, there's anaggressive focus on resourcing
the things that are going tobring that return on the
investment that the investorsare looking for in the short
(13:15):
term.
And investing in anything beyondthat is extremely challenging.
Cat (13:22):
Here's something I feel as a person in this world of
technology, which is like to getall this good work done and to
solve some of these complicatedproblems.
We are so often.
in this kind of collaborativecommunal culture that breaks
down barriers betweenorganizations.
(13:44):
And that's like sometimestotally acceptable to those
organizations and sometimes notlike sometimes the work is out
ahead of the organizationalboundaries.
And I think it's reallyinteresting with software
because, you know, you mighthave this.
deeply real, tangibleunderstanding.
Like we've got guys, we've gotto use this framework.
(14:06):
You know, it's, it's just, it'sgoing to be the one, it's going
to be the one five years fromnow, you just can't see it yet.
And I can feel like the stressand the tension of people who I
talked to in my research, whoare trying to advocate for that
and negotiate for that withtheir organizations.
Sometimes there's like this deepempathy that I feel for
developers because they areworking across boundaries in a
(14:27):
similar way to scientists.
I don't know if that resonateswith you, Sue.
Sue (14:31):
It's really interesting that you say that because I was
thinking earlier on about Thefact that we don't do a
fantastic job of creatingcultures of learning there are a
lot of reasons for that.
We don't really have thetraditional engineering
practices of likeapprenticeships and mentoring
the way that other engineeringdisciplines have.
Well, mentoring happens, butit's, it's sort of at the
(14:54):
discretion of people whether todo it or not.
It's not like a baselineexpectation of a software
engineer.
And one of the things that makesit really difficult to create
the conditions for people tolearn and grow inside companies
is also the fact that we havehigh attrition, that we have
turnover of employees and itmakes it really difficult to
create communities of practiceinside companies.
(15:17):
But the conclusion that I kindof came to when I was thinking
about that is that we need tocreate those communities beyond
our organizations.
You know, maybe looking for thatinside a company is barking up
the wrong tree.
Perhaps we need to create humancommunities that form those,
that give us that culture oflearning and give us the space
(15:38):
to support growth.
Cat (15:41):
Developers are coming through my research and they
sound really lonely to me.
They sound like they've had to.
Form a team with people theybarely know.
And then that team getsreconstituted like on a, what an
18 month average cycle orsomething is, I mean, that's not
a cycle of long termrelationships and deep, like
(16:03):
learning together.
And I think that the human costof attrition is really, and like
change just is really, reallyvery salient to people right
now, you know, after like layoffcycles in tech.
Sue (16:17):
When we have learning and development programs in
companies.
It tends to be a kind ofbudgetary exercise.
It's like, it will give you anamount of money off you go and
spend that on a course.
And it kind of puts thatresponsibility for learning and
development on the individualrather than us having a kind of
(16:38):
collective effort at that.
And when, when you look atreally any other engineering
discipline that is radicallydifferent, but it's so
difficult, as you said, tocreate those relationships.
When people are in and out, orpeople are in the door one
minute and out the next.
Ashley (16:54):
I wonder if there's like good examples of community of
practice around like otherthings you know Python and R for
example they have likeconferences and you know groups
associated with them like thesebig communities and I'm
wondering like um, I don't know,are there like, cross company
examples of communities ofpractice that either of you know
of?
Sue (17:13):
Where my mind immediately goes is open source, but
problematic route to go down aswell because it's, It's like
having a massive crisis and it'sum, so much shady nonsense going
on in the world of open sourceand also it's been one of the
mechanisms for gatekeeping thoseopportunities, you know, if you
have to have contributions toopen source on your CV to get a
(17:38):
job, then of course that's goingto buy us, you know, young men
primarily, who have the sparetime to do unpaid labour.
Ashley (17:47):
Yeah.
Sue (17:47):
So my mind goes to open source as a potential place
where that could have happenedbut
Ashley (17:53):
Hmm.
Sue (17:53):
hasn't.
Cat (17:55):
Yeah.
I think about, you know, becauseI'm sort of an intersectional
person who's not a developer,right?
And so maybe my examples aren't,you know, quite in the niche,
but, you know, I think aboutwhen people organize around
problems that they really careabout rather than sort of like,
a jargony line on your resumeabout what language you know.
(18:17):
And so I had this experience,um, When I started working, when
I was doing my researchconsultancy, and I started
working with a friend who wasrunning a small campaign for a
local office, and I was pullingsome data for him, and it was
like looking at road repairs,and this is like state data
(18:39):
sets, you know, that areuploaded in a certain way in
California, and This is people'swhole job, and I knew nothing
about it.
And I remember looking at beinglike, there must be people who
do like this sort of nonprofitcivic data work out there in,
you know, in R, which is thething I knew.
And so I started looking for it.
And I just remember like theabsolute kindest, nicest,
(19:03):
sweetest replies from the oneforum that I asked this in that
were like, absolutely, you'remaking the classic mistake that
everybody makes when they pullthis data and here's someone
wrote a package for it.
And it was so lovely because wewere all completely united
around this problem, which waslike, Hey, how do we help like
local people running for officeaccess and use the data that's
(19:27):
around them?
Sue (19:28):
When we look at successful social movements where people
will organize around a problemand it means that they will come
together from perhaps differentgroups.
And it's kind of taking thatmodel and applying it to a tech
community, isn't it?
Cat (19:42):
totally.
I've been reading a lot about usversus them psychology, and how
we form groups, and how do wedecide at that kind of moment of
ambiguity, are we together inthis, you know, do we have like
what psychologists call a sharedfate, you know, or you outgroup,
you're the other, you know, andI really am struck by this in my
(20:04):
research, software developershave a lot of others.
There's a lot of like, I'm adeveloper, you're not, and I
feel safe because I'm on theingroup side, you're
Ashley (20:14):
you're
Cat (20:15):
Sometimes I challenge people to say, you know, has a
PM ever been really nice to you?
Has a manager ever seen likesomething that you could do that
you haven't, you know, seen inyourself, right?
Like, what would it look like totap into those moments and try
to be that person and form thosealliances?
Yeah.
Sue (20:36):
The developer exceptionalism.
I've heard this expression usedin developer relations.
This idea that developers arethis kind of special species
that no normal human rules applyto.
a lot of people are reallyinvested in that and being part
of that little group, aren'tthey?
Um,
Ashley (20:58):
I'm so curious, as like The non developer here, like the
person's farthest fromdevelopers, like where does that
come from and Who does it serveto have this idea of developer
exceptionalism?
Sue (21:10):
I mean, there's tremendous economic opportunity, or has
been historically, at least, inbeing a software engineer, so
there's, that would be my firstguess at why people are so
invested in it.
And we see, you see a lot of itin the reactions to AI assisted
coding now, um, and to me that'sa basic misunderstanding of what
(21:33):
software engineering is as well,because not writing syntax.
You know, that is not what asoftware engineer does.
That's a detail, you know, butwe talk about these AI assisted
coding tools as if they're goingto make software engineers
obsolete.
Ashley (21:47):
This is a misconception I see in my students all the
time, like they think being aprogrammer is sitting at a
terminal and like hacking intothe mainframe line by line,
right?
And as you pointed out with AI,this is changing.
And you've also developed a lotof tools to help people build
things like code.
And so I guess my question foryou is like, I don't know, is
(22:08):
that something that's acceptedin those communities as like a
legitimate way to be adeveloper?
Or are there people who feellike that's not legitimate?
Cat (22:18):
the easier things are, the less real developing, the less
hardcore they are.
But then we also have thesetechnological advances,
especially in like webdevelopment, right?
That make things way easier thanthey used to be.
So there's like a tension thereor something.
Sue (22:32):
Oh yeah, I mean, they're always going to be the"you're
not a real developer, you're nota real software engineer"
people.
And then other people who willself select as I'm not a real
software engineer, I'm not areal developer.
And, you know, the history ofsoftware engineering is these
waves of increasing abstraction.
(22:52):
And all of the tools that we'retalking about are just new
levels of abstraction.
What I've started to do in morerecent years is to stop
describing what I do asdeveloper learning and stop
using the word developer you dothat people will kind of self
select out of the group.
They'll say well that's not forme I don't really care if
someone sees themselves as adeveloper or not.
(23:14):
I'm trying to enable people tobuild with software.
Ashley (23:17):
In neuroscience, if we get a tool, like, for example,
in recent years, there's these,AI models that can like map an
animal moving through space andthis is like really useful in a
lot of experiments wherenormally, or I should say like
20 years ago, you might have hada college student watching a
mouse move around an arena andthey would sit there and like
manually tag, okay, this iswhere the mouse's nose is and
(23:38):
this is where its tail is.
Right.
And now we have AI models thatdo this In a second.
And no one in neuroscience issaying that's not real
neuroscience.
You know, we're saying, Oh, mygoodness, give me that tool.
Let me get to the answerquicker, you know, and let's get
to the next thing.
And I hear this like happeningreally differently in some of
these like developer tools thatyou're working on.
Sue (24:01):
Totally and I've, my kind of baseline assumption is that
if something can be automatedand still done effectively then
there's something better for thehuman being to spend their time
doing.
is that our ability to pay therent and have food and clothing
and all that is dependent ondoing some of these activities
(24:23):
and you know there are a lot ofexecutives who think these tools
are going to reduce theirdependence on employees, but in
general, I feel like ifsomething's automatable, then
why would, why would a humanwant to waste their time on that
task?
You know, surely there'ssomething more interesting for
them to be doing.
Cat (24:43):
when I studied this and people's beliefs around AI
obviously tapped into people'svery deep beliefs about all
kinds of things that would bethere, whether it was AI or some
other thing, some other economicchange that was like the beliefs
like My boss understands whatI'm doing.
So they're not going to makeludicrous, ridiculous decisions
(25:05):
because they don't understandit.
You know, that's a reallyimportant thing to believe.
There's also the community ofpractice piece I saw really come
in for developers because peoplewere sort of
Ashley (25:16):
tool
Cat (25:17):
Am I supposed to be using this tool in this way?
What do we all think?
It's like a moment of, you know,Deep ambiguity and uncertainty
because there's a lot of mixedmessages and I, sorry to be the
psych nerd, but like, I justkept going to the in group out
group psych stuff because a lotof that gets so heightened in
moments of uncertainty, You havea bunch of layoffs and you have
(25:38):
a bunch of new tools coming in,you know, and you have massive
media scrutiny of what it meansto do your job.
I've seen people move from astate of real paralysis And fear
and into a state of being like,okay, look, I am an engineer.
I can think about this like anengineering problem.
I can audit the edge cases.
(25:59):
I can bring all these skills tothis moment.
And that was a cool thing thatwe did this AI pre mortem where
we just asked people surface,all the fears and the doubts and
the things you feel like you'rewondering if other people are
thinking.
Sue (26:14):
I love it.
And I mean, I think what we'regoing to find is that some of
the skills that have beenundervalued historically in
software engineering are goingto come at the fore.
You know, you're not going to beable to just rely on writing
beautiful code.
Maybe we're going to need toexpect people to communicate and
collaborate and think about thebigger problems.
(26:35):
You know, one of the biggestaspects of software engineering
now is managing complexity.
We're not gonna be able toautomate that for a very long
time, if ever.
And so I think we're going tosee that there's an emphasis on
different skills.
Some of them may be the onesthat we call soft skills.
are going to start to come tothe fore as actually the more
valuable skills that arerequired to deliver a solution
(26:58):
to a problem.
Cat (27:00):
From my vantage point as a VP of research at a company that
develops, you know, skill basedlearning products for technology
teams, 1 million percent that isat the forefront.
And I really wish we wouldn'talways call it soft skills
because sometimes it's like, asyou know, I can see it on your
face, you know, deeply, likethese are very intertwined with
(27:23):
building intertwined, twinedwith creation, you know, skills,
but.
I think about all those peoplewho tried this stuff one time
and got told they didn't have aprogramming brain.
And now we don't have thosepeople to meet that,
Ashley (27:36):
didn't How do you teach those skills?
How do you select for thoseskills, especially when people
came up like through softwareengineering in a particular way?
Like what does that look like insort of your ideal world?
Sue (27:48):
I mean I think I would unapologetically say don't hire
the people who come from thetraditional backgrounds, like
hire people who come from thenon traditional backgrounds who
didn't have access to the.
qualifications and who perhapshave done other jobs, maybe low
paid jobs in other industriesbecause you're probably going to
find that they have a lot ofthose skills walking in.
Cat (28:11):
I used to think about as a kind of radical thought
experiment, what if we just hada total moratorium on hiring
from like, So there are like top10 computer science programs,
right, out there, especially inthe U.
S.
They're very dominant at largetech companies.
I mean, you know, I'll say incasual conversations in San
Francisco, I heard people justsay that's the only places
(28:33):
they'd hire from, I used to havethis thought experiment as I'd
walk around that was like, whatif we just made it, You could
not hire from any of thosedegreed programs and you for
three years, we could only hirenon degreed software developers.
What would that do?
I'm not proposing that as asolution, cause that's obviously
(28:54):
a deeply unethical humanexperiment,
Ashley (28:56):
maybe there's a way to think about this instead of,
like, instead of cutting thosepeople out, let's, like, try to
get all the linguistics andphilosophy majors, like, into
programming and see how thatchanges how people think about
some of these problems.
I'll join you in
Cat (29:10):
I'll join you in the spiteful, you see, you talked
about being driven byspitefulness earlier and like
Sue, you know, sometimes I havethis feeling of like, can we
just point out computer science
Ashley (29:21):
power to
Cat (29:21):
Like if they're not meeting the needs of a holistic student
population, if they'resystematically failing groups in
society, they're failing at theeducational outcomes and goals
that we've said these
Ashley (29:32):
you know,
Cat (29:33):
And we always make the problem about
Ashley (29:35):
fields
Cat (29:35):
or the people, you know, instead of the problem being,
why on earth have these fieldsfailed to desegregate?
Other fields have
Ashley (29:45):
to serve.
Cat (29:46):
Other fields are making more
Ashley (29:48):
and things
Cat (29:49):
This field is really digging its heels in and that's
a failure of who it's supposedto
Ashley (29:54):
is
Sue (29:54):
I think there's a strong argument that a more effective
way to teach these skills wouldbe.
through a more vocational typeof tradition.
You know, these are practical,uh, industry skills, and the
idea that you would teach thatthrough an academic path, I
think, is pretty questionable.
Anyway, you know, not all acomputer science degree can do
(30:15):
for you is give you afoundation.
As soon as you enter theworkplace, everything's changing
constantly.
Probably all the technologiesyou've learned are obsolete
already.
Um, you know, it can give youthe foundation and teach you how
to pick up technologies.
But I think that shifting to amore vocational model would
probably solve a lot of thoseproblems anyway.
Cat (30:38):
Yeah, you mentioned apprenticeships and things like
that, right?
Sue (30:41):
Yeah, but then you have the, this is something that I
think is really tricky.
And you and I had a briefexchange about this on Social
Media Cat about, you were to doan apprenticeship program,
Cat (30:52):
Mm.
Sue (30:53):
would you select for that?
Yeah.
in a way that minimized bias,you know, what, how would you
pick, how would you fill thatpipeline?
You know, any kind of idea ofaptitude, as soon as you start
digging into that, it becomesreally problematic, doesn't it?
Cat (31:09):
Okay, I have a second radical thought experiment for
you.
So this is something I'vethought, I've made this argument
before about grad schooladmissions and admissions for
college.
I think we have reasonablecriteria sometimes to say
someone is not set up to succeedin this program.
And Ashley would say, no, saymore about this, but like, you
(31:29):
know, there is a, there is areason to say we want to know
people have certain things, youknow, in place before they can
benefit from this program.
So there's a reason for that.
that.
when things are really, reallycompetitive, you get in this
situation where we have a bunchof people that we basically
can't meaningfully discriminatebetween.
Like My radical thoughtexperiment is Do a fricking
(31:51):
lottery and for a limited, ifyou have a limited number of
spots, just randomly admit
Ashley (31:57):
could think
Cat (31:58):
I think it behooves us to admit when we don't know how to
predict human potential.
And when our efforts to do thathave been really damaging.
And that was the argument thatpeople made for establishing a
public school system, you whatwe think people deserve as like
a right, like the right toeducation.
That's something that we didn'talways have.
(32:20):
And it's actually pretty recent,you know, and we don't really
have that problem solved when itcomes to college.
So I feel that deeply.
You know, my mom didn't finishcollege and went back to school
later in life.
My grandfather was the firstperson in his family to go past
eighth grade.
Like, it's so incredibly deeplypersonal to me.
(32:43):
The fact that I have a PhD feelsso unlikely, you know, and, um,
just like you did, I, I lookaround at the things that made
me capable of doing that.
And I'm like, a lot of this hadnothing to do with whether I
deserved this.
It was.
It was really some good luck andlike I worked really hard But it
was some really some really goodluck and there's so many
(33:04):
deserving people who didn't havethat
Sue (33:07):
Totally.
I have really ambivalentfeelings about that as well.
Living in a country where wedon't pay tuition fees, Because
there's like no shortage of overqualified people who still are
under hired because they comefrom an under represented group
or whatever.
I'm really uncomfortable assomeone working in education
with the myth that educationprovides like equity of access
(33:30):
to opportunity because it justdoesn't, does it?
And in a lot of ways it kind oflegitimizes the fact that we
don't have that equity.
One of the things that What I'vetried to do in companies is to
use access to an educationresource or whatever with a
training course or acertification or whatever to
(33:51):
maybe prioritizeunderrepresented groups.
So one of the things we did inthe past was we had this program
that resulted in a certificationand we just prioritized the
training that I delivered.
to like HBCUs or the nonexploitative boot camps of which
there were a few.
(34:12):
Um, but then the, the realitythat I hadn't quite fully
grasped was that, that itdoesn't really matter because
there are like no shortage of,let's say for example, black
women who are like ludicrouslyoverqualified for jobs that they
don't get hired for, but thatlike a white man will walk into
(34:33):
with no relevant qualificationand experience.
So something that I've ended uphaving a bit of discomfort with
is just offering education asthis pathway to opportunity.
You know, I think we need tofind to leverage it in
conjunction with measures andone of the things I've thought
(34:55):
about doing, but I've nevermanaged to pull it off yet.
would be to maybe partner with acompany that like hires for a
particular skill set ortechnology um to co author a
learning experience but as partof that have them agree that
they will prioritize the peoplewho've completed this in their
(35:16):
hiring pipeline Maybe they'reguaranteed a certain interview
or whatever and then prioritizeaccess to the education path,
but in a way you're, you're sortof using the myth, you're kind
of manipulating the, this liethat education provides access
by cobbling all these piecestogether to make it actually
(35:39):
provide access to that
Cat (35:40):
appreciate you bringing this up, I think it speaks to
like change is not easy at all.
And you're like very bravelyacknowledging that like it's
not, it's never going to belike, Oh my gosh, everybody go
to college.
And then suddenly when everybodygoes to college, the bar gets
moved to something else, There'sa paper that I always like to
send people, which is called,um, A Mark of a Woman's Record
(36:01):
is the name of this title,paper.
And, um, it talks about how thesame grade on a male or a female
resume is interpreted
Ashley (36:10):
feel like
Cat (36:12):
you know, by the person who reads it.
And you're, you're making, ofcourse, racial bias, so many
other identities come in andhave this same different effect.
This is something that I feellike it's really hard for people
who haven't thought about it towrap their head around, like,
the same achievement does notfunction the same way for
different people.
And that's the root problem, notpresence or lack of education.
(36:36):
You know, the root problem isthe bias, yeah.
Sue (36:39):
Totally.
And it's the same inorganizations, you know, when we
talk about things likepsychological safety and how
learn, we have to be able tofail and make mistakes and all
that.
But like, if you're like asingle mother or whatever, and
you're the only person on yourteam who's not like a young man,
(36:59):
like you better not makemistakes.
You make too many mistakes.
Come performance review cycle,you're more likely to get marked
down for it.
You're more likely to beoverlooked for promotion or let
go.
When there's a layoff cycle, youknow, the, the real factors
affecting that safety are thesystemic.
(37:20):
You know, and the only way we'regoing to improve that is by
improving representation,especially in positions of
seniority and organizations.
I think education can play arole in that, but like there's
only so much we can do at thelevel of a learning experience
to address that.
Ashley (37:39):
Yeah, I feel like what I hear you saying is like the
systemic and structural changesare really what's needed, like
building pipelines, not justbuilding like opportunities, but
really making sure people getthrough one stage and have a
spot in the next stage.
Otherwise, you allow the bias tocreep in when they're trying to
transition stages and move up.
(37:59):
What do they do after that?
And how do you guarantee thatthey're going to succeed after
that?
And there's a lot of work bylike the national institutes of
health in the U S to try tobuild pipelines for people to
move through, which is I think abetter direction to go in.
Yeah, we're not going to fixeverybody's bias, but we can
build some supports to make surethose students get catapulted to
(38:21):
the next stage.
Cat (38:23):
It's so easy to be like, oh my gosh, it's so beautiful to
have all of these peoplelearning to code who wouldn't
have learned to code.
But then you're like, well,okay, the flip side is do the
managers know how to treat thosepeople?
Are they getting fairperformance reviews?
You know, if you have thisdinosaur, everybody walks around
and treats like carefully, youknow, and oh, everybody knows
(38:45):
that this person's, you know,just really harsh on all the
women on the software team,who's going to do something
about that?
And what message does it send?
I think a lot about this becauseI've done some work on learning
cultures.
And I think a lot about the factthat if you encounter that
hypocrisy, if you get onemessage that you can learn and
you get another message that,Yeah, but we're not going to
(39:07):
protect learning at the expenseof hurting this one guy's
feelings.
What message do we walk awayfrom with, you know?
Of course we walk away with themessage that is like learning is
not as important as protectingthis guy's feelings.
Sue (39:20):
And if only we had the evidence to show the impact that
that one genius that tanks theentire team's productivity.
You know, we wouldn't even haveto make those arguments, but we
still have this genius softwareengineer mentality that like one
person can possibly contributeenough to a problem or an
(39:44):
organization that makes itworthwhile that they make
everybody else less successful.
Cat (39:51):
you know, I'll just say over and over again, we have
that evidence.
we do.
Like there was just an HBRarticle just published that
summarized it.
That
Ashley (39:59):
it.
It
Cat (40:00):
toxic productive person costs businesses, like an
enormous amount.
We do have that evidence.
I think we need in engineeringcircles, like the will to use
that evidence.
This is not remotely towardssomeone like you, who is
obviously out there on the frontline fighting this.
This is maybe to somebodylistening to this, who's a
(40:20):
little bit like, you know,scared to raise that inside of
their team or theirorganization.
We really do have that evidenceand I would encourage people to
try to use it.
Sue (40:32):
Is anybody using it?
Cat (40:33):
I think so.
I, I hear people talk to meabout their sort of middle of
the road startup that is at apoint where they might go one
way or the other way, culturallyspeaking, and that they've
walked into a room and said, Iwant us to think about.
How we're doing hiring, youknow, or I want us to think
(40:55):
about whether we're actuallygoing to partner with this org
that everybody says has thisperson, you know, at it and what
message would that send to likeour female users, for instance,
you know, so I do think thesebattles are being fought.
I really do, because I get a lotof emails about this kind of
thing.
Ashley (41:14):
I mean, I, I sort of wanted to come back to something
Sue was getting at earlier,which was like, The difference
between having the focus be onpeople trying to be really good
developers versus the focusbeing, we're here to solve a
problem all together and we'lldo whatever it takes to solve
that problem.
And it feels like, you know,this gets at the in group, out
(41:34):
group thing, right?
Because it's like, if you're allin the in group trying to solve
a problem together and comingback to the social movements
thing, it's like, Is that a, anorienting principle that we can
use on our teams to get peopleto like, just kind of like
detach from themselves a littlebit, like get out of the, the
insecurity and the likequestions about their own
identity and focus on a biggerthing, like something bigger
(41:56):
than themselves.
I don't know.
Is that, is that a knob we canturn?
Yeah.
Sue (42:03):
when I did that course that I found something I was good at.
And the fact that I went throughschool, primary school,
secondary school, and didn'tfind anything that I was good
at, it shows that that waspretty much a failed experiment.
And I think most people probablyhave that experience.
But when we're able to do moreshared learning like that, more
(42:25):
kind of, more project basedgroups, group learning where
people are bringing their owncontribution to a shared
pursuit.
I feel like we're probablybetter able to create the
conditions for people to findout what kind of contribution
they, they do like to make.
Ashley (42:42):
Yeah, I agree with you that doing this early is really
important.
And I think like the, the thingI often grapple with when we do
this in the classroom atuniversity is like, it's tied to
grades as well.
And so students, you know,don't, they, they do the group
work, but they're maybepredominantly concerned about
the grade that they're getting.
Something I think about iscreating low stakes group work
(43:05):
opportunities where maybe it'slike not tied to your grade and
you can actually learn what itfeels like to be in a group
setting without that kind ofthing at stake.
And then maybe you can take thatinto the workplace afterwards.
But yeah, I think a lot abouthow do you teach people some of
these things, like what it meansto work in a group and actually
to get value out of group workin the same way you might get
(43:26):
value out of an individualcontribution that you might have
made.
Sue (43:31):
I think we have the same problem in industry because
people are wanting to get thegood performance review score,
get a higher salary or whatever,and it really is similar to
grading.
Ashley (43:45):
What if we like leveled up teams instead of individuals?
Cat (43:48):
you, know, a couple, a year ago or so when everyone on
social media was going, having abreakdown about what developer
productivity is, was like, so ifyou so deeply don't believe in
believe this individualperformance model is failing us,
you know, you don't think weshould even talk about it.
Are you going to advocate forteams to be promoted together?
(44:09):
Like holistically, are you goingto share a promotion with
somebody?
You know, how about, let's sayyour promotion?
Will you walk into work and say,listen, um, yes, I'm the
software developer, but alsothis 25 year old, you know, PM
who's on this other team, um, Ithink she should get a promotion
with us as well.
And by the way, I took a look atthe fact that we have different
(44:31):
bonus ratios The fact that Ihave a higher bonus percentage,
just cause I'm a developer, eventhough this person's sitting
next to my team, again, radicalthought
Ashley (44:39):
experiments.
Sue (44:40):
And like you're describing the kind of people who have the
most positive impact on thesuccess of an organisation.
That, like, that's how they doit, they do it by, like, we win
together, we lift other peopleup.
Even, like, the idea ofdeveloper productivity is such a
red flag to me because, when Ilook back at my own career, the
(45:00):
times when I've had the mostimpact are typically the times
when I've not been the mostproductive I've had the space to
think and reflect and to betargeted in where I dedicated my
efforts instead of being like onthis production line trying to
churn out as much output aspossible and getting nowhere and
(45:21):
not actually contributing to thesuccess of the organisation I
was working for in the way thatI have.
When I have been able to havethat time and space to not be
productive.
Cat (45:33):
Yeah.
It sounds like that's a veryparticular version of
productivity.
Like you weren't like productionproductive, but you were were
effective, right?
Sue (45:41):
I suppose it would depend on what we mean, why we even use
that term.
It's like, it's not, we're notchurning out cars.
Like it's more, it's a creativepursuit.
It's more complex.
You're trying to create acertain outcome the amount of
hours worked or whatever isjust, really has no bearing on
(46:02):
success.
Ashley (46:04):
Like maybe we need to value creative as much as we
value productive, right?
some of the skills that have been undervalued
historically in softwareengineering are going to come at
the fore.
You know, you're not going to beable to just rely on writing
beautiful code.
Maybe we're going to need toexpect people to communicate and
collaborate and think about thebigger problems.
Cat (00:22):
I'm excited about today's episode, which is our very first
interview.
We have Sue Smith on the showand Sue has an incredible
background coming in to codingthrough some really unique
pathways and then using all ofthat experience and wisdom to
broaden the entry points forother people.
Ashley (00:43):
We're going to talk about the myth of the lone
genius.
We're going to do a lot ofreally weird thought experiments
about how we should bestructuring our teams.
And we're just so excited tohave Sue here as our first
guest.
Sue (00:53):
I was quite late coming to tech.
I was in my late 20s and I waslucky enough to be able to do a
master's course because at thattime the Scottish government was
funding any course to do withsoftware.
They talked about this highdropout rate on computer science
courses as though it was justlike this unavoidable fact that
(01:15):
there was nothing they could doto perhaps figure out how to
teach it more effectively.
The assumption was just it'seither for you or it's not.
You know, tough luck if it'snot.
Probably the people who itturned out it was for were the
ones who had perhaps had accessto a computer at home.
growing up as well, there's noroom for that complacency
(01:35):
anymore because there has been aton of research that has given
us tried and tested techniquesto teach people coding skills
that work.
So I don't know what thosecourses are like.
Now the course I was on actuallyhad a really high teaching
standard and the teaching staffwere very attentive and did
whatever they had to get peoplethrough it.
(01:57):
But in, within the field ingeneral, there just seemed to be
this assumption that we weregoing to inevitably have this
high dropout rate.
Cat (02:05):
If this is not too personal, Sue, how did that make
you feel?
Like you were a person changingyour own life trajectory and
what you were going to work on.
Did you buy into that?
Sue (02:16):
I was tempted to use the word spiteful.
But that would be extreme.
Cat (02:22):
go for it!
Sue (02:23):
they had this assumption that I come from an arts
background, and my degree was inEnglish and philosophy.
And so because my background wasin what they called a non
numeric discipline, there was anassumption that I would struggle
and that I would need access toall these remedial classes and
things like that.
Um, and not to toot my own horn,but that was an incorrect
(02:46):
assumption.
And I'm hopefully now thatthere's better understanding of
the fact that, especially forsoftware development, that that
has a lot in common withlinguistic skills, perhaps more
than it does with mathematicalskills.
And so I was actually in a goodposition to make the most of it.
And I was lucky because I foundthat Whatever an aptitude means,
(03:09):
and I have extreme ambivalenceto that term, but I did find
that I took to it quite easily,um, and I had found something I
was good at, which was great, aswell as it giving me access to
economic opportunity.
But I have a lot of ambivalenceabout that as well, because I
think that I have had theability to make something of the
(03:34):
opportunities that I've had,because of perhaps my being
neurotypical in having access tothe kind of education I had
access to, whereas other peopleprobably wouldn't have been able
to make of the opportunitieswhat I did.
But I would say that that's,that's in a nutshell why I work
(03:57):
in education now.
Because it annoyed the hell outof me that other people were not
getting that experience.
You know, it put my life on atrajectory that I couldn't have
imagined.
Just opportunity, the experienceof life that I have now, I would
never have imagined as a kid.
And it infuriates me that otherpeople don't have that
(04:19):
opportunity and that we gatekeepso severely in tech.
Even requiring people to havedegrees for, you know, Typical
software engineering jobs, whichis totally unnecessary.
And is an example of using theeducation to gatekeep
opportunity rather than toenable people to access it.
Cat (04:39):
The promise is real.
Like the promise of an entryinto power, the ability to do
things.
Like I remember, what code waslike, I genuinely did not know.
And when I was in college,realizing like, Oh, I had no
idea that some people had thislevel of being able to create
(05:00):
things like products and thingslike that.
I just had no idea how any ofthat
Ashley (05:04):
worked.
Sue (05:05):
interesting that you used the word create there because
the thing that struck me as wellcoming from an arts background
was that if anything, once Istarted having access to writing
code, I found it to be a morecreative job.
than perhaps creative writing orwhatever.
Um, and I think there'ssomething in that about having
constraints about how that cankind of stimulate creativity.
(05:29):
And actually the people whostruggled on the course I was
on, the thing that theystruggled with the most,
typically from coming fromscience backgrounds, was the
idea that there wasn't a correctanswer.
So they would give us a problemto solve, a set of requirements,
And then it was up to you, whatyou built, to satisfy those
requirements, but there werepeople who had a really hard
(05:51):
time with the idea that therewasn't, wasn't one right answer,
there wasn't a correct solution.
And of course the students fromthe arts backgrounds didn't have
an issue with that because thatwas normal to them.
Ashley (06:02):
That's something I see in my students too.
Cause I, you know, I primarilywork with biology students and
they're very familiar withclasses where there's one
answer, they memorize something.
There is like a biologicalpathway they're supposed to
know.
And that's it.
And they come into my classroomand they're like, wait, you're
saying I could write the loopthis way, or I could write it
(06:23):
this way, it was like, And forour purposes, they're
equivalent.
And I agree.
That's like something peoplestruggle with.
And I think also this pointabout coding for creativity is
something that.
My students actually love, and Ithink is like for many of them,
especially those who have someartsy inclination or creative
inclination, they come into theclass and I'm like, Whoa, I can
(06:45):
like create things.
And that's actually one of thereasons I would want to learn
how to code.
Like, great.
It'll get me a job later.
It helps me analyze data.
That's all good.
But like, I just made somethingand that's really, really fun.
And that's not something Iexpected.
We saw that in our research andI thought that was really,
really neat.
And I was like, well, I shouldbe selling this for the creative
Part of it, just as much as thecareer path opening part of it.
Sue (07:09):
It's a better motivator, isn't it?
Cat (07:11):
You were talking about the science of helping people stay
in difficult learning, you know,there is a science to it.
And part of that science iscaring about motivation, right?
And yeah.
So I'm thinking, like, Hey,there's actually a lot of
different possible goals astudent might have when they're
showing up or a person mighthave when they're showing up and
paying for a bootcamp orsomething.
(07:32):
And like, absolutely, there arethese big goals about jobs and,
you know, financialtrajectories, but there are also
these like immediate dailyexperiences.
Right.
And I think a lot of my work inpsychology has always been
around, who are we lettingpeople be like, what version of
themselves are we letting thembe?
Sue (07:50):
All of these ideas are super undervalued in the
industry.
You know, the work I do isbasically enabling people to use
developer products and tooling.
Um, and we have to explain thisover and over again, that you
can't make the learningexperience about your product,
that you have to make it about agoal that's meaningful to the
(08:12):
learner.
Because that's the only realmotivator that they're going to
have for you.
to use the thing and it'sespecially the case with the way
that we build software nowbecause it's so modular that we
plug all these littledependencies in together to
create something.
So if you have too heavy a focuson your little piece of the
puzzle you just alienate people.
(08:35):
You really have to center thelearner um in whatever context
they're in and what like yousaid whatever motivator they
have in this that's somethingthat's like super valuable to
people who are trying itperhaps.
Grow adoption for a developerproduct, but it's still really
poorly understood in theindustry.
Cat (08:53):
Yeah.
why is it hard for people to seethis connection?
Sue (08:56):
Economic dynamics, the systemic dynamics in a company
and how certain activities areresourced would, would be a
vague answer to that.
Um, you know, if you havesomeone whose job it is to to
teach people about a productthat's going to be tied to the
(09:17):
life cycle of how you build andrelease that product.
Um, and persuading people inthose kind of circumstances to
think more broadly than that isreally quite challenging because
the way that most organizationsare designed discourages that.
You're meant to stay in yourlane, aren't you?
(09:38):
You're meant to just documentthe thing you were supposed to
document and check that off thelist.
We have a kind of productionline mentality, I think a lot of
the time.
Um, and it's like, I'mpersonally trying to find a
sweet spot where I can enablepeople with technology learning
and add value to a businesswherever it is I happen to be
(10:01):
working.
I'm trying to find the, uh, thetrade off there.
Um, but even if all you careabout is like building adoption
for a product.
You just can't have the mindsetof focusing on your own little
piece of the puzzle because inpractice it's much more complex
than that.
You, we see it a lot, you see itin any developer product when
(10:24):
you look at like maybe theirdocumentation.
You can tell straight awaywhether the thinking along those
terms are not, whether theyunderstand that they're one
piece of a puzzle or not.
Cat (10:34):
Is there an example that comes to mind of like a place
that's really getting this, or atool that happened that came out
that's, that really understoodlike developers as learners or,
you know, and, and got thatright?
Sue (10:46):
I think when you, when you see it done well is where
someone has recognised thattheir tool integrates well with
another one but that's, that'susually quite challenging in
companies as well becausethere's always a kind of risk
aversion around teachingsomething that's beyond your
control.
I'll give you an example fromyears ago because nobody's
(11:09):
around who will care about itanymore.
I worked at a startup that itwas a no code mobile app
development platform and it wasbased on the OpenAPI
specification.
So OpenAPI is a way ofdocumenting an API and you can
use it to automate integration.
(11:29):
But, we found that gettingpeople to author the
specification was reallychallenging, but there was
another start up thatspecialised in that.
And so, one of the first thingsI did, rather than document our
own product, was document how touse this, this other product
with ours.
Cat (11:46):
Strategic.
Sue (11:47):
really cagey about that, because it's somebody else's
product, and you don't know whenit's going to change, or you
don't know if it's going to goaway and all that.
Um,
Cat (11:55):
Hmm
Sue (11:56):
ignoring the reality of dependency on other technology
is just, it's a dead end in, inweb development now because
there's no self containedtechnology anymore.
Ashley (12:09):
this really reminds me of like what I see happen in
open science sometimes, which islike someone makes a tool to do
a really specific thing.
And sometimes there's aconversation about the ecosystem
that the tool lives in, but alot of times people develop the
tool in isolation and thenthere's dependencies on even
like very common.
Python packages, let's say.
And as soon as those things fallthrough, it's like, now the tool
(12:31):
doesn't work and there's noconsideration for that.
So it's interesting to thinkabout these things happening in
industry too.
And like, in some of theseother, like what I would think
of as like more professionaloperations, but I guess this can
still happen.
Sue (12:43):
Yes.
Cat (12:44):
we're hearing out loud, like, you know, the non software
person being like, surely not,
Ashley (12:50):
Surely not.
Cat (12:51):
don't break out there.
Sue (12:53):
It's probably even worse because when you look, it's
going to boil down toincentivization, isn't it?
And you know, what is resourced?
And in industry, there's anaggressive focus on resourcing
the things that are going tobring that return on the
investment that the investorsare looking for in the short
(13:15):
term.
And investing in anything beyondthat is extremely challenging.
Cat (13:22):
Here's something I feel as a person in this world of
technology, which is like to getall this good work done and to
solve some of these complicatedproblems.
We are so often.
in this kind of collaborativecommunal culture that breaks
down barriers betweenorganizations.
(13:44):
And that's like sometimestotally acceptable to those
organizations and sometimes notlike sometimes the work is out
ahead of the organizationalboundaries.
And I think it's reallyinteresting with software
because, you know, you mighthave this.
deeply real, tangibleunderstanding.
Like we've got guys, we've gotto use this framework.
(14:06):
You know, it's, it's just, it'sgoing to be the one, it's going
to be the one five years fromnow, you just can't see it yet.
And I can feel like the stressand the tension of people who I
talked to in my research, whoare trying to advocate for that
and negotiate for that withtheir organizations.
Sometimes there's like this deepempathy that I feel for
developers because they areworking across boundaries in a
(14:27):
similar way to scientists.
I don't know if that resonateswith you, Sue.
Sue (14:31):
It's really interesting that you say that because I was
thinking earlier on about Thefact that we don't do a
fantastic job of creatingcultures of learning there are a
lot of reasons for that.
We don't really have thetraditional engineering
practices of likeapprenticeships and mentoring
the way that other engineeringdisciplines have.
Well, mentoring happens, butit's, it's sort of at the
(14:54):
discretion of people whether todo it or not.
It's not like a baselineexpectation of a software
engineer.
And one of the things that makesit really difficult to create
the conditions for people tolearn and grow inside companies
is also the fact that we havehigh attrition, that we have
turnover of employees and itmakes it really difficult to
create communities of practiceinside companies.
(15:17):
But the conclusion that I kindof came to when I was thinking
about that is that we need tocreate those communities beyond
our organizations.
You know, maybe looking for thatinside a company is barking up
the wrong tree.
Perhaps we need to create humancommunities that form those,
that give us that culture oflearning and give us the space
(15:38):
to support growth.
Cat (15:41):
Developers are coming through my research and they
sound really lonely to me.
They sound like they've had to.
Form a team with people theybarely know.
And then that team getsreconstituted like on a, what an
18 month average cycle orsomething is, I mean, that's not
a cycle of long termrelationships and deep, like
(16:03):
learning together.
And I think that the human costof attrition is really, and like
change just is really, reallyvery salient to people right
now, you know, after like layoffcycles in tech.
Sue (16:17):
When we have learning and development programs in
companies.
It tends to be a kind ofbudgetary exercise.
It's like, it will give you anamount of money off you go and
spend that on a course.
And it kind of puts thatresponsibility for learning and
development on the individualrather than us having a kind of
(16:38):
collective effort at that.
And when, when you look atreally any other engineering
discipline that is radicallydifferent, but it's so
difficult, as you said, tocreate those relationships.
When people are in and out, orpeople are in the door one
minute and out the next.
Ashley (16:54):
I wonder if there's like good examples of community of
practice around like otherthings you know Python and R for
example they have likeconferences and you know groups
associated with them like thesebig communities and I'm
wondering like um, I don't know,are there like, cross company
examples of communities ofpractice that either of you know
of?
Sue (17:13):
Where my mind immediately goes is open source, but
problematic route to go down aswell because it's, It's like
having a massive crisis and it'sum, so much shady nonsense going
on in the world of open sourceand also it's been one of the
mechanisms for gatekeeping thoseopportunities, you know, if you
have to have contributions toopen source on your CV to get a
(17:38):
job, then of course that's goingto buy us, you know, young men
primarily, who have the sparetime to do unpaid labour.
Ashley (17:47):
Yeah.
Sue (17:47):
So my mind goes to open source as a potential place
where that could have happenedbut
Ashley (17:53):
Hmm.
Sue (17:53):
hasn't.
Cat (17:55):
Yeah.
I think about, you know, becauseI'm sort of an intersectional
person who's not a developer,right?
And so maybe my examples aren't,you know, quite in the niche,
but, you know, I think aboutwhen people organize around
problems that they really careabout rather than sort of like,
a jargony line on your resumeabout what language you know.
(18:17):
And so I had this experience,um, When I started working, when
I was doing my researchconsultancy, and I started
working with a friend who wasrunning a small campaign for a
local office, and I was pullingsome data for him, and it was
like looking at road repairs,and this is like state data
(18:39):
sets, you know, that areuploaded in a certain way in
California, and This is people'swhole job, and I knew nothing
about it.
And I remember looking at beinglike, there must be people who
do like this sort of nonprofitcivic data work out there in,
you know, in R, which is thething I knew.
And so I started looking for it.
And I just remember like theabsolute kindest, nicest,
(19:03):
sweetest replies from the oneforum that I asked this in that
were like, absolutely, you'remaking the classic mistake that
everybody makes when they pullthis data and here's someone
wrote a package for it.
And it was so lovely because wewere all completely united
around this problem, which waslike, Hey, how do we help like
local people running for officeaccess and use the data that's
(19:27):
around them?
Sue (19:28):
When we look at successful social movements where people
will organize around a problemand it means that they will come
together from perhaps differentgroups.
And it's kind of taking thatmodel and applying it to a tech
community, isn't it?
Cat (19:42):
totally.
I've been reading a lot about usversus them psychology, and how
we form groups, and how do wedecide at that kind of moment of
ambiguity, are we together inthis, you know, do we have like
what psychologists call a sharedfate, you know, or you outgroup,
you're the other, you know, andI really am struck by this in my
(20:04):
research, software developershave a lot of others.
There's a lot of like, I'm adeveloper, you're not, and I
feel safe because I'm on theingroup side, you're
Ashley (20:14):
you're
Cat (20:15):
Sometimes I challenge people to say, you know, has a
PM ever been really nice to you?
Has a manager ever seen likesomething that you could do that
you haven't, you know, seen inyourself, right?
Like, what would it look like totap into those moments and try
to be that person and form thosealliances?
Yeah.
Sue (20:36):
The developer exceptionalism.
I've heard this expression usedin developer relations.
This idea that developers arethis kind of special species
that no normal human rules applyto.
a lot of people are reallyinvested in that and being part
of that little group, aren'tthey?
Um,
Ashley (20:58):
I'm so curious, as like The non developer here, like the
person's farthest fromdevelopers, like where does that
come from and Who does it serveto have this idea of developer
exceptionalism?
Sue (21:10):
I mean, there's tremendous economic opportunity, or has
been historically, at least, inbeing a software engineer, so
there's, that would be my firstguess at why people are so
invested in it.
And we see, you see a lot of itin the reactions to AI assisted
coding now, um, and to me that'sa basic misunderstanding of what
(21:33):
software engineering is as well,because not writing syntax.
You know, that is not what asoftware engineer does.
That's a detail, you know, butwe talk about these AI assisted
coding tools as if they're goingto make software engineers
obsolete.
Ashley (21:47):
This is a misconception I see in my students all the
time, like they think being aprogrammer is sitting at a
terminal and like hacking intothe mainframe line by line,
right?
And as you pointed out with AI,this is changing.
And you've also developed a lotof tools to help people build
things like code.
And so I guess my question foryou is like, I don't know, is
(22:08):
that something that's acceptedin those communities as like a
legitimate way to be adeveloper?
Or are there people who feellike that's not legitimate?
Cat (22:18):
the easier things are, the less real developing, the less
hardcore they are.
But then we also have thesetechnological advances,
especially in like webdevelopment, right?
That make things way easier thanthey used to be.
So there's like a tension thereor something.
Sue (22:32):
Oh yeah, I mean, they're always going to be the"you're
not a real developer, you're nota real software engineer"
people.
And then other people who willself select as I'm not a real
software engineer, I'm not areal developer.
And, you know, the history ofsoftware engineering is these
waves of increasing abstraction.
(22:52):
And all of the tools that we'retalking about are just new
levels of abstraction.
What I've started to do in morerecent years is to stop
describing what I do asdeveloper learning and stop
using the word developer you dothat people will kind of self
select out of the group.
They'll say well that's not forme I don't really care if
someone sees themselves as adeveloper or not.
(23:14):
I'm trying to enable people tobuild with software.
Ashley (23:17):
In neuroscience, if we get a tool, like, for example,
in recent years, there's these,AI models that can like map an
animal moving through space andthis is like really useful in a
lot of experiments wherenormally, or I should say like
20 years ago, you might have hada college student watching a
mouse move around an arena andthey would sit there and like
manually tag, okay, this iswhere the mouse's nose is and
(23:38):
this is where its tail is.
Right.
And now we have AI models thatdo this In a second.
And no one in neuroscience issaying that's not real
neuroscience.
You know, we're saying, Oh, mygoodness, give me that tool.
Let me get to the answerquicker, you know, and let's get
to the next thing.
And I hear this like happeningreally differently in some of
these like developer tools thatyou're working on.
Sue (24:01):
Totally and I've, my kind of baseline assumption is that
if something can be automatedand still done effectively then
there's something better for thehuman being to spend their time
doing.
is that our ability to pay therent and have food and clothing
and all that is dependent ondoing some of these activities
(24:23):
and you know there are a lot ofexecutives who think these tools
are going to reduce theirdependence on employees, but in
general, I feel like ifsomething's automatable, then
why would, why would a humanwant to waste their time on that
task?
You know, surely there'ssomething more interesting for
them to be doing.
Cat (24:43):
when I studied this and people's beliefs around AI
obviously tapped into people'svery deep beliefs about all
kinds of things that would bethere, whether it was AI or some
other thing, some other economicchange that was like the beliefs
like My boss understands whatI'm doing.
So they're not going to makeludicrous, ridiculous decisions
(25:05):
because they don't understandit.
You know, that's a reallyimportant thing to believe.
There's also the community ofpractice piece I saw really come
in for developers because peoplewere sort of
Ashley (25:16):
tool
Cat (25:17):
Am I supposed to be using this tool in this way?
What do we all think?
It's like a moment of, you know,Deep ambiguity and uncertainty
because there's a lot of mixedmessages and I, sorry to be the
psych nerd, but like, I justkept going to the in group out
group psych stuff because a lotof that gets so heightened in
moments of uncertainty, You havea bunch of layoffs and you have
(25:38):
a bunch of new tools coming in,you know, and you have massive
media scrutiny of what it meansto do your job.
I've seen people move from astate of real paralysis And fear
and into a state of being like,okay, look, I am an engineer.
I can think about this like anengineering problem.
I can audit the edge cases.
(25:59):
I can bring all these skills tothis moment.
And that was a cool thing thatwe did this AI pre mortem where
we just asked people surface,all the fears and the doubts and
the things you feel like you'rewondering if other people are
thinking.
Sue (26:14):
I love it.
And I mean, I think what we'regoing to find is that some of
the skills that have beenundervalued historically in
software engineering are goingto come at the fore.
You know, you're not going to beable to just rely on writing
beautiful code.
Maybe we're going to need toexpect people to communicate and
collaborate and think about thebigger problems.
(26:35):
You know, one of the biggestaspects of software engineering
now is managing complexity.
We're not gonna be able toautomate that for a very long
time, if ever.
And so I think we're going tosee that there's an emphasis on
different skills.
Some of them may be the onesthat we call soft skills.
are going to start to come tothe fore as actually the more
valuable skills that arerequired to deliver a solution
(26:58):
to a problem.
Cat (27:00):
From my vantage point as a VP of research at a company that
develops, you know, skill basedlearning products for technology
teams, 1 million percent that isat the forefront.
And I really wish we wouldn'talways call it soft skills
because sometimes it's like, asyou know, I can see it on your
face, you know, deeply, likethese are very intertwined with
(27:23):
building intertwined, twinedwith creation, you know, skills,
but.
I think about all those peoplewho tried this stuff one time
and got told they didn't have aprogramming brain.
And now we don't have thosepeople to meet that,
Ashley (27:36):
didn't How do you teach those skills?
How do you select for thoseskills, especially when people
came up like through softwareengineering in a particular way?
Like what does that look like insort of your ideal world?
Sue (27:48):
I mean I think I would unapologetically say don't hire
the people who come from thetraditional backgrounds, like
hire people who come from thenon traditional backgrounds who
didn't have access to the.
qualifications and who perhapshave done other jobs, maybe low
paid jobs in other industriesbecause you're probably going to
find that they have a lot ofthose skills walking in.
Cat (28:11):
I used to think about as a kind of radical thought
experiment, what if we just hada total moratorium on hiring
from like, So there are like top10 computer science programs,
right, out there, especially inthe U.
S.
They're very dominant at largetech companies.
I mean, you know, I'll say incasual conversations in San
Francisco, I heard people justsay that's the only places
(28:33):
they'd hire from, I used to havethis thought experiment as I'd
walk around that was like, whatif we just made it, You could
not hire from any of thosedegreed programs and you for
three years, we could only hirenon degreed software developers.
What would that do?
I'm not proposing that as asolution, cause that's obviously
(28:54):
a deeply unethical humanexperiment,
Ashley (28:56):
maybe there's a way to think about this instead of,
like, instead of cutting thosepeople out, let's, like, try to
get all the linguistics andphilosophy majors, like, into
programming and see how thatchanges how people think about
some of these problems.
I'll join you in
Cat (29:10):
I'll join you in the spiteful, you see, you talked
about being driven byspitefulness earlier and like
Sue, you know, sometimes I havethis feeling of like, can we
just point out computer science
Ashley (29:21):
power to
Cat (29:21):
Like if they're not meeting the needs of a holistic student
population, if they'resystematically failing groups in
society, they're failing at theeducational outcomes and goals
that we've said these
Ashley (29:32):
you know,
Cat (29:33):
And we always make the problem about
Ashley (29:35):
fields
Cat (29:35):
or the people, you know, instead of the problem being,
why on earth have these fieldsfailed to desegregate?
Other fields have
Ashley (29:45):
to serve.
Cat (29:46):
Other fields are making more
Ashley (29:48):
and things
Cat (29:49):
This field is really digging its heels in and that's
a failure of who it's supposedto
Ashley (29:54):
is
Sue (29:54):
I think there's a strong argument that a more effective
way to teach these skills wouldbe.
through a more vocational typeof tradition.
You know, these are practical,uh, industry skills, and the
idea that you would teach thatthrough an academic path, I
think, is pretty questionable.
Anyway, you know, not all acomputer science degree can do
(30:15):
for you is give you afoundation.
As soon as you enter theworkplace, everything's changing
constantly.
Probably all the technologiesyou've learned are obsolete
already.
Um, you know, it can give youthe foundation and teach you how
to pick up technologies.
But I think that shifting to amore vocational model would
probably solve a lot of thoseproblems anyway.
Cat (30:38):
Yeah, you mentioned apprenticeships and things like
that, right?
Sue (30:41):
Yeah, but then you have the, this is something that I
think is really tricky.
And you and I had a briefexchange about this on Social
Media Cat about, you were to doan apprenticeship program,
Cat (30:52):
Mm.
Sue (30:53):
would you select for that?
Yeah.
in a way that minimized bias,you know, what, how would you
pick, how would you fill thatpipeline?
You know, any kind of idea ofaptitude, as soon as you start
digging into that, it becomesreally problematic, doesn't it?
Cat (31:09):
Okay, I have a second radical thought experiment for
you.
So this is something I'vethought, I've made this argument
before about grad schooladmissions and admissions for
college.
I think we have reasonablecriteria sometimes to say
someone is not set up to succeedin this program.
And Ashley would say, no, saymore about this, but like, you
(31:29):
know, there is a, there is areason to say we want to know
people have certain things, youknow, in place before they can
benefit from this program.
So there's a reason for that.
that.
when things are really, reallycompetitive, you get in this
situation where we have a bunchof people that we basically
can't meaningfully discriminatebetween.
Like My radical thoughtexperiment is Do a fricking
(31:51):
lottery and for a limited, ifyou have a limited number of
spots, just randomly admit
Ashley (31:57):
could think
Cat (31:58):
I think it behooves us to admit when we don't know how to
predict human potential.
And when our efforts to do thathave been really damaging.
And that was the argument thatpeople made for establishing a
public school system, you whatwe think people deserve as like
a right, like the right toeducation.
That's something that we didn'talways have.
(32:20):
And it's actually pretty recent,you know, and we don't really
have that problem solved when itcomes to college.
So I feel that deeply.
You know, my mom didn't finishcollege and went back to school
later in life.
My grandfather was the firstperson in his family to go past
eighth grade.
Like, it's so incredibly deeplypersonal to me.
(32:43):
The fact that I have a PhD feelsso unlikely, you know, and, um,
just like you did, I, I lookaround at the things that made
me capable of doing that.
And I'm like, a lot of this hadnothing to do with whether I
deserved this.
It was.
It was really some good luck andlike I worked really hard But it
was some really some really goodluck and there's so many
(33:04):
deserving people who didn't havethat
Sue (33:07):
Totally.
I have really ambivalentfeelings about that as well.
Living in a country where wedon't pay tuition fees, Because
there's like no shortage of overqualified people who still are
under hired because they comefrom an under represented group
or whatever.
I'm really uncomfortable assomeone working in education
with the myth that educationprovides like equity of access
(33:30):
to opportunity because it justdoesn't, does it?
And in a lot of ways it kind oflegitimizes the fact that we
don't have that equity.
One of the things that What I'vetried to do in companies is to
use access to an educationresource or whatever with a
training course or acertification or whatever to
(33:51):
maybe prioritizeunderrepresented groups.
So one of the things we did inthe past was we had this program
that resulted in a certificationand we just prioritized the
training that I delivered.
to like HBCUs or the nonexploitative boot camps of which
there were a few.
(34:12):
Um, but then the, the realitythat I hadn't quite fully
grasped was that, that itdoesn't really matter because
there are like no shortage of,let's say for example, black
women who are like ludicrouslyoverqualified for jobs that they
don't get hired for, but thatlike a white man will walk into
(34:33):
with no relevant qualificationand experience.
So something that I've ended uphaving a bit of discomfort with
is just offering education asthis pathway to opportunity.
You know, I think we need tofind to leverage it in
conjunction with measures andone of the things I've thought
(34:55):
about doing, but I've nevermanaged to pull it off yet.
would be to maybe partner with acompany that like hires for a
particular skill set ortechnology um to co author a
learning experience but as partof that have them agree that
they will prioritize the peoplewho've completed this in their
(35:16):
hiring pipeline Maybe they'reguaranteed a certain interview
or whatever and then prioritizeaccess to the education path,
but in a way you're, you're sortof using the myth, you're kind
of manipulating the, this liethat education provides access
by cobbling all these piecestogether to make it actually
(35:39):
provide access to that
Cat (35:40):
appreciate you bringing this up, I think it speaks to
like change is not easy at all.
And you're like very bravelyacknowledging that like it's
not, it's never going to belike, Oh my gosh, everybody go
to college.
And then suddenly when everybodygoes to college, the bar gets
moved to something else, There'sa paper that I always like to
send people, which is called,um, A Mark of a Woman's Record
(36:01):
is the name of this title,paper.
And, um, it talks about how thesame grade on a male or a female
resume is interpreted
Ashley (36:10):
feel like
Cat (36:12):
you know, by the person who reads it.
And you're, you're making, ofcourse, racial bias, so many
other identities come in andhave this same different effect.
This is something that I feellike it's really hard for people
who haven't thought about it towrap their head around, like,
the same achievement does notfunction the same way for
different people.
And that's the root problem, notpresence or lack of education.
(36:36):
You know, the root problem isthe bias, yeah.
Sue (36:39):
Totally.
And it's the same inorganizations, you know, when we
talk about things likepsychological safety and how
learn, we have to be able tofail and make mistakes and all
that.
But like, if you're like asingle mother or whatever, and
you're the only person on yourteam who's not like a young man,
(36:59):
like you better not makemistakes.
You make too many mistakes.
Come performance review cycle,you're more likely to get marked
down for it.
You're more likely to beoverlooked for promotion or let
go.
When there's a layoff cycle, youknow, the, the real factors
affecting that safety are thesystemic.
(37:20):
You know, and the only way we'regoing to improve that is by
improving representation,especially in positions of
seniority and organizations.
I think education can play arole in that, but like there's
only so much we can do at thelevel of a learning experience
to address that.
Ashley (37:39):
Yeah, I feel like what I hear you saying is like the
systemic and structural changesare really what's needed, like
building pipelines, not justbuilding like opportunities, but
really making sure people getthrough one stage and have a
spot in the next stage.
Otherwise, you allow the bias tocreep in when they're trying to
transition stages and move up.
(37:59):
What do they do after that?
And how do you guarantee thatthey're going to succeed after
that?
And there's a lot of work bylike the national institutes of
health in the U S to try tobuild pipelines for people to
move through, which is I think abetter direction to go in.
Yeah, we're not going to fixeverybody's bias, but we can
build some supports to make surethose students get catapulted to
(38:21):
the next stage.
Cat (38:23):
It's so easy to be like, oh my gosh, it's so beautiful to
have all of these peoplelearning to code who wouldn't
have learned to code.
But then you're like, well,okay, the flip side is do the
managers know how to treat thosepeople?
Are they getting fairperformance reviews?
You know, if you have thisdinosaur, everybody walks around
and treats like carefully, youknow, and oh, everybody knows
(38:45):
that this person's, you know,just really harsh on all the
women on the software team,who's going to do something
about that?
And what message does it send?
I think a lot about this becauseI've done some work on learning
cultures.
And I think a lot about the factthat if you encounter that
hypocrisy, if you get onemessage that you can learn and
you get another message that,Yeah, but we're not going to
(39:07):
protect learning at the expenseof hurting this one guy's
feelings.
What message do we walk awayfrom with, you know?
Of course we walk away with themessage that is like learning is
not as important as protectingthis guy's feelings.
Sue (39:20):
And if only we had the evidence to show the impact that
that one genius that tanks theentire team's productivity.
You know, we wouldn't even haveto make those arguments, but we
still have this genius softwareengineer mentality that like one
person can possibly contributeenough to a problem or an
(39:44):
organization that makes itworthwhile that they make
everybody else less successful.
Cat (39:51):
you know, I'll just say over and over again, we have
that evidence.
we do.
Like there was just an HBRarticle just published that
summarized it.
That
Ashley (39:59):
it.
It
Cat (40:00):
toxic productive person costs businesses, like an
enormous amount.
We do have that evidence.
I think we need in engineeringcircles, like the will to use
that evidence.
This is not remotely towardssomeone like you, who is
obviously out there on the frontline fighting this.
This is maybe to somebodylistening to this, who's a
(40:20):
little bit like, you know,scared to raise that inside of
their team or theirorganization.
We really do have that evidenceand I would encourage people to
try to use it.
Sue (40:32):
Is anybody using it?
Cat (40:33):
I think so.
I, I hear people talk to meabout their sort of middle of
the road startup that is at apoint where they might go one
way or the other way, culturallyspeaking, and that they've
walked into a room and said, Iwant us to think about.
How we're doing hiring, youknow, or I want us to think
(40:55):
about whether we're actuallygoing to partner with this org
that everybody says has thisperson, you know, at it and what
message would that send to likeour female users, for instance,
you know, so I do think thesebattles are being fought.
I really do, because I get a lotof emails about this kind of
thing.
Ashley (41:14):
I mean, I, I sort of wanted to come back to something
Sue was getting at earlier,which was like, The difference
between having the focus be onpeople trying to be really good
developers versus the focusbeing, we're here to solve a
problem all together and we'lldo whatever it takes to solve
that problem.
And it feels like, you know,this gets at the in group, out
(41:34):
group thing, right?
Because it's like, if you're allin the in group trying to solve
a problem together and comingback to the social movements
thing, it's like, Is that a, anorienting principle that we can
use on our teams to get peopleto like, just kind of like
detach from themselves a littlebit, like get out of the, the
insecurity and the likequestions about their own
identity and focus on a biggerthing, like something bigger
(41:56):
than themselves.
I don't know.
Is that, is that a knob we canturn?
Yeah.
Sue (42:03):
when I did that course that I found something I was good at.
And the fact that I went throughschool, primary school,
secondary school, and didn'tfind anything that I was good
at, it shows that that waspretty much a failed experiment.
And I think most people probablyhave that experience.
But when we're able to do moreshared learning like that, more
(42:25):
kind of, more project basedgroups, group learning where
people are bringing their owncontribution to a shared
pursuit.
I feel like we're probablybetter able to create the
conditions for people to findout what kind of contribution
they, they do like to make.
Ashley (42:42):
Yeah, I agree with you that doing this early is really
important.
And I think like the, the thingI often grapple with when we do
this in the classroom atuniversity is like, it's tied to
grades as well.
And so students, you know,don't, they, they do the group
work, but they're maybepredominantly concerned about
the grade that they're getting.
Something I think about iscreating low stakes group work
(43:05):
opportunities where maybe it'slike not tied to your grade and
you can actually learn what itfeels like to be in a group
setting without that kind ofthing at stake.
And then maybe you can take thatinto the workplace afterwards.
But yeah, I think a lot abouthow do you teach people some of
these things, like what it meansto work in a group and actually
to get value out of group workin the same way you might get
(43:26):
value out of an individualcontribution that you might have
made.
Sue (43:31):
I think we have the same problem in industry because
people are wanting to get thegood performance review score,
get a higher salary or whatever,and it really is similar to
grading.
Ashley (43:45):
What if we like leveled up teams instead of individuals?
Cat (43:48):
you, know, a couple, a year ago or so when everyone on
social media was going, having abreakdown about what developer
productivity is, was like, so ifyou so deeply don't believe in
believe this individualperformance model is failing us,
you know, you don't think weshould even talk about it.
Are you going to advocate forteams to be promoted together?
(44:09):
Like holistically, are you goingto share a promotion with
somebody?
You know, how about, let's sayyour promotion?
Will you walk into work and say,listen, um, yes, I'm the
software developer, but alsothis 25 year old, you know, PM
who's on this other team, um, Ithink she should get a promotion
with us as well.
And by the way, I took a look atthe fact that we have different
(44:31):
bonus ratios The fact that Ihave a higher bonus percentage,
just cause I'm a developer, eventhough this person's sitting
next to my team, again, radicalthought
Ashley (44:39):
experiments.
Sue (44:40):
And like you're describing the kind of people who have the
most positive impact on thesuccess of an organisation.
That, like, that's how they doit, they do it by, like, we win
together, we lift other peopleup.
Even, like, the idea ofdeveloper productivity is such a
red flag to me because, when Ilook back at my own career, the
(45:00):
times when I've had the mostimpact are typically the times
when I've not been the mostproductive I've had the space to
think and reflect and to betargeted in where I dedicated my
efforts instead of being like onthis production line trying to
churn out as much output aspossible and getting nowhere and
(45:21):
not actually contributing to thesuccess of the organisation I
was working for in the way thatI have.
When I have been able to havethat time and space to not be
productive.
Cat (45:33):
Yeah.
It sounds like that's a veryparticular version of
productivity.
Like you weren't like productionproductive, but you were were
effective, right?
Sue (45:41):
I suppose it would depend on what we mean, why we even use
that term.
It's like, it's not, we're notchurning out cars.
Like it's more, it's a creativepursuit.
It's more complex.
You're trying to create acertain outcome the amount of
hours worked or whatever isjust, really has no bearing on
(46:02):
success.
Ashley (46:04):
Like maybe we need to value creative as much as we
value productive, right?
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